The AI isn’t happening to you. You’re shaping it.

Plus: The human conditions separating firms that measure AI efficiency from those still chasing it.

From the aibl team

I’ve been thinking about perspective and how nearly impossible it is to step back from the day to day. Whether it was the first truly smart phone or real time data systems, these evolutionary steps are too big to digest on our own.

We look for research and smart opinion, but the attention economy rewards hot takes and their hotter responses. Soon enough, the land grab takes every POV, and we’re left to sift through the experts and decide who to trust. People being people, this ends up being as much an emotional choice as a rational one.

So it was in this context that I found our interview with Ed de Minckwitz grounding and refreshing. He’s honest about our frailties as humans and organisations, and offers insightful and sensible ways to work with, not against, them.

I’ve also been thinking about efficiency. It’s arguably the primary thrust of our current stage of AI implementation, but is harder to pin down than GTM applications that can be measured in classic ROI terms.

Digging into the data from our study of 750+ mid market leaders, I split out the efficiency focused organisations, and then categorised them by whether they’ve successfully measured positive impact.

The bottom line is that the winners have built the human infrastructure for success, from strategy to governance to auditing processes before ‘transforming’ them and ensuring their people have the mental and technical resources they need. Check out the details in our research section after our interview with Ed.

Don’t let AI happen to you with Ed de Minckwitz

Ed de Minckwitz, Director of Public Policy at ServiceNow UK, doesn’t start with the technology. He starts with the people using it. ‘We are creatures of habit and we’re also, I think, enterprising creatures. We want to work, we want to endeavour. We want to feel the satisfaction of having done a thing, created a thing, or offered a service.’

That instinct gets compounded in mid-market firms. The day job is so consuming, Ed says, that teams don’t have the bandwidth, the resource, the senior cover, or the space to stop and redesign how they work.

When change does come from the top, it arrives framed as efficiency which can threaten what people find meaningful without showing them what might improve. The tech industry tries to underscore that AI will do the grunt work and leave the interesting bits, but everyone is busy and deep down, uncomfortable with change.

Most people, as Ed puts it, are flying the plane, not thinking about how to re-engineer and build the next generation of aircraft.

Watch the full video interview:

aibl’s Research: The Human Conditions for AI-Driven Efficiency

After digesting too many charts, my takeaway was that successful mid-markets focused on efficiency have built the conditions for measurement: top-down ownership, strategic alignment, formal governance, and deliberate people enablement.

Over 70% of the success group passed the ‘5 managers test’ and believe at least 4 of 5 managers would name the same AI priorities, versus the group still pursuing ROI, where nearly half say only 3 of 5 would agree. Strategic coherence is a clear differentiator for efficiency returns (and revenue, but we’ll get to that next week). The firms that can measure ROI are also the ones where leadership is pulling in the same direction.

Finally, I was interested to see that PE-backed firms dominate the success group, while the rest skew heavily toward privately held firms with no institutional backing. The pressure and performance culture of PE ownership appears to be a meaningful accelerant for actually measuring and proving efficiency gains.

For those in that second group, there are ways to borrow from PE culture without adopting it. Make the choice to impose a small number of non-negotiable metrics and review them relentlessly, with accountability on the line. Define success before you deploy. Set a countdown clock to create urgency and don’t let things drift. The trick is to use shared success as the driving force, rather than the fear of failure that often powers PE backed companies.

Product spotlight of the week

This week we’ve been looking at Fin, Intercom’s AI customer agent, and it’s become one of the more practical options we’re tracking for mid-market support teams.

Fin handles inbound queries across chat, email, and messaging, deflecting routine tickets before they reach a human. For firms already on Salesforce, HubSpot, or Freshworks, it runs on top of those platforms without requiring a migration.

In individual deployments, Intercom’s own case studies show resolution rates of 42–50%. At $0.99 per outcome, you pay for what Fin resolves, not for access to it.

There’s a 14-day free trial via this link.

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