FOMO is enough to start a pilot. It’s not enough to finish one.

Plus: The Ops and Finance leaders designing AI programmes they don’t personally run

From the aibl team

This week we spoke to Paul O’Sullivan, CTO of Salesforce UK, who pointed out that the best agentic solutions are increasingly hard to tell apart from human conversations. Salesforce recently ran a Turing test at their AI Centre where the audience couldn’t reliably pick the AI from the human after a five-minute conversation.

Most mid-market deployments are nowhere near that level. For many of the firms we speak to, very few initiatives are making it out of pilot purgatory at all.

Paul’s advice is to pick one use case, narrow the scope, and connect it to a measurable outcome from the start. Customers who approach it that way are getting pilots into production in ninety days and seeing resolution rates above 80 per cent, as Paul explains in the interview below.

Elsewhere, we’re continuing to share some early findings from our mid-market AI survey of 750+ senior leaders. Last week we looked at strategy and alignment across the organisation. This time it’s all about you and your relationship with AI.

We asked survey participants to describe their level of AI use, and break it down by their area and seniority. It’ll give you a good idea of how you compare to your peers. We also look at a correlation between personal sophistication and positive ROI. We can’t say if it’s chicken or egg, but it’s definitely worth noting.

Moving AI from pilot to production: Salesforce’s Paul O’Sullivan on avoiding FOMO investment

For Paul O’Sullivan, CTO of Salesforce UK and Ireland, the story of how organisations responded to generative AI comes in two stages: wonder, then panic. Senior execs looked sideways at competitors and decided they had to move, not because there was a clear problem to solve, but because standing still felt dangerous. “Lots of organisations and lots of senior execs immediately went, well, they’re doing it. I’ve got to do it.”

The result, in Paul’s words, was investment for the sake of it. “FOMO will get you to a pilot, but having real intention around your transformation… is going to drive real business results. When you’ve applied strategic thinking to what you’re trying to actually unlock within your business, it will see you beyond the pilot phase.”

Where it stalls: data

For most, data is where it stalls. Fragmented systems, silos, a technology estate that built up over time but never got connected, no single view of the customer. Paul has had customers tell him they’ve spent ten years and three major programmes trying to crack their data, and still haven’t.

His advice is to stop trying to solve all of it. Start with what the first use case actually needs. “Your volume of data is all of this, right? It’s huge. But what do you really need that’s going to drive value in that one particular use case? And what you’ll find is it’s probably a small subset of data.”

Watch the full video interview:

From aibl’s survey

Sample: 755 senior mid-market executives

One of the many ways in which AI is different from the other transformative business technologies is that most of you reading this have a personal relationship with it. We asked mid-market leaders to identify how they personally use AI in their work, and before we look at the results, it might be useful for you to do the same.

How do you personally use AI?

• Non-user. I don’t use these tools in my role.
• Light use. I use them occasionally for light administrative tasks (e.g. fixing grammar, rewriting emails), but they aren’t part of my core workflow.
• Routine use. I use them regularly to speed up routine execution (e.g. summarising long documents, drafting agendas), but I do strategic thinking myself.
• Decision-enhancing use. I use them to enhance my decision-making and creativity (e.g. brainstorming strategy, challenging my assumptions, problem-solving).
• Fully integrated. These tools are fully integrated into my workflow; I start almost every significant task with AI and view it as an extension of my own capabilities.

With your answer in mind, here’s how it shakes out when we look at AI sophistication through the lenses of business area and seniority…

Product spotlight of the week

This week the aibl team has been tracking Unframe, a platform built for ops and IT leads sitting on fragmented internal data and manual workflows they know should be automated, but don’t have the internal resource to build anything themselves.

Describe the use case, whether that’s contract extraction, knowledge search, reporting or workflow automation, and Unframe assembles a working solution in days, with no model training required. It’s LLM-agnostic, deploys on-prem or private cloud, and keeps data inside your perimeter.

To get started there’s a scoping process before anything’s built. Then once you’re up and running, you only pay after the result is validated, after which it moves to a standard subscription.

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