You've Got Your AI Impact Results. Now What?

How to turn a personal insight into a conversation that actually goes somewhere.

So you've run your role through the GoFIGR AI Impact Assessment and you're looking at three pages of results that are either reassuring, surprising, or somewhere in between.

The results are yours, nobody else sees them. And right now they're probably sitting in a browser tab while you figure out what to do with them.

Here's the thing: the most valuable thing you can do with your results isn't read them alone. It's to bring them into a conversation - with your manager, your team, or whoever in your organisation is supposed to be thinking about the future of work.

Most people don't do this, and not because they don't want to, but because they're not sure how to start. "Hey, I ran an AI assessment on my job" doesn't exactly roll off the tongue.

This is a guide for making that conversation happen - what to prepare, how to frame it, and what to ask for at the end.

First: make sure you understand what you're looking at

Before you bring your results to anyone, spend five minutes with them yourself. There are three things worth paying attention to.

Your overall score and category - and what it actually means

The percentage at the top is how much of your task mix is transforming by 2030. This is the number that makes people panic, so let's be clear about what it means and what it doesn't.

Transforming is not the same as disappearing.

A task that's transforming might mean AI makes you faster at it. It might mean AI does the first draft and you review. It might mean AI handles the routine version while you handle the complex cases. In most results, only a small proportion of tasks land in the "fully automated" or "no longer needed" categories - the rest are changing how you do the work, not whether you do it at all.

Think of it this way: if 60% of your tasks are transforming, that doesn't mean 60% of your job is going away. It means 60% of your task mix is going to look different - and in most cases, different means more interesting, not redundant.

Low transformation (under 40%) means most of your work stays largely human for now. Medium (40–69%) means a solid chunk is shifting. High (70%+) means significant change is coming - which usually means a lot of opportunity to offload the tedious stuff and focus on the work that actually matters.

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The task breakdown - this is where it gets specific

Each task in your role has been placed into one of five states. Read these carefully before you talk to anyone, because the difference between them matters a lot:

• Stays with you - no AI involvement, fully human
• You lead, AI assists - you're completely in charge, AI just makes you faster and better
• AI leads, you guide - AI does the heavy lifting, but a human reviews before anything goes anywhere
• Fully automated - AI handles this end-to-end with no human in the loop
• No longer needed - the task itself becomes obsolete as the work around it changes

The first two states - "stays with you" and "you lead, AI assists" - mean your role in that task isn't going anywhere. The third - "AI leads, you guide" - means your role shifts from doing the work to reviewing and being accountable for it. The last two are the ones worth paying attention to, but in most results they're a small minority of tasks.

When you're preparing to talk to your manager, look at how your tasks are distributed across these five states. The conversation is very different if most of your shifting tasks land in "you lead, AI assists" versus "fully automated." One is an upgrade. The other is a genuine change in what your role looks like.

Look at where your time currently goes and where those tasks land. That's where the interesting conversation starts.

The skills outlook

Three columns: Double Down, Develop, and Let AI Handle.

Double Down is your foundation - skills you already have that are becoming more valuable as the routine work disappears. These are worth protecting and investing in.

Develop is where the interesting work is - skills you'll need that you may not have yet. These aren't skills you pick up in a workshop. They're built over time, and the earlier you start, the better positioned you are.

Let AI Handle is the permission slip. Stop investing time here. These skills will matter less, not more, as the tools improve.

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Before the conversation: three things to prepare

1. Know your "so what"

Your results are data. Data without interpretation doesn't land. Before you talk to anyone, decide what you think your results mean for your role, your team, and your function. You don't need a fully formed view - just a starting point. Something like: "40% of my tasks are shifting, most of them are the admin-heavy stuff I spend most of my time on, and the skills I need to build are in AI collaboration and strategic analysis."

2. Pick the right moment

Whether your results feel urgent or not, this conversation deserves proper space. Don't bring it up at the end of a 1:1 when your manager has three other things on their mind. Book a specific conversation - even 20 minutes - and frame it as "I want to talk about something I've been thinking about regarding where my role is heading." That framing signals initiative, not anxiety, which sets the tone before you've even started.

3. Decide what you want out of it

The conversation will go better if you know what you're asking for. Are you looking for your manager's view on whether the picture matches what they're seeing? Are you asking for support to develop a specific skill? Are you suggesting the team should do this together? Having a loose idea of what you want at the end makes it easier to get there.

How to frame the conversation

You don't need a presentation. You need a way in and a thread to follow.

The opener

Something simple works best. "I've been thinking about how AI is going to change my role and I did an assessment that gave me some useful data. I wanted to talk through what it showed and get your perspective."

That's it. No drama, no anxiety spiral, no "I'm worried about my job." Just curiosity and initiative - two things most managers respond well to.

Walking through your results

Start with the headline. "The assessment showed that about [X]% of my tasks are going to transform by 2030. Most of that is in the [admin / analytical / operational] work - things like [specific examples from your task breakdown]."

Then move to the skills picture. "What interested me most was the skills section. It flagged [Double Down skills] as things I should be doubling down on, and [Develop skills] as things worth starting to build. I hadn't thought much about [specific skill] before, but looking at how my tasks are shifting, it makes sense."

The question that opens the conversation

After you've walked through your results, ask something that invites your manager's perspective rather than just their reaction. A few options:

"Does this match what you're seeing about how our function is changing?"

"Are there things on the team that you think are shifting faster than this shows?"

"Is there anything in the Develop column you think would be particularly valuable to focus on given where the team is heading?"

These questions do two things: they make your manager a participant in the conversation rather than an audience, and they start surfacing information about where the team is going that you probably don't have full visibility on.

Moving from your role to the bigger question

If the conversation is going well, there's a natural next step worth raising.

Your results show one role. But the same assessment can be run across a whole team - and when multiple people compare their results, the patterns that emerge are usually the ones worth bringing to leadership.

You can raise this simply: "I was thinking it might be worth doing this as a team - even just a 30-minute session where we all try it and compare what comes up. I think it would give us a much clearer picture of where we're exposed and where we should be investing."

This shifts the conversation from "here's my individual data" to "here's something we could do together" - which is both more useful and more likely to get traction.

If your manager is interested, the GoFIGR crib sheet gives you everything you need to run a team session: [crib sheet link]

What a good outcome looks like

You're not trying to solve everything in one conversation. A good outcome is one of the following:

• Your manager has a clearer picture of how your role is shifting and what you're thinking about
• You've agreed on one or two skills worth prioritising in your development plan
• You've planted the seed for a team session if you think they might value this
• You've learned something about where the function is heading that you didn't know before

Any of these is a win. The goal isn't to have all the answers - it's to be the person in the room who brought the question.

What if the conversation doesn't go well?

Sometimes managers aren't ready for this conversation. They're in BAU, they're stretched, or AI feels abstract and distant to them.

If that happens, don't push. Leave the door open. "No worries, just something I've been thinking about - happy to revisit it when the timing's better."

And then keep building your own picture regardless. The skills in your Develop column don't need your manager's permission to work on. The awareness you now have about how your role is shifting is yours, regardless of whether your organisation is ready to talk about it yet.

The people who'll navigate this well aren't necessarily the ones with the most senior managers or the most supportive organisations. They're the ones who looked clearly at what was coming and started preparing before they had to.

Ready to try the assessment? It takes three minutes and you'll have your results instantly: app.gofigr.ai/impact-of-ai

Want to run this with your whole team? Download the GoFIGR team workshop crib sheet here: [crib sheet link]

If you're a manager or leader reading this

Individual results are useful. But when dozens or hundreds of people across your organisation take this assessment, patterns emerge - which functions are most exposed, where the skills gaps are, where you can redeploy people rather than let them go.

The organisations that get this right don't just avoid the difficult conversations. They find growth. The ones that get it wrong learn an expensive lesson about what AI can't replace.

We help organisations map this at scale - task-level analysis across whole functions, skills trajectory data, and enough clarity to walk into any leadership conversation with a point of view rather than a guess.

If that's the conversation you need to have, let's talk.

FAQs

My results show low transformation risk. Should I still worry?

Not worry, but stay alert. Low risk today doesn't mean low risk in three years - the model is based on current AI capability and that's moving fast. The more useful response is to notice which parts of your role are growing in importance and lean into those deliberately. You're in a strong position. Use it to get stronger.

My results show high transformation risk. Am I about to lose my job?

Probably not the way you're imagining. High transformation means the shape of your role is likely changing - not that it's disappearing. Look at where your tasks actually land across the five states. If most of them are in "you lead, AI assists" or "AI leads, you guide," you're still in the picture. The question is whether you're steering that change or reacting to it. Start with the conversation above and build from there.

What's the difference between the free assessment and a full organisational version?

The free tool gives you a snapshot - 10 tasks modelled against a generic AI adoption scenario. It's designed to get you started and to spark a conversation.

A full organisational assessment goes much deeper. It maps every role across your function or organisation against your specific AI adoption scenario - not a generic one. It surfaces where exposure is concentrated, where the skills gaps sit, where you can redeploy people, and where your L&D investment should actually be going. It's the difference between knowing roughly where you stand and having the data to make real decisions.

If that's what you need, let's talk.

Can we get a custom version of this for our whole company?

Yes - and it's one of the most useful things we do. When you run this across a whole team or function, patterns emerge that no individual result can show you. Which roles are most exposed. Where the same job title hides very different task realities. Where your skills investment will have the most impact. Where you can create capacity rather than just cut cost.

We work with organisations globally to map AI impact at scale - from small People functions to large enterprise workforces. If you want to understand what this looks like for your organisation, get in touch.

How accurate is the assessment?

It analyses your role at the task level using current AI capability data and our methodology, which is grounded in an International Labour Organization framework and extended significantly by the GoFIGR team. It's not a crystal ball - AI is evolving and no model can predict exactly what happens. But it's significantly more specific than the generic "X% of jobs at risk" headlines, because it looks at what you actually do, not just what you're called.

How often is the assessment updated?

We update the model regularly as AI capability evolves. The assessment reflects current AI capability - what tools can do today and what's on a credible near-term horizon. We're not modelling science fiction. We're modelling what's already technically possible or in active development, which is more than enough to be getting on with.

Is my data private?

Yes. Your results are yours - nobody else sees them. We don't share individual assessment results with employers, managers, or anyone else. The data we use to improve the model is aggregated and anonymised. If you have specific questions about how your data is handled, you can read our privacy policy here.

Can I share my results with my team?

Please do. The most valuable thing about this assessment isn't any individual result - it's what happens when people compare notes. Two people with the same job title often get quite different results, because the assessment looks at the actual task mix rather than the role label. That difference is usually the most interesting thing to talk about.

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