Interactive assessment
Human Sustainability Risk Assessment
Evaluate whether your organisation's AI adoption pace is creating conditions for sustained human performance — or depleting the capacity it depends on.
AI systems operate continuously. The people working alongside them do not. This assessment measures four factors — cognitive load, recovery adequacy, boundary health, and autonomous cycle pressure — that together determine whether your human-AI operating model is building or consuming human capacity. Based on Deloitte's 2026 Global Human Capital Trends research, WEF's Future of Jobs analysis, and neuroscientific research on cognitive performance and brain health (Maslach and Leiter, 2016; Eyre and Bhugra, 2023).
- Questions or items
- 20 questions or items
- Completion time
- Around 12 minutes
- Dimensions
- Cognitive Load, Recovery Adequacy, Boundary Health, Autonomous Cycle Pressure
- What you receive
- Personalised results with configured interpretation bands, section scores and development guidance.
What it covers
- Cognitive Load
- Recovery Adequacy
- Boundary Health
- Autonomous Cycle Pressure
Rate each statement from 1 (Strongly Disagree) to 5 (Strongly Agree). Answer based on what is consistently true across the organisation or team you are assessing — not on individual exceptions or best-case scenarios.
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.
Cognitive Load
Cognitive load refers to the total amount of mental effort being used at any given time. When cognitive load is consistently high without adequate relief, the quality of judgment, creativity, and decision-making deteriorates — often before people consciously recognise the problem (Kahneman, 2011).
- People in this organisation have adequate time for focused, uninterrupted thinking on complex tasks
- The volume of information people are expected to process each day is manageable without significant cognitive strain
- Meetings and interruptions are structured to protect blocks of deep work rather than fragment them
- People are not regularly making high-stakes decisions under time pressure that does not reflect genuine urgency
- The organisation actively monitors and responds to signs of cognitive overload in its teams
Recovery Adequacy
Recovery is not a productivity luxury. It is the biological process through which cognitive capacity is restored and consolidated. Organisations that structurally prevent adequate recovery are systematically degrading the human capital they depend on (Maslach and Leiter, 2016).
- People are able to disconnect from work during evenings and weekends without implicit or explicit professional penalty
- Leave is taken at the rate it is accrued — there is not a systemic pattern of people accumulating unused leave
- Leaders in this organisation model healthy recovery practices rather than signalling availability at all hours
- There are structured recovery periods within working days — people are not expected to be cognitively active for eight or more hours without breaks
- People who take time away from work to recover return to the same workload — it has not accumulated in ways that defeat the purpose of recovery
Boundary Health
Boundaries between work and recovery are being eroded structurally in many organisations — not because of individual failures of self-discipline but because technology and culture have removed the natural friction that previously enforced them. Healthy boundaries are an organisational design responsibility (Deloitte, 2026).
- There are clear organisational norms about when it is and is not appropriate to send messages and expect responses
- Technology tools (messaging platforms, email, collaboration software) are configured in ways that support boundaries rather than eroding them
- Senior leaders respect the stated boundaries of their team members rather than routinely overriding them
- People feel genuinely empowered to enforce their own boundaries without professional risk
- The organisation has reviewed its human-AI workflow handoff points to ensure they do not create always-on expectations for humans
Autonomous Cycle Pressure
As AI agents operate continuously, they generate outputs, recommendations, and escalations outside of human working hours. If human review and response is implicitly or explicitly expected to match this pace, the result is a structural erosion of recovery that no individual policy can address. This dimension measures whether the organisation has designed consciously for this risk (WEF, 2025).
- AI-generated outputs and recommendations that require human review are batched or scheduled rather than arriving as continuous notifications
- The organisation has explicitly designed the timing of human-AI handoff points to respect human working hours
- Escalations from autonomous AI systems to human supervisors follow defined protocols that do not create expectations of immediate out-of-hours response
- Leaders have audited their human-AI workflows to identify which escalation points genuinely require immediate human response and which are technical artefacts of system design
- The organisation distinguishes clearly between genuine operational urgency and the ambient urgency created by always-on AI systems
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.
- High Risk, 20 to 45: The pattern across your responses indicates significant human sustainability risk. Multiple dimensions are showing conditions that, if sustained, will produce cognitive capacity degradation, capability loss, and high turnover among your highest-performing people — typically before those consequences are visible in standard metrics. The most urgent action is not a wellness programme but an operating model review: identify which of the four dimensions scores lowest and treat it as a design problem, not an individual problem. Start with the section with the lowest score. If it is autonomous cycle pressure, the intervention is a human-AI workflow audit — mapping every point where AI outputs require human review and designing the timing of those handoffs deliberately. If it is boundary health, the intervention is leadership behaviour change, starting with the most senior person in the unit being assessed.
- Moderate Risk, 46 to 65: Your organisation has some of the conditions for sustainable human performance in place, but significant gaps remain in at least one dimension. The risk at this level is that the gaps are not yet producing visible crisis — which makes them easy to defer. The research on cognitive capacity depletion shows that degradation is largely invisible until it becomes severe. Look at your lowest-scoring section and ask: what specific operating model or cultural change would move that score by ten points? The answer is almost never a training programme or a wellness initiative. It is a design decision about how work is structured and what leaders model.
- Adequate, 66 to 82: Your organisation is managing human sustainability reasonably well across most dimensions, with some areas for improvement. The most valuable next step is to identify your lowest-scoring section and design a targeted intervention — not a broad programme but a specific change to how work is structured or how leaders behave in that dimension. At this level, the greatest risk is complacency: as AI capabilities expand and autonomous cycle pressure increases, what is adequate today may not be adequate in twelve months without proactive design. Use the next planning cycle to embed human sustainability as a standing agenda item in your leadership team's operating rhythm.
- Sustainable, 83 to 100: Your organisation's human-AI operating model appears to be designed for sustainability across all four dimensions. The cognitive infrastructure your people need to perform at their best is largely in place. The priority at this level is maintaining what has been built — particularly as AI capabilities expand and the autonomous cycle pressure dimension becomes increasingly consequential. Two disciplines are worth building if they are not already in place: a regular review cadence (quarterly) specifically focused on human sustainability indicators, and explicit governance of new AI deployments that includes a human sustainability impact assessment before rollout.
Sources named in this diagnostic
- Deloitte (2026) Global Human Capital Trends 2026. New York: Deloitte Insights.
- World Economic Forum (2025) Future of Jobs Report 2025. Geneva: WEF.
- Eyre, H.A. and Bhugra, D. (2023) Brain capital: a new framework for mental health investment. World Psychiatry, 22(1), pp. 1–3.
- Kahneman, D. (2011) Thinking, Fast and Slow. London: Penguin.
- Maslach, C. and Leiter, M.P. (2016) Understanding the burnout experience: recent research and its implications for psychiatry. World Psychiatry, 15(2), pp. 103–111.
Where to take the next step
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Explore Leadership DevelopmentFrequently asked questions
What does the Human Sustainability Risk Assessment measure?
AI systems operate continuously. The people working alongside them do not. This assessment measures four factors — cognitive load, recovery adequacy, boundary health, and autonomous cycle pressure — that together determine whether your human-AI operating model is building or consuming human capacity. Based on Deloitte's 2026 Global Human Capital Trends research, WEF's Future of Jobs analysis, and neuroscientific research on cognitive performance and brain health (Maslach and Leiter, 2016; Eyre and Bhugra, 2023).
How many questions are in the Human Sustainability Risk Assessment?
It contains 20 questions grouped into 4 dimensions: Cognitive Load, Recovery Adequacy, Boundary Health, Autonomous Cycle Pressure.
How is the Human Sustainability Risk Assessment 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 Human Sustainability Risk Assessment?
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.