Jannaways

Jannaways Clear thinking for complex change | Board & transformation work for purpose-led organisations

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Have you ever been part of a project where everyone was working flat out, but somehow the results didn't add up to much?...
03/09/2026

Have you ever been part of a project where everyone was working flat out, but somehow the results didn't add up to much?

It's rarely about effort. More often, different people are quietly working towards slightly different ideas of what success looks like, and nobody's noticed because it's never been said out loud.

That's what we call the Purpose lens, one of the 5 Lenses we use to help organisations see what's really going on beneath the busyness. It starts with two simple questions: why does this matter now, and who benefits if it succeeds?

Small question, big difference.

Read more: https://www.jannaways.co.uk/blog/seeing-the-whole-why-complex-change-needs-more-than-one-lens

31/08/2026

A question from our March session that I haven't been able to shake, from Andrew Whyatt-Sames: is your leadership team AI literate enough to address this, rather than just talk about it?

The default in most organisations is to hand it to IT, hand it to the governance lead, write a policy, and consider it done.

But AI is already embedded across your organisation in ways you may not have mapped. It's in your case management system, your referral tools, your HR platform, your communications. Often put there by people long since left, running on assumptions nobody has revisited.

You cannot govern what your leadership does not understand. AI literacy isn't a nice-to-have for senior teams. It's a governance prerequisite.

Read the blog here - https://www.jannaways.co.uk/blog/ai-governance-isnt-a-policy-problem.-its-a-visibility-problem

28/08/2026

The answer to AI governance isn't a better policy, a bigger risk register, or waiting for a regulator to tell you what to do.

It's every person in the organisation, from the board down to the person doing the work, taking ownership of one question: do we know where decisions are being made, and do we have what we need to challenge them if something's wrong?

That's not a technology ask. It's a culture and leadership ask. And it's entirely doable.

Thank you for following this series. If any of these have raised questions about your own organisation, start with the diagnostic or reach out directly.

Diagnostic - jannaways.co.uk/ai-governance-diagnostic

Governance Workshop with uptakeAI - uptakeai.co.uk/our-services/ai-governance-workshop

26/08/2026

We built this because we kept seeing the same thing: organisations that had policies and strategies, but could not evidence whether any of it was making a difference to how decisions were actually being made on the ground.

18 questions. Yes, Partial, No. About 15 minutes. At the end, a personalised report with recommendations.

It works as an individual exercise. It works best when a leadership team does it separately and compares answers. The gaps in the answers are usually more useful than the scores.

Check out the diagnostic tool here - jannaways.co.uk/ai-governance-diagnostic

And if you want to go further, uptakeAI runs a full-day Governance is a Team Sport workshop for leadership teams - uptakeai.co.uk/our-services/ai-governance-workshop

24/08/2026

Here's the bit most AI policies miss.

Most organisations have an AI policy. Many of those policies ban quite a lot of things. Almost none of them tell you where decisions are actually being made.

Governance aimed at the policy is governance aimed at the intention. It is not governance aimed at the practice.

If your policy is the most specific thing you have, that is where to start.

Take a look at the diagnostic tool here - jannaways.co.uk/ai-governance-diagnostic

21/08/2026

Public sector organisations are sitting on mountains of data and legacy systems. AI gets added on top. And then the question nobody asks: can we actually see the decisions being made in there?

Can we justify them? Can we audit them? Do we know if the underlying data is good?

The question is not whether your organisation has AI-influenced decisions. It does. The question is whether you have the visibility to govern them.

Check out the Ai Governance Workshops here - https://www.uptakeai.co.uk/our-services/ai-governance-workshop

19/08/2026

This is Andrew Whyatt-Sames, consultant psychologist and one of the people I recorded this session with. His point here is the one that tends to land hardest in rooms.

The IT director writes a policy. Bottom of the document: use ChatGPT and you will be sacked. They send it to everyone and go to sleep feeling they have done their job.

Meanwhile, staff are emailing work to personal laptops, running it through ChatGPT, and emailing it back. They are not being reckless. They are trying to do their jobs in an environment that has not given them sanctioned tools or real guidance.

On paper, governance looks intact. In practice, exposure is increasing and nobody is watching.

If this is happening in your organisation - and it almost certainly is - the question is not how to stop it. It is how to bring it into the open so you can actually govern it.

Read the blog here - https://www.jannaways.co.uk/blog/ai-governance-isnt-a-policy-problem.-its-a-visibility-problem

17/08/2026

Who can push the stop button?

When a decision is automated, that is the governance question that actually matters. Not "do we have a policy?" but "who can genuinely intervene, and do they know they can?"

In the housing example we walk through in this session: the coordinator could have overridden the system. But the case never reached their desk. So the override never happened.

And when the tenant complained? The complaint went back through the same system. That is not governance. That is a loop.

If you want to know where your organisation stands on questions like this, the AI Governance Readiness Diagnostic takes about 15 minutes. jannaways.co.uk/ai-governance-diagnostic

Read more about the Power Lens - https://www.jannaways.co.uk/blog/through-the-power-lens-when-seeing-the-problem-isnt-enough

14/08/2026

One of the questions I find most useful when looking at any AI system: who is the system seeing, and who is it missing?

Systems make assumptions. Every one of them. Most were baked in by someone long gone, in a context that's since changed, using data that reflects the world as it was rather than as it is.

That's where real people fall through the gap. Not through negligence. Through invisibility.

This is the People lens, one of five ways of looking at any AI use case. The template's free at jannaways.co.uk/ai-governance-diagnostic if you want to use it on your own systems.

Read more about the People Lens - https://www.jannaways.co.uk/blog/through-the-people-lens-what-hesitation-reveals-about-the-system-fullversion

12/08/2026

I have a test I use in change management work. I call it the Tuesday morning test.

If I cannot explain how a decision or a system is different for a specific person doing a specific job on a Tuesday morning - not in theory, not in policy terms, but in practice - I have not understood the real problem yet.

The same applies to AI governance. If somebody on a Tuesday morning does not know how an automated decision is influencing their work, or cannot challenge it, we are not governing it. We have just written a policy about it.

Diagnostic Link - jannaways.co.uk/ai-governance-diagnostic

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