Copilot isn't a strategy: Industrialising AI in the enterpriseCopilot isn't a strategy: Industrialising AI in the enterpriseCopilot isn't a strategy: Industrialising AI in the enterprise

Look, AI is absolutely transforming software engineering right now. But here's the thing… handing everyone Copilot and calling it a strategy is like giving someone a Ferrari and expecting them to win Formula 1. Individual tools are great, but they're not enough. Real impact comes from industrialising AI.

We recently hosted a webinar: "Copilot isn't a strategy: how to industrialise AI in the enterprise", with some seriously clever people. Dave Kerr (Head of Engineering at Quantum Black Labs, McKinsey), Katie Roberts (Technical Director here at Nearform), and I joined Helene Haughney (Global Accounts owner & SVP for Global Delivery Transformation, Nearform) to dig into this properly. For the full deep dive, you can watch the full video below. But I also wanted to pull out some of the key points that I reckon matter most.

Dave spoke about the revolution in software engineering currently happening. The real shift happening right now is that AI is transforming how we do software engineering itself, moving towards what Dave called "software engineering factories". Of course, individual engineers are seeing productivity wins. Nearform’s poll during the webinar showed that 68% of attendees are seeing gains. That's brilliant. But here's where people get it wrong: those individual supercharges don't automatically translate to organisational impact.

The honest truth? You can hand out Copilot licenses tomorrow and watch engineers code faster. But you still end up with the same bottlenecks, the same broken processes, the same burnout. You need to scale that individual productivity into a collective force - build AI-native engineering teams that can deliver actual systemic change. That's the real challenge.

We discussed the key challenges that are emerging from this new era of "big code" and asked how it changes our approach to development. Dave absolutely called it out during the webinar, and, in my opinion, he he nailed it:

"The honeymoon is over. Individual team members have superpowers, but collaboration is actually getting harder and harder and harder.”

He then asked the question we were all thinking: “If the honeymoon is over, what is marriage counselling 101?”

We came up with the following answers:

• Create time and space to learn this new world. Stop treating agentic engineering like a side project. Engineers need to actually experiment, try different approaches and figure out what works for their team.
• Build your machine. Your dev environment is your most important product. Automate everything. If you're doing something three times, it's automated.
• Work on your relationships… with your team members and with your LLMs. Your job isn't to review code anymore, it's to build feedback loops. So, when something doesn't work at first, you improve the system, the sub-agents, the skills, the processes and the collaboration.
• And communication? That's the golden skill now. Individuals can be colossally fast and productive, but that doesn't scale. We need to collaborate, communicate and find ways to make sure other people can actually work with what we're building.

Dave’s describing what at Nearform we've been calling the era of "big code". The successor to “big data”, it implies massive velocity, huge volume and insane variability. And here's a concrete example: Dave mentioned a 20,000-line pull request. You know what a human trying to review that is? Broken. It's impossible. And it's demoralising.

What happens? Burnout. Cognitive overload. Engineers who were flying three months ago now feel lost. At Nearform, we're clear on this: individual productivity gains don't automatically equal whole-team productivity. You need a fundamentally different operating model to handle this scale and complexity. Otherwise, you're just running faster towards a wall.

Many enterprises face the challenge of implementing AI in complex brownfield environments. How do we tackle this and ensure safeguards in regulated industries?

Brownfield is real. It's messy. And it's where most of us actually live, right? Katie's advice during the webinar was spot on. She said, "Don't boil the ocean”. Instead carve out smaller spaces, write clear specs, be very explicit about your intent with your LLMs and set rules around it.

Essentially, don't try to AI-enable your entire legacy codebase tomorrow. That's a recipe for disaster. Instead, isolate specific areas, strangle them out (in the technical sense) and pick spaces where you can build new features or tackle real technical debt with clear intent. Small, intentional moves. That's how you move the needle without imploding.

With AI generating so much code, how do we ensure robust safeguards and maintain accountability, especially in regulated industries?

Agents can't be held accountable when things go wrong. That's on us.

So safeguards aren't optional, they're non-negotiable. At Nearform, we're building a ‘trust stack’ in parallel to the tech stack, integrating layers of rigour across the entire SDLC:

• Static analysis to catch obvious issues
• Agent-based code reviews that actually understand intent
• Eval suites to validate behaviour
• Formal methods where it matters
• AI red teams for threat modelling
• Clear accountability chains so everyone knows who's responsible for what

The goal here is simple - velocity increases, but stability and security never take a hit. You want to move fast? Grand. But not at the cost of trust.

Industrialising AI in your enterprise isn't optional anymore, it's how you stay competitive. And while it's not straightforward, it's absolutely doable. It starts with being honest about where you actually are right now. Then, it’s about creating a clear roadmap and working with a partner who's actually done this in the real world. Not outsiders talking theory, but the practitioners shipping it.

At Nearform, we're on the front lines - navigating brownfield complexity, shipping robust safeguards and scaling teams to become agentic factories.

It’s the enterprise engineers who should be the heroes here. For those organisations ready to move past one-off productivity gains and unlock what AI can actually do at scale, get in touch. In the meantime, our Impact Talks series continues with the next webinar, The AI execution gap is opening. Which side of it are you on? on June 16th. Register here to secure your spot to learn how to be on the winning side of the gap.