How Hatmill is building internal AI readiness: Practical steps toward responsible transformation

Right now, we’re doing three things in parallel:

• Using AI on ourselves first to speed up proposals, research and internal knowledge‑sharing.
• Building the backbone of clear governance, security and ethics so we don’t cut corners with client data.
• Translating the noise by turning what’s happening in AI for SC&L into practical, Hatmill-style advice for our clients.

In the early part of 2025, we set up a firmwide AI programme with six workstreams: skills and capability, consulting tools, governance and security, client impact and thought leadership, technical foundations, and how AI will reshape our consulting model. We’re working hard to make sure this isn’t in a silo, and from the start, it’s embedded in how we design and deliver work.

We’re making measured and pragmatic progress:

• We’re not running big AI projects with clients, but we’re starting to talk about it more.
• We are running real pilots inside Hatmill, for example, an AI-assisted proposal tool and an N8N-based research assistant.  We’re using what we learn to shape how we work internally, and we’ll share it with our clients to help them build their own capability.
• We’re investing heavily in AI literacy for everyone, not just a few specialists, so that any Hatmill consultant can combine tools with judgment on client discovery work and in projects.
• We’re making conscious choices about how we use AI and developing our consulting skills accordingly to support clients in the most practical, effective way.

For our clients, this means our focus is on practical, near-term value, not science projects:

• Helping SC&L leaders spot “AI-ready” areas in warehouses, transport, forecasting and ESG where data already flows, and manual work may well be blocking progress.
• Designing human-in-the-loop patterns where planners, operators and managers stay firmly in charge, with AI acting as a copilot rather than a black box.
• Being transparent about where we do and don’t use AI in our work, and why.

We’re also working with academic partners on the “next horizon,” e.g., agentic AI in domains such as forecasting, logistics control towers, and warehouse operations. This will mean we can separate what’s hype from what’s genuinely ready for early adopters in the UK and Europe.

If you’re a supply chain or logistics leader who’s still in the “thinking and experimenting” phase, that’s precisely where we are too, just with a structured programme, some learnings from our own pilots and a clear view of where AI can (and can’t yet) move the dial.

If you’d like to see how we’re approaching this, from internal pilots to “AI-ready” operating models and low-risk diagnostics, we’re always happy to share what’s working, what isn’t, and what we’re learning along the way email ai@hatmill.com.