Human&AI Mastery Program
A program for managing AI not as a ‘tool’, but as a cognitive partner.
Many organizations say, ‘We’re using AI.’
But the real questions are:
Many organizations say, ‘We’re using AI.’ But the real questions are:
Many organizations say, ‘We’re using AI.’ But the real questions are:
Who does which work?
When AI produces an output, who is accountable for the decision?
Where does AI recommend and where does it actually execute?
Who does which work?
When AI produces an output, who is accountable for the decision?
Where does AI recommend and where does it actually execute?
Many organizations say, ‘We’re using AI.’
But the real questions are:
Who does which
work?
When AI produces an output, who is accountable for the decision?
Where does AI recommend and where does it actually execute?
Who does which work?
When AI produces an output, who is accountable for the decision?
Where does AI recommend and where does it actually execute?
What We Deliver
Role clarity (who does what?)
We define the working boundaries of humans and AI: Who creates, who reviews, who approves and who is ultimately accountable.
Decision clarity (who owns which decision?)
Kritik karar noktalarını çıkarır, ‘sorumluluk haritası’ oluştururuz: Yapay zeka önerir mi, karar verir mi, uygular mı, sınırları belirleriz.
Measurement clarity (how will we see the value?)
Not ‘we implemented AI’, but impact: Time saved, fewer errors, lower risk, customer outcomes, cost/revenue effect. We make it measurable.
Trust clarity (risk is not a brake design it in)
We turn ethics, security, regulation, and transparency into design parameters, not after-the-fact controls: how much authority AI has in which work, when humans intervene, what needs to be logged/tracked.
Leadership clarity
Leaders can answer the question, ‘What are we asking AI to do?’, and accountability doesn’t get lost.
Schedule a call for a detailed needs assessment.
Why Human&AI Mastery?
As AI spreads fast, the following basics are still unclear in most organizations:
Who does the work and with what level of responsibility?
Where does AI recommend, and where does it act?
How do ethics, security, regulation, and transparency become design parameters, not ‘friction’?
We remove uncertainty by designing human–machine harmony at an organizational level. The result is an operating model that produces outcomes with AI, controlled, measured, and sustainable.
What We Do
Human&AI Mastery Foundation
The core rules for working with AI raising cognitive capability for individuals and leaders. We build the ‘observer muscle’, balance intuition and rationality, and develop cognitive alignment practices reducing where humans and AI collide or duplicate effort.
Human–AI Collaboration Lab
We redesign critical roles and responsibilities for working with AI in real conditions (human-in-the-loop / on-the-loop). We produce an augmented role blueprint and a practical delegation logic.
Human–AI Practice Lab
We enable the sustainability of human–AI collaboration. For leaders and teams, we provide a practical space to build the muscles of asking the right questions, evaluating outputs with evidence and context, recognizing bias and hallucinations, accelerating without transferring accountability, and communicating effectively with AI.
Who Is It For?
Organizations that want to move AI transformation from pilot to scale
C-level / board leaders who want AI’s business impact to be visible and measurable
Teams building hybrid ways of working across product, operations, marketing, sales, technology, risk, finance, and people & culture
Organizations that want to manage Responsible AI, security, and reputation risk at the design level
Those who want to make AI’s business impact visible on the board agenda
Teams already using AI daily but struggling to standardize ways of working
Leaders who want to increase AI usage without losing quality and risk control
Professionals producing outcomes with AI in functions such as marketing, product, tech, operations, sales, risk, finance, and HR
Collaboration Steps
Human&AI Mastery Discovery Call (goals + risk areas + context)
Diagnosis Workshop (current state + barriers)
Decision Intelligence Workshop (critical decision portfolio + KPIs)
Human-AI Operating Model Design (roles/accountability + protocols)
Mastery Modules + Implementation Sprints (practice + measurement + iteration)
Executive Readout & Roadmap (90 days / 6 months / 12 months)
Outcomes
Standard operating protocols for human–AI collaboration
A shared leadership language: not an “AI project,” but a decision and value system
Clear success criteria and KPI set that makes AI’s business impact visible
A Decision Intelligence-based roadmap for critical decisions
A Responsible AI approach that reduces trust, compliance, and reputation risk
What We Deliver
01
02
03
04
05
Role clarity (who does what?)
We define the working boundaries of humans and AI: Who creates, who reviews, who approves and who is ultimately accountable.
Decision clarity (who owns which decision?)
We map critical decision points and build an accountability map: Does AI recommend, decide, or execute, where are the boundaries?
Measurement clarity (how will we see the value?)
Not ‘we implemented AI’, but impact: Time saved, fewer errors, lower risk, customer outcomes, cost/revenue effect. We make it measurable.
GÜVEN NETLİĞİ (RİSK FREN DEĞİL, TASARIM OLSUN)
We turn ethics, security, regulation, and transparency into design parameters, not after-the-fact controls: how much authority AI has in which work, when humans intervene, what needs to be logged/tracked.
Leadership clarity
Leaders can answer the question, ‘What are we asking AI to do?’, and accountability doesn’t get lost.
Schedule a call for a detailed needs assessment.
What We Deliver
01
02
03
04
05
Role clarity (who does what?)
We define the working boundaries of humans and AI: Who creates, who reviews, who approves and who is ultimately accountable.
Decision clarity (who owns which decision?)
We map critical decision points and build an accountability map: Does AI recommend, decide, or execute, where are the boundaries?
Measurement clarity (how will we see the value?)
Not ‘we implemented AI’, but impact: Time saved, fewer errors, lower risk, customer outcomes, cost/revenue effect. We make it measurable.
GÜVEN NETLİĞİ (RİSK FREN DEĞİL, TASARIM OLSUN)
We turn ethics, security, regulation, and transparency into design parameters, not after-the-fact controls: how much authority AI has in which work, when humans intervene, what needs to be logged/tracked.
Leadership clarity
Leaders can answer the question, ‘What are we asking AI to do?’, and accountability doesn’t get lost.
Schedule a call for a detailed needs assessment.
Why Human&AI Mastery?
As AI spreads fast, the following basics are still unclear in most organizations:
Who does the work and with what level of responsibility?
Where does AI recommend, and where does it act?
How do ethics, security, regulation, and transparency become design parameters, not ‘friction’?
We remove uncertainty by designing human–machine harmony at an organizational level. The result is an operating model that produces outcomes with AI, controlled, measured, and sustainable.
What We Do
Human&AI Mastery Foundation
The core rules for working with AI raising cognitive capability for individuals and leaders. We build the ‘observer muscle’, balance intuition and rationality, and develop cognitive alignment practices reducing where humans and AI collide or duplicate effort.
Human–AI Collaboration Lab
We redesign critical roles and responsibilities for working with AI in real conditions (human-in-the-loop / on-the-loop). We produce an augmented role blueprint and a practical delegation logic.
Human–AI Practice Lab
We enable the sustainability of human–AI collaboration. For leaders and teams, we provide a practical space to build the muscles of asking the right questions, evaluating outputs with evidence and context, recognizing bias and hallucinations, accelerating without transferring accountability, and communicating effectively with AI.
Human&AI Mastery Foundation
The core rules for working with AI raising cognitive capability for individuals and leaders. We build the ‘observer muscle’, balance intuition and rationality, and develop cognitive alignment practices reducing where humans and AI collide or duplicate effort.
Human–AI Collaboration Lab
We redesign critical roles and responsibilities for working with AI in real conditions (human-in-the-loop / on-the-loop). We produce an augmented role blueprint and a practical delegation logic.
Human–AI Practice Lab
We enable the sustainability of human–AI collaboration. For leaders and teams, we provide a practical space to build the muscles of asking the right questions, evaluating outputs with evidence and context, recognizing bias and hallucinations, accelerating without transferring accountability, and communicating effectively with AI.
Who Is It For?
Organizations that want to move AI transformation from pilot to scale
C-level / board leaders who want AI’s business impact to be visible and measurable
Teams building hybrid ways of working across product, operations, marketing, sales, technology, risk, finance, and people & culture
Organizations that want to manage Responsible AI, security, and reputation risk at the design level
Teams already using AI daily but struggling to standardize ways of working
Those who want to make AI’s business impact visible on the board agenda
Leaders who want to increase AI usage without losing quality and risk control
Professionals producing outcomes with AI in functions such as marketing, product, tech, operations, sales, risk, finance, and HR
Who Is It For?
Organizations that want to move AI transformation from pilot to scale
C-level / board leaders who want AI’s business impact to be visible and measurable
Teams building hybrid ways of working across product, operations, marketing, sales, technology, risk, finance, and people & culture
Organizations that want to manage Responsible AI, security, and reputation risk at the design level
Teams already using AI daily but struggling to standardize ways of working
Those who want to make AI’s business impact visible on the board agenda
Leaders who want to increase AI usage without losing quality and risk control
Professionals producing outcomes with AI in functions such as marketing, product, tech, operations, sales, risk, finance, and HR
Collaboration Steps
Human&AI Mastery Discovery Call (goals + risk areas + context)
Human&AI Mastery Discovery Call (goals + risk areas + context)
Diagnosis Workshop (current state + barriers)
Diagnosis Workshop (current state + barriers)
Decision Intelligence Workshop (critical decision portfolio + KPIs)
Decision Intelligence Workshop (critical decision portfolio + KPIs)
Human-AI Operating Model Design (roles/accountability + protocols)
Human-AI Operating Model Design (roles/accountability + protocols)
Mastery Modules + Implementation Sprints (practice + measurement + iteration)
Mastery Modules + Implementation Sprints (practice + measurement + iteration)
Executive Readout & Roadmap (90 days / 6 months / 12 months)
Executive Readout & Roadmap (90 days / 6 months / 12 months)
Outcomes
Clear success criteria and KPI set that makes AI’s business impact visible
A Decision Intelligence-based roadmap for critical decisions
A Responsible AI approach that reduces trust, compliance, and reputation risk
A shared leadership language: not an “AI project,” but a decision and value system
Standard operating protocols for human–AI collaboration
What We Deliver
Role clarity (who does what?)
We define the working boundaries of humans and AI: Who creates, who reviews, who approves and who is ultimately accountable.
Decision clarity (who owns which decision?)
Kritik karar noktalarını çıkarır, ‘sorumluluk haritası’ oluştururuz: Yapay zeka önerir mi, karar verir mi, uygular mı, sınırları belirleriz.
Measurement clarity (how will we see the value?)
Not ‘we implemented AI’, but impact: Time saved, fewer errors, lower risk, customer outcomes, cost/revenue effect. We make it measurable.
Trust clarity (risk is not a brake design it in)
We turn ethics, security, regulation, and transparency into design parameters, not after-the-fact controls: how much authority AI has in which work, when humans intervene, what needs to be logged/tracked.
Leadership clarity
Leaders can answer the question, ‘What are we asking AI to do?’, and accountability doesn’t get lost.
Schedule a call for a detailed needs assessment.
Why Human&AI Mastery?
As AI spreads fast, the following basics are still unclear in most organizations:
Who does the work and with what level of responsibility?
Where does AI recommend, and where does it act?
How do ethics, security, regulation, and transparency become design parameters, not ‘friction’?
We remove uncertainty by designing human–machine harmony at an organizational level. The result is an operating model that produces outcomes with AI, controlled, measured, and sustainable.
What We Do
Human&AI Mastery Foundation
The core rules for working with AI raising cognitive capability for individuals and leaders. We build the ‘observer muscle’, balance intuition and rationality, and develop cognitive alignment practices reducing where humans and AI collide or duplicate effort.
Human–AI Collaboration Lab
We redesign critical roles and responsibilities for working with AI in real conditions (human-in-the-loop / on-the-loop). We produce an augmented role blueprint and a practical delegation logic.
Human–AI Practice Lab
We enable the sustainability of human–AI collaboration. For leaders and teams, we provide a practical space to build the muscles of asking the right questions, evaluating outputs with evidence and context, recognizing bias and hallucinations, accelerating without transferring accountability, and communicating effectively with AI.
Who Is It For?
Organizations that want to move AI transformation from pilot to scale
C-level / board leaders who want AI’s business impact to be visible and measurable
Teams building hybrid ways of working across product, operations, marketing, sales, technology, risk, finance, and people & culture
Organizations that want to manage Responsible AI, security, and reputation risk at the design level
Those who want to make AI’s business impact visible on the board agenda
Teams already using AI daily but struggling to standardize ways of working
Leaders who want to increase AI usage without losing quality and risk control
Professionals producing outcomes with AI in functions such as marketing, product, tech, operations, sales, risk, finance, and HR
Collaboration Steps
Human&AI Mastery Discovery Call (goals + risk areas + context)
Diagnosis Workshop (current state + barriers)
Decision Intelligence Workshop (critical decision portfolio + KPIs)
Human-AI Operating Model Design (roles/accountability + protocols)
Mastery Modules + Implementation Sprints (practice + measurement + iteration)
Executive Readout & Roadmap (90 days / 6 months / 12 months)
Outcomes
Standard operating protocols for human–AI collaboration
A shared leadership language: not an “AI project,” but a decision and value system
Clear success criteria and KPI set that makes AI’s business impact visible
A Decision Intelligence-based roadmap for critical decisions
A Responsible AI approach that reduces trust, compliance, and reputation risk
What We Deliver
Role clarity (who does what?)
We define the working boundaries of humans and AI: Who creates, who reviews, who approves and who is ultimately accountable.
Decision clarity (who owns which decision?)
Kritik karar noktalarını çıkarır, ‘sorumluluk haritası’ oluştururuz: Yapay zeka önerir mi, karar verir mi, uygular mı, sınırları belirleriz.
Measurement clarity (how will we see the value?)
Not ‘we implemented AI’, but impact: Time saved, fewer errors, lower risk, customer outcomes, cost/revenue effect. We make it measurable.
Trust clarity (risk is not a brake design it in)
We turn ethics, security, regulation, and transparency into design parameters, not after-the-fact controls: how much authority AI has in which work, when humans intervene, what needs to be logged/tracked.
Leadership clarity
Leaders can answer the question, ‘What are we asking AI to do?’, and accountability doesn’t get lost.
Schedule a call for a detailed needs assessment.
Why Human&AI Mastery?
As AI spreads fast, the following basics are still unclear in most organizations:
Who does the work and with what level of responsibility?
Where does AI recommend, and where does it act?
How do ethics, security, regulation, and transparency become design parameters, not ‘friction’?
We remove uncertainty by designing human–machine harmony at an organizational level. The result is an operating model that produces outcomes with AI, controlled, measured, and sustainable.
What We Do
Human&AI Mastery Foundation
The core rules for working with AI raising cognitive capability for individuals and leaders. We build the ‘observer muscle’, balance intuition and rationality, and develop cognitive alignment practices reducing where humans and AI collide or duplicate effort.
Human–AI Collaboration Lab
We redesign critical roles and responsibilities for working with AI in real conditions (human-in-the-loop / on-the-loop). We produce an augmented role blueprint and a practical delegation logic.
Human–AI Practice Lab
We enable the sustainability of human–AI collaboration. For leaders and teams, we provide a practical space to build the muscles of asking the right questions, evaluating outputs with evidence and context, recognizing bias and hallucinations, accelerating without transferring accountability, and communicating effectively with AI.
Who Is It For?
Organizations that want to move AI transformation from pilot to scale
C-level / board leaders who want AI’s business impact to be visible and measurable
Teams building hybrid ways of working across product, operations, marketing, sales, technology, risk, finance, and people & culture
Organizations that want to manage Responsible AI, security, and reputation risk at the design level
Those who want to make AI’s business impact visible on the board agenda
Teams already using AI daily but struggling to standardize ways of working
Leaders who want to increase AI usage without losing quality and risk control
Professionals producing outcomes with AI in functions such as marketing, product, tech, operations, sales, risk, finance, and HR
Collaboration Steps
Human&AI Mastery Discovery Call (goals + risk areas + context)
Diagnosis Workshop (current state + barriers)
Decision Intelligence Workshop (critical decision portfolio + KPIs)
Human-AI Operating Model Design (roles/accountability + protocols)
Mastery Modules + Implementation Sprints (practice + measurement + iteration)
Executive Readout & Roadmap (90 days / 6 months / 12 months)
Outcomes
Standard operating protocols for human–AI collaboration
A shared leadership language: not an “AI project,” but a decision and value system
Clear success criteria and KPI set that makes AI’s business impact visible
A Decision Intelligence-based roadmap for critical decisions
A Responsible AI approach that reduces trust, compliance, and reputation risk
What We Deliver
01
02
03
04
05
Role clarity (who does what?)
We define the working boundaries of humans and AI: Who creates, who reviews, who approves and who is ultimately accountable.
Decision clarity (who owns which decision?)
We map critical decision points and build an accountability map: Does AI recommend, decide, or execute, where are the boundaries?
Measurement clarity (how will we see the value?)
Not ‘we implemented AI’, but impact: Time saved, fewer errors, lower risk, customer outcomes, cost/revenue effect. We make it measurable.
GÜVEN NETLİĞİ (RİSK FREN DEĞİL, TASARIM OLSUN)
We turn ethics, security, regulation, and transparency into design parameters, not after-the-fact controls: how much authority AI has in which work, when humans intervene, what needs to be logged/tracked.
Leadership clarity
Leaders can answer the question, ‘What are we asking AI to do?’, and accountability doesn’t get lost.
Schedule a call for a detailed needs assessment.
Why Human&AI Mastery?
As AI spreads fast, the following basics are still unclear in most organizations:
Who does the work and with what level of responsibility?
Where does AI recommend, and where does it act?
How do ethics, security, regulation, and transparency become design parameters, not ‘friction’?
We remove uncertainty by designing human–machine harmony at an organizational level. The result is an operating model that produces outcomes with AI, controlled, measured, and sustainable.
What We Do
Human&AI Mastery Foundation
The core rules for working with AI raising cognitive capability for individuals and leaders. We build the ‘observer muscle’, balance intuition and rationality, and develop cognitive alignment practices reducing where humans and AI collide or duplicate effort.
Human–AI Collaboration Lab
We redesign critical roles and responsibilities for working with AI in real conditions (human-in-the-loop / on-the-loop). We produce an augmented role blueprint and a practical delegation logic.
Human–AI Practice Lab
We enable the sustainability of human–AI collaboration. For leaders and teams, we provide a practical space to build the muscles of asking the right questions, evaluating outputs with evidence and context, recognizing bias and hallucinations, accelerating without transferring accountability, and communicating effectively with AI.
Who Is It For?
Organizations that want to move AI transformation from pilot to scale
C-level / board leaders who want AI’s business impact to be visible and measurable
Teams building hybrid ways of working across product, operations, marketing, sales, technology, risk, finance, and people & culture
Organizations that want to manage Responsible AI, security, and reputation risk at the design level
Teams already using AI daily but struggling to standardize ways of working
Those who want to make AI’s business impact visible on the board agenda
Leaders who want to increase AI usage without losing quality and risk control
Professionals producing outcomes with AI in functions such as marketing, product, tech, operations, sales, risk, finance, and HR
Collaboration Steps
Human&AI Mastery Discovery Call (goals + risk areas + context)
Diagnosis Workshop (current state + barriers)
Decision Intelligence Workshop (critical decision portfolio + KPIs)
Human-AI Operating Model Design (roles/accountability + protocols)
Mastery Modules + Implementation Sprints (practice + measurement + iteration)
Executive Readout & Roadmap (90 days / 6 months / 12 months)
Outcomes
Clear success criteria and KPI set that makes AI’s business impact visible
A Decision Intelligence-based roadmap for critical decisions
A Responsible AI approach that reduces trust, compliance, and reputation risk
A shared leadership language: not an “AI project,” but a decision and value system
Standard operating protocols for human–AI collaboration
© 2024 Forenzone. Tüm hakları saklıdır.
Created by Tolga Arslan
© 2024 Forenzone. Tüm hakları saklıdır.
Created by Tolga Arslan
Human&AI Mastery Program
A program for managing AI not as a ‘tool’, but as a cognitive partner.
Many organizations say, ‘We’re using AI.’
But the real questions are:
Many organizations say, ‘We’re using AI.’ But the real questions are:
Many organizations say, ‘We’re using AI.’ But the real questions are:
Who does which work?
When AI produces an output, who is accountable for the decision?
Where does AI recommend and where does it actually execute?
Who does which work?
When AI produces an output, who is accountable for the decision?
Where does AI recommend and where does it actually execute?
Many organizations say, ‘We’re using AI.’
But the real questions are:
Who does which
work?
When AI produces an output, who is accountable for the decision?
Where does AI recommend and where does it actually execute?
Who does which work?
When AI produces an output, who is accountable for the decision?
Where does AI recommend and where does it actually execute?
What We Deliver
Role clarity (who does what?)
We define the working boundaries of humans and AI: Who creates, who reviews, who approves and who is ultimately accountable.
Decision clarity (who owns which decision?)
Kritik karar noktalarını çıkarır, ‘sorumluluk haritası’ oluştururuz: Yapay zeka önerir mi, karar verir mi, uygular mı, sınırları belirleriz.
Measurement clarity (how will we see the value?)
Not ‘we implemented AI’, but impact: Time saved, fewer errors, lower risk, customer outcomes, cost/revenue effect. We make it measurable.
Trust clarity (risk is not a brake design it in)
We turn ethics, security, regulation, and transparency into design parameters, not after-the-fact controls: how much authority AI has in which work, when humans intervene, what needs to be logged/tracked.
Leadership clarity
Leaders can answer the question, ‘What are we asking AI to do?’, and accountability doesn’t get lost.
Schedule a call for a detailed needs assessment.
Why Human&AI Mastery?
As AI spreads fast, the following basics are still unclear in most organizations:
Who does the work and with what level of responsibility?
Where does AI recommend, and where does it act?
How do ethics, security, regulation, and transparency become design parameters, not ‘friction’?
We remove uncertainty by designing human–machine harmony at an organizational level. The result is an operating model that produces outcomes with AI, controlled, measured, and sustainable.
What We Do
Human&AI Mastery Foundation
The core rules for working with AI raising cognitive capability for individuals and leaders. We build the ‘observer muscle’, balance intuition and rationality, and develop cognitive alignment practices reducing where humans and AI collide or duplicate effort.
Human–AI Collaboration Lab
We redesign critical roles and responsibilities for working with AI in real conditions (human-in-the-loop / on-the-loop). We produce an augmented role blueprint and a practical delegation logic.
Human–AI Practice Lab
We enable the sustainability of human–AI collaboration. For leaders and teams, we provide a practical space to build the muscles of asking the right questions, evaluating outputs with evidence and context, recognizing bias and hallucinations, accelerating without transferring accountability, and communicating effectively with AI.
Who Is It For?
Organizations that want to move AI transformation from pilot to scale
C-level / board leaders who want AI’s business impact to be visible and measurable
Teams building hybrid ways of working across product, operations, marketing, sales, technology, risk, finance, and people & culture
Organizations that want to manage Responsible AI, security, and reputation risk at the design level
Those who want to make AI’s business impact visible on the board agenda
Teams already using AI daily but struggling to standardize ways of working
Leaders who want to increase AI usage without losing quality and risk control
Professionals producing outcomes with AI in functions such as marketing, product, tech, operations, sales, risk, finance, and HR
Collaboration Steps
Human&AI Mastery Discovery Call (goals + risk areas + context)
Diagnosis Workshop (current state + barriers)
Decision Intelligence Workshop (critical decision portfolio + KPIs)
Human-AI Operating Model Design (roles/accountability + protocols)
Mastery Modules + Implementation Sprints (practice + measurement + iteration)
Executive Readout & Roadmap (90 days / 6 months / 12 months)
Outcomes
Standard operating protocols for human–AI collaboration
A shared leadership language: not an “AI project,” but a decision and value system
Clear success criteria and KPI set that makes AI’s business impact visible
A Decision Intelligence-based roadmap for critical decisions
A Responsible AI approach that reduces trust, compliance, and reputation risk
What We Deliver
01
02
03
04
05
Role clarity (who does what?)
We define the working boundaries of humans and AI: Who creates, who reviews, who approves and who is ultimately accountable.
Decision clarity (who owns which decision?)
We map critical decision points and build an accountability map: Does AI recommend, decide, or execute, where are the boundaries?
Measurement clarity (how will we see the value?)
Not ‘we implemented AI’, but impact: Time saved, fewer errors, lower risk, customer outcomes, cost/revenue effect. We make it measurable.
GÜVEN NETLİĞİ (RİSK FREN DEĞİL, TASARIM OLSUN)
We turn ethics, security, regulation, and transparency into design parameters, not after-the-fact controls: how much authority AI has in which work, when humans intervene, what needs to be logged/tracked.
Leadership clarity
Leaders can answer the question, ‘What are we asking AI to do?’, and accountability doesn’t get lost.
Schedule a call for a detailed needs assessment.
Why Human&AI Mastery?
As AI spreads fast, the following basics are still unclear in most organizations:
Who does the work and with what level of responsibility?
Where does AI recommend, and where does it act?
How do ethics, security, regulation, and transparency become design parameters, not ‘friction’?
We remove uncertainty by designing human–machine harmony at an organizational level. The result is an operating model that produces outcomes with AI, controlled, measured, and sustainable.
What We Do
Human&AI Mastery Foundation
The core rules for working with AI raising cognitive capability for individuals and leaders. We build the ‘observer muscle’, balance intuition and rationality, and develop cognitive alignment practices reducing where humans and AI collide or duplicate effort.
Human–AI Collaboration Lab
We redesign critical roles and responsibilities for working with AI in real conditions (human-in-the-loop / on-the-loop). We produce an augmented role blueprint and a practical delegation logic.
Human–AI Practice Lab
We enable the sustainability of human–AI collaboration. For leaders and teams, we provide a practical space to build the muscles of asking the right questions, evaluating outputs with evidence and context, recognizing bias and hallucinations, accelerating without transferring accountability, and communicating effectively with AI.
Who Is It For?
Organizations that want to move AI transformation from pilot to scale
C-level / board leaders who want AI’s business impact to be visible and measurable
Teams building hybrid ways of working across product, operations, marketing, sales, technology, risk, finance, and people & culture
Organizations that want to manage Responsible AI, security, and reputation risk at the design level
Teams already using AI daily but struggling to standardize ways of working
Those who want to make AI’s business impact visible on the board agenda
Leaders who want to increase AI usage without losing quality and risk control
Professionals producing outcomes with AI in functions such as marketing, product, tech, operations, sales, risk, finance, and HR
Collaboration Steps
Human&AI Mastery Discovery Call (goals + risk areas + context)
Diagnosis Workshop (current state + barriers)
Decision Intelligence Workshop (critical decision portfolio + KPIs)
Human-AI Operating Model Design (roles/accountability + protocols)
Mastery Modules + Implementation Sprints (practice + measurement + iteration)
Executive Readout & Roadmap (90 days / 6 months / 12 months)
Outcomes
Clear success criteria and KPI set that makes AI’s business impact visible
A Decision Intelligence-based roadmap for critical decisions
A Responsible AI approach that reduces trust, compliance, and reputation risk
A shared leadership language: not an “AI project,” but a decision and value system
Standard operating protocols for human–AI collaboration
What We Deliver
Role clarity (who does what?)
We define the working boundaries of humans and AI: Who creates, who reviews, who approves and who is ultimately accountable.
Decision clarity (who owns which decision?)
Kritik karar noktalarını çıkarır, ‘sorumluluk haritası’ oluştururuz: Yapay zeka önerir mi, karar verir mi, uygular mı, sınırları belirleriz.
Measurement clarity (how will we see the value?)
Not ‘we implemented AI’, but impact: Time saved, fewer errors, lower risk, customer outcomes, cost/revenue effect. We make it measurable.
Trust clarity (risk is not a brake design it in)
We turn ethics, security, regulation, and transparency into design parameters, not after-the-fact controls: how much authority AI has in which work, when humans intervene, what needs to be logged/tracked.
Leadership clarity
Leaders can answer the question, ‘What are we asking AI to do?’, and accountability doesn’t get lost.
Schedule a call for a detailed needs assessment.
Why Human&AI Mastery?
As AI spreads fast, the following basics are still unclear in most organizations:
Who does the work and with what level of responsibility?
Where does AI recommend, and where does it act?
How do ethics, security, regulation, and transparency become design parameters, not ‘friction’?
We remove uncertainty by designing human–machine harmony at an organizational level. The result is an operating model that produces outcomes with AI, controlled, measured, and sustainable.
What We Do
Human&AI Mastery Foundation
The core rules for working with AI raising cognitive capability for individuals and leaders. We build the ‘observer muscle’, balance intuition and rationality, and develop cognitive alignment practices reducing where humans and AI collide or duplicate effort.
Human–AI Collaboration Lab
We redesign critical roles and responsibilities for working with AI in real conditions (human-in-the-loop / on-the-loop). We produce an augmented role blueprint and a practical delegation logic.
Human–AI Practice Lab
We enable the sustainability of human–AI collaboration. For leaders and teams, we provide a practical space to build the muscles of asking the right questions, evaluating outputs with evidence and context, recognizing bias and hallucinations, accelerating without transferring accountability, and communicating effectively with AI.
Who Is It For?
Organizations that want to move AI transformation from pilot to scale
C-level / board leaders who want AI’s business impact to be visible and measurable
Teams building hybrid ways of working across product, operations, marketing, sales, technology, risk, finance, and people & culture
Organizations that want to manage Responsible AI, security, and reputation risk at the design level
Those who want to make AI’s business impact visible on the board agenda
Teams already using AI daily but struggling to standardize ways of working
Leaders who want to increase AI usage without losing quality and risk control
Professionals producing outcomes with AI in functions such as marketing, product, tech, operations, sales, risk, finance, and HR
Collaboration Steps
Human&AI Mastery Discovery Call (goals + risk areas + context)
Diagnosis Workshop (current state + barriers)
Decision Intelligence Workshop (critical decision portfolio + KPIs)
Human-AI Operating Model Design (roles/accountability + protocols)
Mastery Modules + Implementation Sprints (practice + measurement + iteration)
Executive Readout & Roadmap (90 days / 6 months / 12 months)
Outcomes
Standard operating protocols for human–AI collaboration
A shared leadership language: not an “AI project,” but a decision and value system
Clear success criteria and KPI set that makes AI’s business impact visible
A Decision Intelligence-based roadmap for critical decisions
A Responsible AI approach that reduces trust, compliance, and reputation risk
What We Deliver
Role clarity (who does what?)
We define the working boundaries of humans and AI: Who creates, who reviews, who approves and who is ultimately accountable.
Decision clarity (who owns which decision?)
Kritik karar noktalarını çıkarır, ‘sorumluluk haritası’ oluştururuz: Yapay zeka önerir mi, karar verir mi, uygular mı, sınırları belirleriz.
Measurement clarity (how will we see the value?)
Not ‘we implemented AI’, but impact: Time saved, fewer errors, lower risk, customer outcomes, cost/revenue effect. We make it measurable.
Trust clarity (risk is not a brake design it in)
We turn ethics, security, regulation, and transparency into design parameters, not after-the-fact controls: how much authority AI has in which work, when humans intervene, what needs to be logged/tracked.
Leadership clarity
Leaders can answer the question, ‘What are we asking AI to do?’, and accountability doesn’t get lost.
Schedule a call for a detailed needs assessment.
Why Human&AI Mastery?
As AI spreads fast, the following basics are still unclear in most organizations:
Who does the work and with what level of responsibility?
Where does AI recommend, and where does it act?
How do ethics, security, regulation, and transparency become design parameters, not ‘friction’?
We remove uncertainty by designing human–machine harmony at an organizational level. The result is an operating model that produces outcomes with AI, controlled, measured, and sustainable.
What We Do
Human&AI Mastery Foundation
The core rules for working with AI raising cognitive capability for individuals and leaders. We build the ‘observer muscle’, balance intuition and rationality, and develop cognitive alignment practices reducing where humans and AI collide or duplicate effort.
Human–AI Collaboration Lab
We redesign critical roles and responsibilities for working with AI in real conditions (human-in-the-loop / on-the-loop). We produce an augmented role blueprint and a practical delegation logic.
Human–AI Practice Lab
We enable the sustainability of human–AI collaboration. For leaders and teams, we provide a practical space to build the muscles of asking the right questions, evaluating outputs with evidence and context, recognizing bias and hallucinations, accelerating without transferring accountability, and communicating effectively with AI.
Who Is It For?
Organizations that want to move AI transformation from pilot to scale
C-level / board leaders who want AI’s business impact to be visible and measurable
Teams building hybrid ways of working across product, operations, marketing, sales, technology, risk, finance, and people & culture
Organizations that want to manage Responsible AI, security, and reputation risk at the design level
Those who want to make AI’s business impact visible on the board agenda
Teams already using AI daily but struggling to standardize ways of working
Leaders who want to increase AI usage without losing quality and risk control
Professionals producing outcomes with AI in functions such as marketing, product, tech, operations, sales, risk, finance, and HR
Collaboration Steps
Human&AI Mastery Discovery Call (goals + risk areas + context)
Diagnosis Workshop (current state + barriers)
Decision Intelligence Workshop (critical decision portfolio + KPIs)
Human-AI Operating Model Design (roles/accountability + protocols)
Mastery Modules + Implementation Sprints (practice + measurement + iteration)
Executive Readout & Roadmap (90 days / 6 months / 12 months)
Outcomes
Standard operating protocols for human–AI collaboration
A shared leadership language: not an “AI project,” but a decision and value system
Clear success criteria and KPI set that makes AI’s business impact visible
A Decision Intelligence-based roadmap for critical decisions
A Responsible AI approach that reduces trust, compliance, and reputation risk
What We Deliver
01
02
03
04
05
Role clarity (who does what?)
We define the working boundaries of humans and AI: Who creates, who reviews, who approves and who is ultimately accountable.
Decision clarity (who owns which decision?)
We map critical decision points and build an accountability map: Does AI recommend, decide, or execute, where are the boundaries?
Measurement clarity (how will we see the value?)
Not ‘we implemented AI’, but impact: Time saved, fewer errors, lower risk, customer outcomes, cost/revenue effect. We make it measurable.
GÜVEN NETLİĞİ (RİSK FREN DEĞİL, TASARIM OLSUN)
We turn ethics, security, regulation, and transparency into design parameters, not after-the-fact controls: how much authority AI has in which work, when humans intervene, what needs to be logged/tracked.
Leadership clarity
Leaders can answer the question, ‘What are we asking AI to do?’, and accountability doesn’t get lost.
Schedule a call for a detailed needs assessment.
Why Human&AI Mastery?
As AI spreads fast, the following basics are still unclear in most organizations:
Who does the work and with what level of responsibility?
Where does AI recommend, and where does it act?
How do ethics, security, regulation, and transparency become design parameters, not ‘friction’?
We remove uncertainty by designing human–machine harmony at an organizational level. The result is an operating model that produces outcomes with AI, controlled, measured, and sustainable.
What We Do
Human&AI Mastery Foundation
The core rules for working with AI raising cognitive capability for individuals and leaders. We build the ‘observer muscle’, balance intuition and rationality, and develop cognitive alignment practices reducing where humans and AI collide or duplicate effort.
Human–AI Collaboration Lab
We redesign critical roles and responsibilities for working with AI in real conditions (human-in-the-loop / on-the-loop). We produce an augmented role blueprint and a practical delegation logic.
Human–AI Practice Lab
We enable the sustainability of human–AI collaboration. For leaders and teams, we provide a practical space to build the muscles of asking the right questions, evaluating outputs with evidence and context, recognizing bias and hallucinations, accelerating without transferring accountability, and communicating effectively with AI.
Who Is It For?
Organizations that want to move AI transformation from pilot to scale
C-level / board leaders who want AI’s business impact to be visible and measurable
Teams building hybrid ways of working across product, operations, marketing, sales, technology, risk, finance, and people & culture
Organizations that want to manage Responsible AI, security, and reputation risk at the design level
Teams already using AI daily but struggling to standardize ways of working
Those who want to make AI’s business impact visible on the board agenda
Leaders who want to increase AI usage without losing quality and risk control
Professionals producing outcomes with AI in functions such as marketing, product, tech, operations, sales, risk, finance, and HR
Collaboration Steps
Human&AI Mastery Discovery Call (goals + risk areas + context)
Diagnosis Workshop (current state + barriers)
Decision Intelligence Workshop (critical decision portfolio + KPIs)
Human-AI Operating Model Design (roles/accountability + protocols)
Mastery Modules + Implementation Sprints (practice + measurement + iteration)
Executive Readout & Roadmap (90 days / 6 months / 12 months)
Outcomes
Clear success criteria and KPI set that makes AI’s business impact visible
A Decision Intelligence-based roadmap for critical decisions
A Responsible AI approach that reduces trust, compliance, and reputation risk
A shared leadership language: not an “AI project,” but a decision and value system
Standard operating protocols for human–AI collaboration
© 2024 Forenzone. Tüm hakları saklıdır.
Created by Tolga Arslan
Human&AI Mastery Program
A program for managing AI not as a ‘tool’, but as a cognitive partner.
Many organizations say, ‘We’re using AI.’
But the real questions are:
Many organizations say, ‘We’re using AI.’ But the real questions are:
Many organizations say, ‘We’re using AI.’ But the real questions are:
Who does which work?
When AI produces an output, who is accountable for the decision?
Where does AI recommend and where does it actually execute?
Who does which work?
When AI produces an output, who is accountable for the decision?
Where does AI recommend and where does it actually execute?
Many organizations say, ‘We’re using AI.’
But the real questions are:
Who does which
work?
When AI produces an output, who is accountable for the decision?
Where does AI recommend and where does it actually execute?
Who does which work?
When AI produces an output, who is accountable for the decision?
Where does AI recommend and where does it actually execute?
What We Deliver
Role clarity (who does what?)
We define the working boundaries of humans and AI: Who creates, who reviews, who approves and who is ultimately accountable.
Decision clarity (who owns which decision?)
Kritik karar noktalarını çıkarır, ‘sorumluluk haritası’ oluştururuz: Yapay zeka önerir mi, karar verir mi, uygular mı, sınırları belirleriz.
Measurement clarity (how will we see the value?)
Not ‘we implemented AI’, but impact: Time saved, fewer errors, lower risk, customer outcomes, cost/revenue effect. We make it measurable.
Trust clarity (risk is not a brake design it in)
We turn ethics, security, regulation, and transparency into design parameters, not after-the-fact controls: how much authority AI has in which work, when humans intervene, what needs to be logged/tracked.
Leadership clarity
Leaders can answer the question, ‘What are we asking AI to do?’, and accountability doesn’t get lost.
Schedule a call for a detailed needs assessment.
Why Human&AI Mastery?
As AI spreads fast, the following basics are still unclear in most organizations:
Who does the work and with what level of responsibility?
Where does AI recommend, and where does it act?
How do ethics, security, regulation, and transparency become design parameters, not ‘friction’?
We remove uncertainty by designing human–machine harmony at an organizational level. The result is an operating model that produces outcomes with AI, controlled, measured, and sustainable.
What We Do
Human&AI Mastery Foundation
The core rules for working with AI raising cognitive capability for individuals and leaders. We build the ‘observer muscle’, balance intuition and rationality, and develop cognitive alignment practices reducing where humans and AI collide or duplicate effort.
Human–AI Collaboration Lab
We redesign critical roles and responsibilities for working with AI in real conditions (human-in-the-loop / on-the-loop). We produce an augmented role blueprint and a practical delegation logic.
Human–AI Practice Lab
We enable the sustainability of human–AI collaboration. For leaders and teams, we provide a practical space to build the muscles of asking the right questions, evaluating outputs with evidence and context, recognizing bias and hallucinations, accelerating without transferring accountability, and communicating effectively with AI.
Who Is It For?
Organizations that want to move AI transformation from pilot to scale
C-level / board leaders who want AI’s business impact to be visible and measurable
Teams building hybrid ways of working across product, operations, marketing, sales, technology, risk, finance, and people & culture
Organizations that want to manage Responsible AI, security, and reputation risk at the design level
Those who want to make AI’s business impact visible on the board agenda
Teams already using AI daily but struggling to standardize ways of working
Leaders who want to increase AI usage without losing quality and risk control
Professionals producing outcomes with AI in functions such as marketing, product, tech, operations, sales, risk, finance, and HR
Collaboration Steps
Human&AI Mastery Discovery Call (goals + risk areas + context)
Diagnosis Workshop (current state + barriers)
Decision Intelligence Workshop (critical decision portfolio + KPIs)
Human-AI Operating Model Design (roles/accountability + protocols)
Mastery Modules + Implementation Sprints (practice + measurement + iteration)
Executive Readout & Roadmap (90 days / 6 months / 12 months)
Outcomes
Standard operating protocols for human–AI collaboration
A shared leadership language: not an “AI project,” but a decision and value system
Clear success criteria and KPI set that makes AI’s business impact visible
A Decision Intelligence-based roadmap for critical decisions
A Responsible AI approach that reduces trust, compliance, and reputation risk
What We Deliver
01
02
03
04
05
Role clarity (who does what?)
We define the working boundaries of humans and AI: Who creates, who reviews, who approves and who is ultimately accountable.
Decision clarity (who owns which decision?)
We map critical decision points and build an accountability map: Does AI recommend, decide, or execute, where are the boundaries?
Measurement clarity (how will we see the value?)
Not ‘we implemented AI’, but impact: Time saved, fewer errors, lower risk, customer outcomes, cost/revenue effect. We make it measurable.
GÜVEN NETLİĞİ (RİSK FREN DEĞİL, TASARIM OLSUN)
We turn ethics, security, regulation, and transparency into design parameters, not after-the-fact controls: how much authority AI has in which work, when humans intervene, what needs to be logged/tracked.
Leadership clarity
Leaders can answer the question, ‘What are we asking AI to do?’, and accountability doesn’t get lost.
Schedule a call for a detailed needs assessment.
Why Human&AI Mastery?
As AI spreads fast, the following basics are still unclear in most organizations:
Who does the work and with what level of responsibility?
Where does AI recommend, and where does it act?
How do ethics, security, regulation, and transparency become design parameters, not ‘friction’?
We remove uncertainty by designing human–machine harmony at an organizational level. The result is an operating model that produces outcomes with AI, controlled, measured, and sustainable.
What We Do
Human&AI Mastery Foundation
The core rules for working with AI raising cognitive capability for individuals and leaders. We build the ‘observer muscle’, balance intuition and rationality, and develop cognitive alignment practices reducing where humans and AI collide or duplicate effort.
Human–AI Collaboration Lab
We redesign critical roles and responsibilities for working with AI in real conditions (human-in-the-loop / on-the-loop). We produce an augmented role blueprint and a practical delegation logic.
Human–AI Practice Lab
We enable the sustainability of human–AI collaboration. For leaders and teams, we provide a practical space to build the muscles of asking the right questions, evaluating outputs with evidence and context, recognizing bias and hallucinations, accelerating without transferring accountability, and communicating effectively with AI.
Who Is It For?
Organizations that want to move AI transformation from pilot to scale
C-level / board leaders who want AI’s business impact to be visible and measurable
Teams building hybrid ways of working across product, operations, marketing, sales, technology, risk, finance, and people & culture
Organizations that want to manage Responsible AI, security, and reputation risk at the design level
Teams already using AI daily but struggling to standardize ways of working
Those who want to make AI’s business impact visible on the board agenda
Leaders who want to increase AI usage without losing quality and risk control
Professionals producing outcomes with AI in functions such as marketing, product, tech, operations, sales, risk, finance, and HR
Collaboration Steps
Human&AI Mastery Discovery Call (goals + risk areas + context)
Diagnosis Workshop (current state + barriers)
Decision Intelligence Workshop (critical decision portfolio + KPIs)
Human-AI Operating Model Design (roles/accountability + protocols)
Mastery Modules + Implementation Sprints (practice + measurement + iteration)
Executive Readout & Roadmap (90 days / 6 months / 12 months)
Outcomes
Clear success criteria and KPI set that makes AI’s business impact visible
A Decision Intelligence-based roadmap for critical decisions
A Responsible AI approach that reduces trust, compliance, and reputation risk
A shared leadership language: not an “AI project,” but a decision and value system
Standard operating protocols for human–AI collaboration
What We Deliver
Role clarity (who does what?)
We define the working boundaries of humans and AI: Who creates, who reviews, who approves and who is ultimately accountable.
Decision clarity (who owns which decision?)
Kritik karar noktalarını çıkarır, ‘sorumluluk haritası’ oluştururuz: Yapay zeka önerir mi, karar verir mi, uygular mı, sınırları belirleriz.
Measurement clarity (how will we see the value?)
Not ‘we implemented AI’, but impact: Time saved, fewer errors, lower risk, customer outcomes, cost/revenue effect. We make it measurable.
Trust clarity (risk is not a brake design it in)
We turn ethics, security, regulation, and transparency into design parameters, not after-the-fact controls: how much authority AI has in which work, when humans intervene, what needs to be logged/tracked.
Leadership clarity
Leaders can answer the question, ‘What are we asking AI to do?’, and accountability doesn’t get lost.
Schedule a call for a detailed needs assessment.
Why Human&AI Mastery?
As AI spreads fast, the following basics are still unclear in most organizations:
Who does the work and with what level of responsibility?
Where does AI recommend, and where does it act?
How do ethics, security, regulation, and transparency become design parameters, not ‘friction’?
We remove uncertainty by designing human–machine harmony at an organizational level. The result is an operating model that produces outcomes with AI, controlled, measured, and sustainable.
What We Do
Human&AI Mastery Foundation
The core rules for working with AI raising cognitive capability for individuals and leaders. We build the ‘observer muscle’, balance intuition and rationality, and develop cognitive alignment practices reducing where humans and AI collide or duplicate effort.
Human–AI Collaboration Lab
We redesign critical roles and responsibilities for working with AI in real conditions (human-in-the-loop / on-the-loop). We produce an augmented role blueprint and a practical delegation logic.
Human–AI Practice Lab
We enable the sustainability of human–AI collaboration. For leaders and teams, we provide a practical space to build the muscles of asking the right questions, evaluating outputs with evidence and context, recognizing bias and hallucinations, accelerating without transferring accountability, and communicating effectively with AI.
Who Is It For?
Organizations that want to move AI transformation from pilot to scale
C-level / board leaders who want AI’s business impact to be visible and measurable
Teams building hybrid ways of working across product, operations, marketing, sales, technology, risk, finance, and people & culture
Organizations that want to manage Responsible AI, security, and reputation risk at the design level
Those who want to make AI’s business impact visible on the board agenda
Teams already using AI daily but struggling to standardize ways of working
Leaders who want to increase AI usage without losing quality and risk control
Professionals producing outcomes with AI in functions such as marketing, product, tech, operations, sales, risk, finance, and HR
Collaboration Steps
Human&AI Mastery Discovery Call (goals + risk areas + context)
Diagnosis Workshop (current state + barriers)
Decision Intelligence Workshop (critical decision portfolio + KPIs)
Human-AI Operating Model Design (roles/accountability + protocols)
Mastery Modules + Implementation Sprints (practice + measurement + iteration)
Executive Readout & Roadmap (90 days / 6 months / 12 months)
Outcomes
Standard operating protocols for human–AI collaboration
A shared leadership language: not an “AI project,” but a decision and value system
Clear success criteria and KPI set that makes AI’s business impact visible
A Decision Intelligence-based roadmap for critical decisions
A Responsible AI approach that reduces trust, compliance, and reputation risk
What We Deliver
Role clarity (who does what?)
We define the working boundaries of humans and AI: Who creates, who reviews, who approves and who is ultimately accountable.
Decision clarity (who owns which decision?)
Kritik karar noktalarını çıkarır, ‘sorumluluk haritası’ oluştururuz: Yapay zeka önerir mi, karar verir mi, uygular mı, sınırları belirleriz.
Measurement clarity (how will we see the value?)
Not ‘we implemented AI’, but impact: Time saved, fewer errors, lower risk, customer outcomes, cost/revenue effect. We make it measurable.
Trust clarity (risk is not a brake design it in)
We turn ethics, security, regulation, and transparency into design parameters, not after-the-fact controls: how much authority AI has in which work, when humans intervene, what needs to be logged/tracked.
Leadership clarity
Leaders can answer the question, ‘What are we asking AI to do?’, and accountability doesn’t get lost.
Schedule a call for a detailed needs assessment.
Why Human&AI Mastery?
As AI spreads fast, the following basics are still unclear in most organizations:
Who does the work and with what level of responsibility?
Where does AI recommend, and where does it act?
How do ethics, security, regulation, and transparency become design parameters, not ‘friction’?
We remove uncertainty by designing human–machine harmony at an organizational level. The result is an operating model that produces outcomes with AI, controlled, measured, and sustainable.
What We Do
Human&AI Mastery Foundation
The core rules for working with AI raising cognitive capability for individuals and leaders. We build the ‘observer muscle’, balance intuition and rationality, and develop cognitive alignment practices reducing where humans and AI collide or duplicate effort.
Human–AI Collaboration Lab
We redesign critical roles and responsibilities for working with AI in real conditions (human-in-the-loop / on-the-loop). We produce an augmented role blueprint and a practical delegation logic.
Human–AI Practice Lab
We enable the sustainability of human–AI collaboration. For leaders and teams, we provide a practical space to build the muscles of asking the right questions, evaluating outputs with evidence and context, recognizing bias and hallucinations, accelerating without transferring accountability, and communicating effectively with AI.
Who Is It For?
Organizations that want to move AI transformation from pilot to scale
C-level / board leaders who want AI’s business impact to be visible and measurable
Teams building hybrid ways of working across product, operations, marketing, sales, technology, risk, finance, and people & culture
Organizations that want to manage Responsible AI, security, and reputation risk at the design level
Those who want to make AI’s business impact visible on the board agenda
Teams already using AI daily but struggling to standardize ways of working
Leaders who want to increase AI usage without losing quality and risk control
Professionals producing outcomes with AI in functions such as marketing, product, tech, operations, sales, risk, finance, and HR
Collaboration Steps
Human&AI Mastery Discovery Call (goals + risk areas + context)
Diagnosis Workshop (current state + barriers)
Decision Intelligence Workshop (critical decision portfolio + KPIs)
Human-AI Operating Model Design (roles/accountability + protocols)
Mastery Modules + Implementation Sprints (practice + measurement + iteration)
Executive Readout & Roadmap (90 days / 6 months / 12 months)
Outcomes
Standard operating protocols for human–AI collaboration
A shared leadership language: not an “AI project,” but a decision and value system
Clear success criteria and KPI set that makes AI’s business impact visible
A Decision Intelligence-based roadmap for critical decisions
A Responsible AI approach that reduces trust, compliance, and reputation risk
What We Deliver
01
02
03
04
05
Role clarity (who does what?)
We define the working boundaries of humans and AI: Who creates, who reviews, who approves and who is ultimately accountable.
Decision clarity (who owns which decision?)
We map critical decision points and build an accountability map: Does AI recommend, decide, or execute, where are the boundaries?
Measurement clarity (how will we see the value?)
Not ‘we implemented AI’, but impact: Time saved, fewer errors, lower risk, customer outcomes, cost/revenue effect. We make it measurable.
GÜVEN NETLİĞİ (RİSK FREN DEĞİL, TASARIM OLSUN)
We turn ethics, security, regulation, and transparency into design parameters, not after-the-fact controls: how much authority AI has in which work, when humans intervene, what needs to be logged/tracked.
Leadership clarity
Leaders can answer the question, ‘What are we asking AI to do?’, and accountability doesn’t get lost.
Schedule a call for a detailed needs assessment.
Why Human&AI Mastery?
As AI spreads fast, the following basics are still unclear in most organizations:
Who does the work and with what level of responsibility?
Where does AI recommend, and where does it act?
How do ethics, security, regulation, and transparency become design parameters, not ‘friction’?
We remove uncertainty by designing human–machine harmony at an organizational level. The result is an operating model that produces outcomes with AI, controlled, measured, and sustainable.
What We Do
Human&AI Mastery Foundation
The core rules for working with AI raising cognitive capability for individuals and leaders. We build the ‘observer muscle’, balance intuition and rationality, and develop cognitive alignment practices reducing where humans and AI collide or duplicate effort.
Human–AI Collaboration Lab
We redesign critical roles and responsibilities for working with AI in real conditions (human-in-the-loop / on-the-loop). We produce an augmented role blueprint and a practical delegation logic.
Human–AI Practice Lab
We enable the sustainability of human–AI collaboration. For leaders and teams, we provide a practical space to build the muscles of asking the right questions, evaluating outputs with evidence and context, recognizing bias and hallucinations, accelerating without transferring accountability, and communicating effectively with AI.
Who Is It For?
Organizations that want to move AI transformation from pilot to scale
C-level / board leaders who want AI’s business impact to be visible and measurable
Teams building hybrid ways of working across product, operations, marketing, sales, technology, risk, finance, and people & culture
Organizations that want to manage Responsible AI, security, and reputation risk at the design level
Teams already using AI daily but struggling to standardize ways of working
Those who want to make AI’s business impact visible on the board agenda
Leaders who want to increase AI usage without losing quality and risk control
Professionals producing outcomes with AI in functions such as marketing, product, tech, operations, sales, risk, finance, and HR
Collaboration Steps
Human&AI Mastery Discovery Call (goals + risk areas + context)
Diagnosis Workshop (current state + barriers)
Decision Intelligence Workshop (critical decision portfolio + KPIs)
Human-AI Operating Model Design (roles/accountability + protocols)
Mastery Modules + Implementation Sprints (practice + measurement + iteration)
Executive Readout & Roadmap (90 days / 6 months / 12 months)
Outcomes
Clear success criteria and KPI set that makes AI’s business impact visible
A Decision Intelligence-based roadmap for critical decisions
A Responsible AI approach that reduces trust, compliance, and reputation risk
A shared leadership language: not an “AI project,” but a decision and value system
Standard operating protocols for human–AI collaboration
© 2024 Forenzone. Tüm hakları saklıdır.
Created by Tolga Arslan
Human&AI Mastery Program
A program for managing AI not as a ‘tool’, but as a cognitive partner.
Many organizations say, ‘We’re using AI.’
But the real questions are:
Many organizations say, ‘We’re using AI.’ But the real questions are:
Many organizations say, ‘We’re using AI.’ But the real questions are:
Who does which work?
When AI produces an output, who is accountable for the decision?
Where does AI recommend and where does it actually execute?
Who does which work?
When AI produces an output, who is accountable for the decision?
Where does AI recommend and where does it actually execute?
Many organizations say, ‘We’re using AI.’
But the real questions are:
Who does which
work?
When AI produces an output, who is accountable for the decision?
Where does AI recommend and where does it actually execute?
Who does which work?
When AI produces an output, who is accountable for the decision?
Where does AI recommend and where does it actually execute?
What We Deliver
Role clarity (who does what?)
We define the working boundaries of humans and AI: Who creates, who reviews, who approves and who is ultimately accountable.
Decision clarity (who owns which decision?)
Kritik karar noktalarını çıkarır, ‘sorumluluk haritası’ oluştururuz: Yapay zeka önerir mi, karar verir mi, uygular mı, sınırları belirleriz.
Measurement clarity (how will we see the value?)
Not ‘we implemented AI’, but impact: Time saved, fewer errors, lower risk, customer outcomes, cost/revenue effect. We make it measurable.
Trust clarity (risk is not a brake design it in)
We turn ethics, security, regulation, and transparency into design parameters, not after-the-fact controls: how much authority AI has in which work, when humans intervene, what needs to be logged/tracked.
Leadership clarity
Leaders can answer the question, ‘What are we asking AI to do?’, and accountability doesn’t get lost.
Schedule a call for a detailed needs assessment.
Why Human&AI Mastery?
As AI spreads fast, the following basics are still unclear in most organizations:
Who does the work and with what level of responsibility?
Where does AI recommend, and where does it act?
How do ethics, security, regulation, and transparency become design parameters, not ‘friction’?
We remove uncertainty by designing human–machine harmony at an organizational level. The result is an operating model that produces outcomes with AI, controlled, measured, and sustainable.
What We Do
Human&AI Mastery Foundation
The core rules for working with AI raising cognitive capability for individuals and leaders. We build the ‘observer muscle’, balance intuition and rationality, and develop cognitive alignment practices reducing where humans and AI collide or duplicate effort.
Human–AI Collaboration Lab
We redesign critical roles and responsibilities for working with AI in real conditions (human-in-the-loop / on-the-loop). We produce an augmented role blueprint and a practical delegation logic.
Human–AI Practice Lab
We enable the sustainability of human–AI collaboration. For leaders and teams, we provide a practical space to build the muscles of asking the right questions, evaluating outputs with evidence and context, recognizing bias and hallucinations, accelerating without transferring accountability, and communicating effectively with AI.
Who Is It For?
Organizations that want to move AI transformation from pilot to scale
C-level / board leaders who want AI’s business impact to be visible and measurable
Teams building hybrid ways of working across product, operations, marketing, sales, technology, risk, finance, and people & culture
Organizations that want to manage Responsible AI, security, and reputation risk at the design level
Those who want to make AI’s business impact visible on the board agenda
Teams already using AI daily but struggling to standardize ways of working
Leaders who want to increase AI usage without losing quality and risk control
Professionals producing outcomes with AI in functions such as marketing, product, tech, operations, sales, risk, finance, and HR
Collaboration Steps
Human&AI Mastery Discovery Call (goals + risk areas + context)
Diagnosis Workshop (current state + barriers)
Decision Intelligence Workshop (critical decision portfolio + KPIs)
Human-AI Operating Model Design (roles/accountability + protocols)
Mastery Modules + Implementation Sprints (practice + measurement + iteration)
Executive Readout & Roadmap (90 days / 6 months / 12 months)
Outcomes
Standard operating protocols for human–AI collaboration
A shared leadership language: not an “AI project,” but a decision and value system
Clear success criteria and KPI set that makes AI’s business impact visible
A Decision Intelligence-based roadmap for critical decisions
A Responsible AI approach that reduces trust, compliance, and reputation risk
What We Deliver
01
02
03
04
05
Role clarity (who does what?)
We define the working boundaries of humans and AI: Who creates, who reviews, who approves and who is ultimately accountable.
Decision clarity (who owns which decision?)
We map critical decision points and build an accountability map: Does AI recommend, decide, or execute, where are the boundaries?
Measurement clarity (how will we see the value?)
Not ‘we implemented AI’, but impact: Time saved, fewer errors, lower risk, customer outcomes, cost/revenue effect. We make it measurable.
GÜVEN NETLİĞİ (RİSK FREN DEĞİL, TASARIM OLSUN)
We turn ethics, security, regulation, and transparency into design parameters, not after-the-fact controls: how much authority AI has in which work, when humans intervene, what needs to be logged/tracked.
Leadership clarity
Leaders can answer the question, ‘What are we asking AI to do?’, and accountability doesn’t get lost.
Schedule a call for a detailed needs assessment.
Why Human&AI Mastery?
As AI spreads fast, the following basics are still unclear in most organizations:
Who does the work and with what level of responsibility?
Where does AI recommend, and where does it act?
How do ethics, security, regulation, and transparency become design parameters, not ‘friction’?
We remove uncertainty by designing human–machine harmony at an organizational level. The result is an operating model that produces outcomes with AI, controlled, measured, and sustainable.
What We Do
Human&AI Mastery Foundation
The core rules for working with AI raising cognitive capability for individuals and leaders. We build the ‘observer muscle’, balance intuition and rationality, and develop cognitive alignment practices reducing where humans and AI collide or duplicate effort.
Human–AI Collaboration Lab
We redesign critical roles and responsibilities for working with AI in real conditions (human-in-the-loop / on-the-loop). We produce an augmented role blueprint and a practical delegation logic.
Human–AI Practice Lab
We enable the sustainability of human–AI collaboration. For leaders and teams, we provide a practical space to build the muscles of asking the right questions, evaluating outputs with evidence and context, recognizing bias and hallucinations, accelerating without transferring accountability, and communicating effectively with AI.
Who Is It For?
Organizations that want to move AI transformation from pilot to scale
C-level / board leaders who want AI’s business impact to be visible and measurable
Teams building hybrid ways of working across product, operations, marketing, sales, technology, risk, finance, and people & culture
Organizations that want to manage Responsible AI, security, and reputation risk at the design level
Teams already using AI daily but struggling to standardize ways of working
Those who want to make AI’s business impact visible on the board agenda
Leaders who want to increase AI usage without losing quality and risk control
Professionals producing outcomes with AI in functions such as marketing, product, tech, operations, sales, risk, finance, and HR
Collaboration Steps
Human&AI Mastery Discovery Call (goals + risk areas + context)
Diagnosis Workshop (current state + barriers)
Decision Intelligence Workshop (critical decision portfolio + KPIs)
Human-AI Operating Model Design (roles/accountability + protocols)
Mastery Modules + Implementation Sprints (practice + measurement + iteration)
Executive Readout & Roadmap (90 days / 6 months / 12 months)
Outcomes
Clear success criteria and KPI set that makes AI’s business impact visible
A Decision Intelligence-based roadmap for critical decisions
A Responsible AI approach that reduces trust, compliance, and reputation risk
A shared leadership language: not an “AI project,” but a decision and value system
Standard operating protocols for human–AI collaboration
What We Deliver
Role clarity (who does what?)
We define the working boundaries of humans and AI: Who creates, who reviews, who approves and who is ultimately accountable.
Decision clarity (who owns which decision?)
Kritik karar noktalarını çıkarır, ‘sorumluluk haritası’ oluştururuz: Yapay zeka önerir mi, karar verir mi, uygular mı, sınırları belirleriz.
Measurement clarity (how will we see the value?)
Not ‘we implemented AI’, but impact: Time saved, fewer errors, lower risk, customer outcomes, cost/revenue effect. We make it measurable.
Trust clarity (risk is not a brake design it in)
We turn ethics, security, regulation, and transparency into design parameters, not after-the-fact controls: how much authority AI has in which work, when humans intervene, what needs to be logged/tracked.
Leadership clarity
Leaders can answer the question, ‘What are we asking AI to do?’, and accountability doesn’t get lost.
Schedule a call for a detailed needs assessment.
Why Human&AI Mastery?
As AI spreads fast, the following basics are still unclear in most organizations:
Who does the work and with what level of responsibility?
Where does AI recommend, and where does it act?
How do ethics, security, regulation, and transparency become design parameters, not ‘friction’?
We remove uncertainty by designing human–machine harmony at an organizational level. The result is an operating model that produces outcomes with AI, controlled, measured, and sustainable.
What We Do
Human&AI Mastery Foundation
The core rules for working with AI raising cognitive capability for individuals and leaders. We build the ‘observer muscle’, balance intuition and rationality, and develop cognitive alignment practices reducing where humans and AI collide or duplicate effort.
Human–AI Collaboration Lab
We redesign critical roles and responsibilities for working with AI in real conditions (human-in-the-loop / on-the-loop). We produce an augmented role blueprint and a practical delegation logic.
Human–AI Practice Lab
We enable the sustainability of human–AI collaboration. For leaders and teams, we provide a practical space to build the muscles of asking the right questions, evaluating outputs with evidence and context, recognizing bias and hallucinations, accelerating without transferring accountability, and communicating effectively with AI.
Who Is It For?
Organizations that want to move AI transformation from pilot to scale
C-level / board leaders who want AI’s business impact to be visible and measurable
Teams building hybrid ways of working across product, operations, marketing, sales, technology, risk, finance, and people & culture
Organizations that want to manage Responsible AI, security, and reputation risk at the design level
Those who want to make AI’s business impact visible on the board agenda
Teams already using AI daily but struggling to standardize ways of working
Leaders who want to increase AI usage without losing quality and risk control
Professionals producing outcomes with AI in functions such as marketing, product, tech, operations, sales, risk, finance, and HR
Collaboration Steps
Human&AI Mastery Discovery Call (goals + risk areas + context)
Diagnosis Workshop (current state + barriers)
Decision Intelligence Workshop (critical decision portfolio + KPIs)
Human-AI Operating Model Design (roles/accountability + protocols)
Mastery Modules + Implementation Sprints (practice + measurement + iteration)
Executive Readout & Roadmap (90 days / 6 months / 12 months)
Outcomes
Standard operating protocols for human–AI collaboration
A shared leadership language: not an “AI project,” but a decision and value system
Clear success criteria and KPI set that makes AI’s business impact visible
A Decision Intelligence-based roadmap for critical decisions
A Responsible AI approach that reduces trust, compliance, and reputation risk
What We Deliver
Role clarity (who does what?)
We define the working boundaries of humans and AI: Who creates, who reviews, who approves and who is ultimately accountable.
Decision clarity (who owns which decision?)
Kritik karar noktalarını çıkarır, ‘sorumluluk haritası’ oluştururuz: Yapay zeka önerir mi, karar verir mi, uygular mı, sınırları belirleriz.
Measurement clarity (how will we see the value?)
Not ‘we implemented AI’, but impact: Time saved, fewer errors, lower risk, customer outcomes, cost/revenue effect. We make it measurable.
Trust clarity (risk is not a brake design it in)
We turn ethics, security, regulation, and transparency into design parameters, not after-the-fact controls: how much authority AI has in which work, when humans intervene, what needs to be logged/tracked.
Leadership clarity
Leaders can answer the question, ‘What are we asking AI to do?’, and accountability doesn’t get lost.
Schedule a call for a detailed needs assessment.
Why Human&AI Mastery?
As AI spreads fast, the following basics are still unclear in most organizations:
Who does the work and with what level of responsibility?
Where does AI recommend, and where does it act?
How do ethics, security, regulation, and transparency become design parameters, not ‘friction’?
We remove uncertainty by designing human–machine harmony at an organizational level. The result is an operating model that produces outcomes with AI, controlled, measured, and sustainable.
What We Do
Human&AI Mastery Foundation
The core rules for working with AI raising cognitive capability for individuals and leaders. We build the ‘observer muscle’, balance intuition and rationality, and develop cognitive alignment practices reducing where humans and AI collide or duplicate effort.
Human–AI Collaboration Lab
We redesign critical roles and responsibilities for working with AI in real conditions (human-in-the-loop / on-the-loop). We produce an augmented role blueprint and a practical delegation logic.
Human–AI Practice Lab
We enable the sustainability of human–AI collaboration. For leaders and teams, we provide a practical space to build the muscles of asking the right questions, evaluating outputs with evidence and context, recognizing bias and hallucinations, accelerating without transferring accountability, and communicating effectively with AI.
Who Is It For?
Organizations that want to move AI transformation from pilot to scale
C-level / board leaders who want AI’s business impact to be visible and measurable
Teams building hybrid ways of working across product, operations, marketing, sales, technology, risk, finance, and people & culture
Organizations that want to manage Responsible AI, security, and reputation risk at the design level
Those who want to make AI’s business impact visible on the board agenda
Teams already using AI daily but struggling to standardize ways of working
Leaders who want to increase AI usage without losing quality and risk control
Professionals producing outcomes with AI in functions such as marketing, product, tech, operations, sales, risk, finance, and HR
Collaboration Steps
Human&AI Mastery Discovery Call (goals + risk areas + context)
Diagnosis Workshop (current state + barriers)
Decision Intelligence Workshop (critical decision portfolio + KPIs)
Human-AI Operating Model Design (roles/accountability + protocols)
Mastery Modules + Implementation Sprints (practice + measurement + iteration)
Executive Readout & Roadmap (90 days / 6 months / 12 months)
Outcomes
Standard operating protocols for human–AI collaboration
A shared leadership language: not an “AI project,” but a decision and value system
Clear success criteria and KPI set that makes AI’s business impact visible
A Decision Intelligence-based roadmap for critical decisions
A Responsible AI approach that reduces trust, compliance, and reputation risk
What We Deliver
01
02
03
04
05
Role clarity (who does what?)
We define the working boundaries of humans and AI: Who creates, who reviews, who approves and who is ultimately accountable.
Decision clarity (who owns which decision?)
We map critical decision points and build an accountability map: Does AI recommend, decide, or execute, where are the boundaries?
Measurement clarity (how will we see the value?)
Not ‘we implemented AI’, but impact: Time saved, fewer errors, lower risk, customer outcomes, cost/revenue effect. We make it measurable.
GÜVEN NETLİĞİ (RİSK FREN DEĞİL, TASARIM OLSUN)
We turn ethics, security, regulation, and transparency into design parameters, not after-the-fact controls: how much authority AI has in which work, when humans intervene, what needs to be logged/tracked.
Leadership clarity
Leaders can answer the question, ‘What are we asking AI to do?’, and accountability doesn’t get lost.
Schedule a call for a detailed needs assessment.
Why Human&AI Mastery?
As AI spreads fast, the following basics are still unclear in most organizations:
Who does the work and with what level of responsibility?
Where does AI recommend, and where does it act?
How do ethics, security, regulation, and transparency become design parameters, not ‘friction’?
We remove uncertainty by designing human–machine harmony at an organizational level. The result is an operating model that produces outcomes with AI, controlled, measured, and sustainable.
What We Do
Human&AI Mastery Foundation
The core rules for working with AI raising cognitive capability for individuals and leaders. We build the ‘observer muscle’, balance intuition and rationality, and develop cognitive alignment practices reducing where humans and AI collide or duplicate effort.
Human–AI Collaboration Lab
We redesign critical roles and responsibilities for working with AI in real conditions (human-in-the-loop / on-the-loop). We produce an augmented role blueprint and a practical delegation logic.
Human–AI Practice Lab
We enable the sustainability of human–AI collaboration. For leaders and teams, we provide a practical space to build the muscles of asking the right questions, evaluating outputs with evidence and context, recognizing bias and hallucinations, accelerating without transferring accountability, and communicating effectively with AI.
Who Is It For?
Organizations that want to move AI transformation from pilot to scale
C-level / board leaders who want AI’s business impact to be visible and measurable
Teams building hybrid ways of working across product, operations, marketing, sales, technology, risk, finance, and people & culture
Organizations that want to manage Responsible AI, security, and reputation risk at the design level
Teams already using AI daily but struggling to standardize ways of working
Those who want to make AI’s business impact visible on the board agenda
Leaders who want to increase AI usage without losing quality and risk control
Professionals producing outcomes with AI in functions such as marketing, product, tech, operations, sales, risk, finance, and HR
Collaboration Steps
Human&AI Mastery Discovery Call (goals + risk areas + context)
Diagnosis Workshop (current state + barriers)
Decision Intelligence Workshop (critical decision portfolio + KPIs)
Human-AI Operating Model Design (roles/accountability + protocols)
Mastery Modules + Implementation Sprints (practice + measurement + iteration)
Executive Readout & Roadmap (90 days / 6 months / 12 months)
Outcomes
Clear success criteria and KPI set that makes AI’s business impact visible
A Decision Intelligence-based roadmap for critical decisions
A Responsible AI approach that reduces trust, compliance, and reputation risk
A shared leadership language: not an “AI project,” but a decision and value system
Standard operating protocols for human–AI collaboration
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