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    Interactive assessment

    Shadow AI Exposure Check

    A 15-statement team reflection on the conditions that make AI use at work easier or harder to see and discuss.

    Rate each statement about your team from strongly disagree to strongly agree. Each describes a condition that supports open AI use, so disagreement raises the exposure score.

    Questions or items
    15 questions or items
    Completion time
    About 4 minutes
    Dimensions
    Guidance clarity, Training coverage, Tool access, Stigma and job-security worry, Transparency norms
    What you receive
    A 0 to 100 exposure score with an interpretation band, a permission-to-transparency gap chart across five dimensions and three targeted actions.

    What it covers

    • Guidance clarity
    • Training coverage
    • Tool access
    • Stigma and job-security worry
    • Transparency norms

    Results: A 0 to 100 exposure score with an interpretation band, a permission-to-transparency gap chart across five dimensions and three targeted actions.

    How this interactive tool 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 then presents the route's existing prompts, controls and completion behaviour.

    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.

    What you will work through

    These are the sections and prompts already used by this route. They describe the scope of the interactive experience and the information it asks you to consider before it creates a result, printable card or saved browser document.

    Guidance clarity

    Whether the team knows which AI tools are approved, what must never be entered into them, and why the organisation wants AI used. A higher score here means: people are less sure what is allowed, so some will guess, some will avoid AI altogether and some will use personal tools without saying so.

    • Our team knows which AI tools are approved for work tasks.
    • Our team knows what information must never be entered into an AI tool.
    • The reasons our organisation wants AI used, and how, have been explained to the team in plain terms.

    Training coverage

    Whether everyone has had practical guidance on safe and effective use, knows how to check output and has time to practise. A higher score here means: without shared practice, people learn alone and in private, quality checks vary and mistakes are less likely to surface.

    • Everyone in the team has had practical guidance on using AI safely and effectively for their own work.
    • People know how to check AI output for errors before relying on it.
    • Time is set aside for the team to practise and share AI techniques.

    Tool access

    Whether approved tools cover the tasks people want AI help with, and whether there is a quick route to request something new. A higher score here means: when approved tools do not fit the work, people who want AI help are more likely to use personal accounts or unapproved tools to get it.

    • The approved AI tools cover the tasks people in the team actually want AI help with.
    • Someone who needs a new AI tool knows how to request it and gets a timely answer.
    • People do not need personal accounts or personal subscriptions to get their work done with AI.

    Stigma and job-security worry

    Whether people can say they used AI without it reflecting badly on them, and whether worries about roles have been discussed openly. A higher score here means: if admitting AI use feels risky to someone's reputation or job, people have a reason to keep it quiet even when it is permitted.

    • People in the team can say they used AI on a piece of work without it reflecting badly on them.
    • How AI may affect roles in the team has been discussed openly and honestly.
    • People do not seem worried that visible AI use will make managers think their job could be automated.

    Transparency norms

    Whether saying when AI contributed to work is normal, mistakes are shared, and people could raise an unapproved tool safely. A higher score here means: where disclosure is not normal, AI use stays invisible, errors are not shared and the team cannot learn from what already works.

    • It is normal in our team to say when AI contributed to a piece of work.
    • Team members share AI mistakes and near misses so that others can learn from them.
    • If someone were using an unapproved AI tool, they would feel able to raise it so a safer route could be found.

    What happens after you complete it

    Results appear on screen as soon as all 15 statements have answers. Each statement describes a condition that makes AI use easier to discuss openly. A higher exposure score means you disagreed more with those statements: guidance is less clear, training is thinner, approved tools fit the work less well, worry about AI use is higher or disclosure is less normal. Where those conditions are weak, AI use is harder to see and harder to talk about, so the team is more exposed to quiet, unsanctioned use. Scores run from 0 (every condition strongly in place) to 100 (every condition strongly absent). Dimension scores are the average of their three statements, and the three actions come from the highest-exposure dimensions. You can also ask for a printable team conversation guide and AI charter starter by email. This check is a structured reflection, not a validated psychometric instrument, an audit or a security risk assessment. It records one person's view of the conditions around AI use in a team. It does not measure how much hidden AI use is happening, and a low score does not show that none is.

    Where to take the next step

    Develop the narrative, role modelling, psychological safety and team norms that make AI use visible and safe.

    Explore Adopt: Leading AI Adoption

    Frequently asked questions

    What is shadow AI?

    Shadow AI is the use of generative AI tools for work without the employer's knowledge or approval.

    Who should complete the Shadow AI Exposure Check?

    A manager can complete it about their own team in about four minutes. For a richer conversation, ask team members to complete it individually and compare where your answers differ, rather than averaging them.

    What does a higher exposure score mean?

    A higher score means more disagreement with statements describing clear guidance, practical training, suitable approved tools, low stigma and open disclosure. It shows where AI use is harder to see and discuss. It does not measure how much hidden use is happening.

    Is this a validated risk assessment?

    No. It is a structured reflection for team conversations, not a validated psychometric scale, audit or security risk assessment. Use it alongside your organisation's information-security and data-protection advice.

    Why are the Deloitte figures not a benchmark for my score?

    The Deloitte percentages describe specific survey groups, such as GenAI users or weekly users, answering different questions. Your score is a 0 to 100 reflection score for one team. They are not on the same scale, so they are shown as context only.

    What do I receive by email?

    If you ask for it, we email a printable team conversation guide ordered by your highest-exposure dimensions, and a printable AI charter starter your team can complete together. Your results are shown on screen whether or not you request the email.