By Alex Smith |
Almost every organisation using AI can now produce adoption numbers on demand. Yet the business results those numbers are supposed to drive can sometimes be difficult to assess.
Nina Carøe, chief human success officer at Zensai, explains why leaders must stop treating adoption as the outcome and how Zensai’s AI platform can help measure the middle layer.
Why isn’t AI adoption the metric that matters most for companies looking to improve their operations?
Adoption is an input, not an outcome. Faster doesn’t automatically mean better. People can write, summarise and respond faster but the organisation still can’t point to a gain in revenue per employee, execution quality or speed of delivery. That’s the trap. You end up with a workforce that feels more productive and a profit and loss statement that doesn’t move.
What’s missing from the equation?
The bit in the middle that almost nobody measures. Think of it as three levels. The first one is easy: are people using AI? The third is the one the board cares about: is the business doing better? In between is the level everyone skips, which is whether your people are getting better at their jobs because of AI. Skip that and you can’t tell whether AI genuinely improved anything or if it just made a bad process run faster.
Microsoft put a number on the gap this year. They asked 20,000 people two things: how good are you with AI, and does your company give you what you need to use it well? Only about one in five respondents said yes to both. One in 10 said something more troubling – they’ve got the skills, but they work somewhere that can’t make use of them. So, the first level looks healthy, but the third one isn’t moving. Everything that explains why sits in the middle. That’s why we built the Human Success Score on the Zensai platform, which measures whether an organisation is progressing, not just whether people are using AI. It brings together signals from learning, engagement and performance to show what is happening week to week.
The point isn’t to create another metric to report on. It’s to give leaders an early signal when AI transformation is working, where adoption is getting stuck and where people need more support.
How does the Zensai platform help to coach and support employees through Microsoft 365?
The work already happens in Microsoft 365 – the meetings, the documents, the conversations – so that’s where growing at your job should happen too, not in a separate system somebody has to remember to open. The coaching turns up in Copilot and Teams, right next to the work it’s about. And, because it’s already inside your Microsoft set-up, there’s nothing extra for IT to look after: no second system to keep secure, and no new AI to sign off.
If an executive reads this on the way into Microsoft Ignite, what should they do on Monday morning?
I would frame it as stop, start, continue. Stop reporting AI usage as if it were an outcome and take those numbers off the board pack on their own. Start by naming the one business result that should move as AI maturity increases, then pick two or three things that would prove your people are getting better at the work behind it – and put a named owner and a review date on each. Continue doing whatever is already giving managers better conversations, because that is the mechanism everything else depends on, and it is usually the first thing cut when a programme gets busy.
Do those three things and you can finally answer the question your executive team is really asking: Is this working, and can we prove it?
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