AI is making your organisation faster. That’s not the same as making it better.

AI is making your organisation faster. That’s not the same as making it better.

Plus: The prep brief that hid the gaps, and what the rep walked into

From the aibl team

Dr Laura Weis leads human-AI strategy globally at WPP. She spends most of her time observing and learning from what happens when AI lands inside large, complex organisations. Put it on a well-functioning organisation and it multiplies what’s working; put it on one that isn’t and problems are amplified.

And even where the process is sound, the instinct is to use AI to do more of the same, faster.

Leadership sees throughput rise and reads it as progress, which it is, but only to a point. The work hasn’t fundamentally changed. Put a client brief into an AI tool and you get twenty plausible responses. Humans are left choosing between them with no clearer basis for deciding than before.

This matches what we often hear from mid-market businesses. Individuals feel faster but organisations can’t scale the gains, and the space to think beyond what AI produces by default mostly goes unused.

Her starting point: find where the work currently breaks, then redesign those workflows with AI embedded rather than bolted on. Grunt work first, not the impressive-sounding use cases. The real measure isn’t speed per se, but whether AI is helping the business make better decisions where it counts. Most companies aren’t taking this approach. Laura’s full conversation is below.

If your organisation was already struggling, AI will just make it louder

AI is the ultimate fix: bring in the tools, improve the numbers, move faster. Dr Laura Weis, Global Human AI Strategy Lead at WPP, thinks that framing is the first mistake.

“It makes good working systems better, multiplies value there. But if you have an organisation that structurally isn’t clear, where there’s ambiguity, where the culture isn’t what it should be, there’s no psychological safety, or people are super stretched and inject AI on into these systems, you just increase noise, and they get worse and worse. It’s an amplifier.”

“You see a lot of what I call shadow work: rework that piles up because the first passes aren’t strong enough. You look under the hood and then have to rework a lot. Usually your strong performers get tied into a lot of correction and editing, and that’s not where they’re best placed.” AI polishes the surface, leadership sees the speed, and the strain lands on whoever fixes what’s underneath.

Speed Is Not a Strategy

That’s the problem when AI lands on a broken system. AI gives organisations two things, Laura argues. Speed, which has absorbed most of the attention over the last two years. And space: time to think, to challenge, to connect ideas that weren’t connected before. As Michael Porter said, speed is not a strategy.

At WPP, the internal narrative has shifted over the last year from quicker production to better decision-making. Laura sees the wider pattern: in times of ambiguity, organisations focus on what’s going away rather than what’s emerging, protecting what they have rather than building toward what’s possible. The efficiency question doesn’t go away, but it’s no longer the primary one.

Very few organisations can currently show they’re saving meaningful time while holding quality steady, partly because they’ve put AI on top of old ways of working without redesigning them. “On an individual level, a lot of people are feeling that efficiency, but we can’t scale it.” It’s the gap aibl hears about most often: individuals feel faster, but leaders can’t find the saving in the numbers. The bottleneck isn’t the tool. It’s the decision-making structures and workflows around it that haven’t kept pace.

Watch the full video interview:

How a better prep process created a new problem

This week we spoke to the head of sales at a mid-market SaaS firm selling compliance and scheduling software to care and housing operators. Several months earlier, one of her reps had walked into a late-stage meeting with less command of the detail than he realised.

The client’s procurement team had joined for the first time and wanted detail on expansion terms. The rep knew they’d agreed to a pilot but couldn’t share the conditions when asked: which regions were in scope, what the review criteria were, whether a timeline had been discussed.

The meeting ended with a list of points to go back and clarify, and what had felt like a formality started to feel less certain. Fortunately, the deal eventually went through, but it took another two weeks to get procurement back on a call.

The firm had been using AI-generated prep briefs for several months by that point. Before that, reps built context from notes and whatever they’d retained from the last call. The issue now was that the prompt had been written to give reps something clear and confident before they walked into the room. But it had also flattened any ambiguity that was still under discussion.

Product spotlight of the week

This week we’ve been tracking Decagon, a platform picking up traction with CX and ops leaders caught between basic chatbots and full bespoke builds: capable enough to automate complex customer journeys, without the engineering overhead either option typically demands.

Decagon builds AI agents that handle full customer journeys, not just FAQ deflection. Agents can process refunds, manage bookings, and update accounts across chat, email, voice, and SMS from a single layer. Workflows are defined through natural language “Agent Operating Procedures” rather than code, so CX ops can iterate without pulling engineers into every change.

Some deployments report deflection rates above 80% and lower cost per conversation across several documented cases. Core infrastructure is up and running in days rather than months. It’s the deployment model aibl has been watching for in this space: enterprise-grade without needing an enterprise team behind it.

It works best where helpdesk, CRM, and knowledge base are already in reasonable shape; the agents need something solid to connect to.

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