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Human \+ AI Decisions™
Strengthening Critical Thinking, Human Oversight and Management Accountability in AI-Supported Decision-Making
Download Course BrochureFlexible delivery options to suit your leadership team and organisational needs.
Duration
5 Days
Certificate
Executive Certificate
Level
Manager / Emerging Leader
Format
In-Person / Virtual
Delivery Mode
Instructor-led Workshops, Discussions, Case Studies, Simulations
Online
Date: 16th – 20th Nov 2026
Location: Virtual
Fee: £3,495
Online
Date: 23rd – 27th Nov 2026
Location: Virtual
Fee: £3,495
Online
Date: 30th – 4th Nov 2026
Location: Virtual
Fee: £3,495
In Person
Date: 23rd – 27th Nov 2026
Location: London
Fee: £4,495
In Person
Date: 30th – 4th Nov 2026
Location: London
Fee: £4,495
In Person
Date: 2nd – 6th Nov 2026
Location: Paris
Fee: £4,495
In Person
Date: 9th – 13th Nov 2026
Location: Dubai
Fee: £4,495
Online
Date: 14th – 18th Dec 2026
Location: Virtual
Fee: £3,495
Online
Date: 21st – 25th Dec 2026
Location: Virtual
Fee: £3,495
Online
Date: 28th – 1st Dec 2026
Location: Virtual
Fee: £3,495
Introduction
As AI becomes more involved in analysis, recommendations and decision support, managers need stronger—not weaker—human judgement. This programme equips managers to critically evaluate AI-generated information, recognise where assumptions, bias or uncertainty may exist and determine when human intervention is essential. Participants learn to combine the speed and analytical capability of AI with context, experience, critical thinking and responsible human oversight to make better organisational decisions.
Middle & Experienced Managers
People Managers & Team Leaders
Functional & Departmental Managers
Managers Making AI-Supported Decisions
Participants will leave the Programme with stronger strategic capability and practical approaches that can be immediately applied within their organisations.
Understanding the role of human judgement in AI-supported decisions
Determining which decisions should and should not involve AI
Critically evaluating AI-generated analysis and recommendations
Recognising bias, uncertainty and limitations in AI outputs
Maintaining clear human ownership and accountability for decisions
Evaluate AI-generated information and recommendations critically
Recognise when AI outputs require further challenge or verification
Determine where human judgement must take precedence
Apply appropriate human oversight to AI-supported decisions
Maintain clear ownership and accountability for final decisions
Human
Judgement
AI-Assisted
Decision-Making
Critical Thinking & Challenge
Human Oversight & Risk
Decision
Accountability
Core Areas
Understanding how AI is entering organisational decision-making
Distinguishing AI-generated information, recommendations and decisions
Understanding what AI can contribute to decision-making
Recognising the limitations of AI-generated outputs
Understanding why confidence does not equal correctness
Identifying the risks of automation bias and over-reliance
Understanding the continuing role of experience and context
Defining the manager's responsibility for human judgement
Understanding where AI-generated information comes from
Assessing relevance, reliability and completeness
Distinguishing evidence from generated interpretation
Identifying unsupported assumptions
Recognising potential bias and distortion
Checking information against appropriate sources
Identifying what may be missing from an AI response
Developing disciplined verification practices
Understanding the strengths of human and machine judgement
Determining when AI should inform rather than decide
Identifying decisions requiring significant human oversight
Applying organisational context to AI recommendations
Incorporating experience, values and stakeholder implications
Challenging AI-generated options
Using AI to broaden rather than narrow management thinking
Building effective Human \+ AI decision processes
Understanding accountability in AI-supported decisions
Identifying high-impact and sensitive decisions
Recognising fairness and ethical considerations
Understanding when explainability becomes important
Determining appropriate levels of human review
Establishing escalation for uncertain or high-risk outputs
Avoiding the transfer of accountability to technology
Documenting important Human \+ AI decisions appropriately
Creating clear boundaries for AI-supported decision-making
Establishing human decision rights
Designing proportionate review and challenge
Building critical thinking into management routines
Knowing when to reject an AI recommendation
Learning from AI-supported decision outcomes
Strengthening judgement as AI capability develops
Developing a Human \+ AI Decisions™ action plan

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