Getting Enterprise AI Right: Why Mid-Market Firms Stand to Gain the Most

The latest State of Enterprise AI 2025 report from OpenAI paints a clear picture: organisations that get AI right aren’t just saving time—they’re growing faster, delivering better customer experiences, and building foundations for entirely new business models. And while many of the headline examples come from giants like BBVA, Intercom and Lowe’s, the lessons are directly transferable to mid-market firms across the UK.

In fact, the data shows that the gap between “leaders” and “laggards” is widening, but not because of access to technology. It’s about readiness, workflow integration, and the ability to scale AI safely and systematically.

AI Is Already Delivering Measurable Productivity Gains

The report highlights striking improvements in day-to-day productivity:

• 75% of enterprise workers say AI improves speed or quality of work.
• Workers save 40–60 minutes per active day, rising to 60–80 minutes in technical and analytic functions.
• Coding and analytical work is increasingly performed by non-technical roles, with a 36% increase in coding-related messages from non-engineering staff.

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For mid-market firms—where teams wear multiple hats and capacity is always stretched—this uplift is transformative. You don’t need thousands of staff to see the compounding value of reclaiming an hour a day per person.

At Disruption Works, we see this repeatedly: once fragmented processes are centralised and the right automations plugged into a single operating platform, these gains appear in weeks, not years.

Customer Experience Is Where AI Shifts the Dial

Enterprise case studies in the report show that AI is now core infrastructure, not an experiment:

• Intercom’s Fin Voice resolves 53% of phone calls end-to-end thanks to low-latency AI voice interaction.
• Lowe’s Mylow Companion more than doubled conversion rates for online shoppers and improved in-store satisfaction by 200 basis points.
• Indeed’s Career Scout helped jobseekers apply to relevant roles 7x faster and increased hires by 38%.

These outcomes translate perfectly for mid-market UK organisations—whether that’s a service desk resolving inbound queries, a retailer providing guided buying advice, or a utilities firm triaging customer requests automatically.

Our own deployments show similar patterns: AI assistants that handle 30–70% of inbound traffic, voicebots that instantly resolve common queries, or automated triage that shaves minutes off every ticket. The technologies are now mature; the differentiator is integration.

The Emerging Divide: Leaders Versus the Rest

One of the most striking findings is the growing capability gap:

• Frontier workers produce 6x more AI messages than median users.
• In coding tasks, that gap stretches to 17x. (we use it all the time and it is incredible)
• Frontier firms generate 7x more messages to GPTs per seat, signalling deep workflow integration.
• Shockingly, 19% of enterprise users have never used data analysis tools inside ChatGPT.

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This divide isn’t about who has the best model. Everyone has access to the same tools. What separates leaders is organisational readiness and the ability to embed AI across workflows—precisely the challenges mid-market companies face when dealing with legacy systems, siloed data, or inconsistent processes.

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What Leading Firms Do Differently (and what you can take from this)

The report distils the behaviour of high-performing AI organisations into five key tips or areas to take note of;

Deep system integration with real business context

Leaders don’t keep AI separate. They connect it securely to CRMs, ERPs, ticketing platforms and internal documentation—unlocking accurate, automated decision-making.

And that is great new to you because

You don’t need enterprise-scale budgets—just clear data pathways, accessible APIs and controlled governance. This is exactly why our AI readiness audits focus first on platform consolidation and data access.

Workflow standardisation and reuse

Top performers create libraries of repeatable automations and GPTs. Some organisations now use thousands of custom GPTs embedded in daily operations.

So just start at the beginning

Start with a single department—service desk, operations, customer support—and create reusable automations that cut manual effort. This compounds rapidly.

Executive sponsorship

It is all about commitment, in the report AI leaders set clear mandates, commit resources, and create protected space for experimentation.

So if you too are serious..

Set up a small steering group with practical authority that is enough to prevent “side-project syndrome” or siloed efforts.

Data readiness and continuous evaluation

Leading firms codify institutional knowledge, establish data pipelines, and measure performance rigorously.

So for a medium sized business

This is where many firms stumble. Our assessments often surface 30–45% process inefficiency caused by fragmented tools and inconsistent data. Fixing this unlocks everything else.

Deliberate change management

Distributed AI champions, training, and governance accelerate adoption.

Mid-market translation

You don’t need an AI department—you need a few motivated people backed by a clear plan.

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Why Now Is the Right Moment for UK Mid-Market Firms

The report shows international growth accelerating rapidly, with the UK ranking among the largest ChatGPT Enterprise markets outside the US.  Mid-market companies that act now can still leapfrog slower competitors.

But the firms that win aren’t those who rush to install AI tools—they’re the ones who first get AI-ready: consolidating systems, establishing clean workflows, and building integration pathways.

Exactly the approach we take at Disruption Works:

‍Assess → Align → Pilot → Scale.

A structured, ROI-led route that avoids the missteps many early adopters made.

So the upshot is: AI Is No Longer Optional

We have been saying this for the last few years, but the evidence is getting more persuasive every day and the report makes it clear: AI is moving from productivity enhancer to core infrastructure. The question for mid-market UK businesses isn’t whether to adopt AI—it’s whether they’ll do it in a way that compounds value or creates complexity.

Those who invest in readiness, integration, and repeatable workflows will see the same gains as the enterprise leaders—just on a faster, more focused trajectory.

The opportunity is here. The firms that move now will define the next decade of competitive advantage.