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    Interactive assessment

    Augmented Team Leadership Diagnostic

    A structured assessment of how well you lead a human-AI team day to day across five dimensions: task allocation and complementarity, workflow redesign, orchestration and verification, decision rights and accountability, and capacity, wellbeing and the human experience.

    Impact comes from redesigning work around human-AI collaboration, not from automating tasks in isolation (McKinsey & Company, 2026). Leaders must allocate work deliberately across people and AI, brief and verify like an agent boss, hold decision rights explicitly, and protect the human experience of augmentation. This diagnostic, which underpins the Leading Augmented Teams module, helps you assess how deliberately you lead your augmented team, so you can improve performance without eroding judgement, skill or wellbeing.

    Questions or items
    25 questions or items
    Completion time
    Around 10 minutes
    Dimensions
    Task Allocation & Complementarity, Workflow Redesign, Orchestration & Verification, Decision Rights & Accountability, Capacity, Wellbeing & Human Experience
    What you receive
    Personalised results with configured interpretation bands, section scores and development guidance.

    What it covers

    • Task Allocation & Complementarity
    • Workflow Redesign
    • Orchestration & Verification
    • Decision Rights & Accountability
    • Capacity, Wellbeing & Human Experience

    Answer for a real team you lead where AI is in live use. Rate each statement from 1 (Strongly Disagree) to 5 (Strongly Agree). The diagnostic is most valuable when it reflects reality, not aspiration.

    Results: Personalised results with configured interpretation bands, section scores and development guidance.

    How this interactive diagnostic works

    This page provides the documented overview before the interactive experience is loaded. It lets you read the purpose, the material covered and the way the result is presented without entering answers or sending a request. When you choose to continue, the interactive version uses the same material shown here. It records your selections while you work and only calculates its result when its required items are complete.

    The interactive experience remains responsible for its own input, score and lead-capture step. Where the route requests a first name and work email, its existing form handles validation and submission. This overview does not replace those steps or submit a lead.

    Statements in this diagnostic

    The interactive version groups the statements below by section. Read them in relation to the situation named in the instructions, then use the response scale shown by the diagnostic. The section descriptions are part of the existing configuration and explain the aspect each group is intended to examine.

    Task Allocation & Complementarity

    Value depends on deliberate judgement about which tasks are delegated to AI, which stay human, and which are shared, reasoned through nuance, stakes, empathy and accountability rather than left to individual habit (Dell'Acqua et al., 2023; Raisch and Krakowski, 2021).

    1. I use a clear frame to decide which tasks go to AI, which stay human, and which are shared
    2. My allocation decisions reason explicitly about nuance, stakes, empathy and accountability
    3. My team shares a common understanding of what AI should and should not do in our work
    4. I can explain what specifically makes a given task human work rather than AI work
    5. I revisit our human-AI task allocation as tools and the work change, rather than fixing it once

    Workflow Redesign

    Redesigning a workflow end to end, so that steps disappear, merge or invert once AI is in the flow, drives impact where task-level automation does not (McKinsey & Company, 2026). Redesign done with the team as co-design outperforms change imposed upon it (Deloitte, 2026).

    1. I have redesigned at least one real workflow end to end around human-AI collaboration
    2. I look for where AI changes the shape of the work, not just where it speeds up existing steps
    3. I redesign workflows with my team as a co-design rather than imposing changes on them
    4. Our redesigned workflows have documented before and after states
    5. Our redesigns would survive contact with the team's busiest week

    Orchestration & Verification

    Leading augmented work means briefing AI with clear intent and quality bars, coordinating multiple tools or agents, and verifying in proportion to the stakes, avoiding both over-reliance on fluent but wrong output and gains-cancelling over-checking (Microsoft, 2026).

    1. I brief AI tools and agents with clear intent and explicit quality bars
    2. I can decompose complex work and coordinate across multiple tools or agents where relevant
    3. I run verification that is proportionate to the stakes, avoiding both over-reliance and over-checking
    4. I calibrate my trust in AI output case by case rather than trusting or distrusting it wholesale
    5. My team has adopted a shared standard for verifying AI output before it is used

    Decision Rights & Accountability

    Clear decision rights reduce paralysis and risk when humans and AI work together: where AI acts, where it recommends, where humans decide, and who is accountable (Raisch and Krakowski, 2021).

    1. My team has agreed, in writing, where AI may act, where it recommends, and where humans decide
    2. A named human is accountable for every consequential outcome AI contributes to
    3. People on my team know when and how they can override an AI recommendation
    4. We have a clear escalation route when AI output is questioned or appears wrong
    5. Our decision rights are visible and used, not just documented once

    Capacity, Wellbeing & Human Experience

    Augmentation only creates value if released capacity is reinvested into higher-value work and the human experience is protected: workload, skill maintenance, meaning and fairness, watching for skill atrophy, hidden overwork and erosion of judgement (DDI, 2026).

    1. I quantify the capacity that augmentation releases and reinvest it into higher-value work
    2. I update roles, objectives and development plans to reflect the new shape of jobs
    3. I monitor workload, skill maintenance, meaning and fairness in my augmented team
    4. I watch for skill atrophy, hidden overwork and erosion of judgement, and act on what I see
    5. I keep my team's habits of critical evaluation alive rather than letting them fade

    How the result is read

    The interactive diagnostic totals the selected item scores by section and across the whole assessment. It then matches those totals to the configured interpretation bands and shows the section-level results alongside the overall result.

    • Getting started, 25 to 50: Your team's use of AI is not yet deliberately led. Task allocation, workflow design, verification and decision rights need structured attention before augmentation can improve performance safely. Begin by redesigning one real workflow end to end with your team.
    • Emerging, 51 to 75: You are developing augmented team leadership, but workflow redesign, orchestration discipline or the human experience of augmentation remain uneven. Target your two weakest dimensions and build them into your normal way of working.
    • Established, 76 to 100: You lead your augmented team deliberately across most dimensions. Strengthen the weaker areas, often decision rights or the human experience, to protect both performance and wellbeing as augmentation scales.
    • Leading, 101 to 125: You lead an augmented team to a high standard: deliberate allocation, redesigned workflows, disciplined orchestration, clear decision rights and a healthy human experience. You are ready to help other leaders redesign work around human-AI collaboration.

    Sources named in this diagnostic

    • McKinsey & Company (2026) The State of AI. New York: McKinsey Global Institute.
    • Microsoft (2026) Work Trend Index Annual Report. Redmond, WA: Microsoft.
    • Deloitte (2026) State of Generative AI in the Enterprise. New York: Deloitte AI Institute.
    • DDI (2026) Global Leadership Forecast 2026. Pittsburgh, PA: Development Dimensions International.
    • Dell'Acqua, F., McFowland, E., Mollick, E., et al. (2023) 'Navigating the jagged technological frontier', Harvard Business School Working Paper 24-013.
    • Raisch, S. and Krakowski, S. (2021) 'Artificial intelligence and management: The automation-augmentation paradox', Academy of Management Review, 46(1), pp. 192-210.

    Where to take the next step

    Our Leading Augmented Teams experience helps leaders redesign work around human-AI collaboration.

    Explore AI Leadership Readiness

    Frequently asked questions

    What does the Augmented Team Leadership Diagnostic measure?

    Impact comes from redesigning work around human-AI collaboration, not from automating tasks in isolation (McKinsey & Company, 2026). Leaders must allocate work deliberately across people and AI, brief and verify like an agent boss, hold decision rights explicitly, and protect the human experience of augmentation. This diagnostic, which underpins the Leading Augmented Teams module, helps you assess how deliberately you lead your augmented team, so you can improve performance without eroding judgement, skill or wellbeing.

    How many questions are in the Augmented Team Leadership Diagnostic?

    It contains 25 questions grouped into 5 dimensions: Task Allocation & Complementarity, Workflow Redesign, Orchestration & Verification, Decision Rights & Accountability, Capacity, Wellbeing & Human Experience.

    How is the Augmented Team Leadership Diagnostic scored?

    Responses are scored within each section and totalled across the diagnostic. The total is compared with the configured interpretation bands.

    What happens after I complete the Augmented Team Leadership Diagnostic?

    After the required items are answered, the existing first-name and email gate is shown before the results are displayed. The result includes an overall interpretation, section scores and development guidance.

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