When DSIT published its interim response to the AI Champions’ adoption plans this month, one line stood out above the rest: the real gains from AI won’t come from firms using it to draft emails and speed up research, they’ll come from using it to redesign how a business works entirely. That’s the right diagnosis. We’d know: it’s the entire premise NoCodeLab.ai was built on a year ago, and it’s already playing out in the businesses we’ve worked with.
We’re a Manchester-founded AI capability company, just past our first birthday. In eleven months we’ve trained almost 3,000 professionals across five countries, not through showing decks or reciting theory, but by turning non-technical people into builders who ship real, working products. The report names three barriers holding adoption back: unclear use cases, missing skills, and uncertainty about where to start. We’ve spent a year building the practical answer to all three, and we think the results are a useful data point for what government-backed adoption support could look like at scale.
On use cases: we don’t teach people to imagine them, we get them shipped
The report identifies a lack of identified use cases as the single biggest barrier to adoption, cited by 71% of firms. This is exactly why techUK and Katie Gallagher OBE - Managing Director of Manchester Digital, Chair of the UK Tech Cluster Group, and Digital and Technologies Sector Champion - are curating an AI use case library for the sector. We’re already involved in this effort: this autumn, we’ll be delivering sessions with Katie in Manchester to bring our own library of shipped, real-world use cases to the project.
Because our experience says the fix isn’t a workshop on “where AI could help,” it’s giving people the tools to build the thing and find out. A product manager with Figma wireframes and no dev team became a technical founder with a live wellness app and 30 active beta users, for under £500 in build cost against a £50k+ agency quote. A physicist-turned-consultant became the founder of a SaaS platform reporting 15x the ROI of his old coaching model. An infrastructure operator went from a decade of spreadsheets to a custom-built NFC asset-tracking system covering 3,000+ pieces of equipment, then built a second monitoring dashboard for 47 sites in a single weekend. None of these people could code a year ago. The use case stopped being theoretical the moment they had the capability to build it themselves.
On skills: capability transformation, not training delivery
The report is right that skills gaps run from the boardroom to the factory floor, and that businesses learn best from peers. Our flagship Builders Accelerator is built around that insight: quarterly cohorts, not one-off courses, with bespoke and co-branded versions now running with Salford University, Manchester Metropolitan University, Manchester Digital, and accelerator partners as far afield as Dubai, New York and Barcelona. We’re CPD accredited and on the UK Register of Learning Providers, and we sit on the board of the Centre for Digital Innovation, which is itself linked to the government's wider AI capability funding. None of this is theoretical positioning, it’s the operating model.
On pro-worker adoption: the model is augmentation, not replacement
The report is explicit that this should be a “pro-worker model of AI adoption,” and it backs that with a new Pro-Worker Adoption Prize chaired by Simon Johnson. Every story above is a pro-worker story by design: a product manager, a physicist, an infrastructure operator, none of them replaced, all of them given a new capability that sits on top of the domain expertise they already had. If the government is looking for case studies to put against that prize, or data to feed the new AI Economics Institute, we’d be glad to share what we’ve already measured: cost savings, ROI multiples, and outcomes across almost 3,000 people.
On sector relevance: we’re already inside the priority sectors the report names
The Champions’ plans single out financial services, creative industries, and digital and technology as the sectors with the most to gain. We’re already working across all three: a Vibe Coding masterclass with Barclays Eagle Labs and Google, a Female Founders programme with NatWest, an Educational and Technology Partnership with Manchester Fashion Week’s CTEM initiative ahead of a North West creative-sector push from September 2026, and an international training partnership with ENAIP Veneto in Italy that’s now turning marketing and strategy teams into people shipping software for European public and private sector clients.
We’re also building this from Manchester, where we were founded, with plans now in motion to bring what we’ve built here to Cambridge too, sessions, accelerators, and capability programmes, supported by a director already based there. We’re keen to explore how that growing footprint can connect with the Cambridge x Manchester Partnership, the first cross-UK innovation collaboration of its kind, backed by Research England and both cities’ combined authorities, and one that sits squarely alongside the report’s own emphasis on spreading AI capability beyond London and into the regions driving the Industrial Strategy sectors.
On entry-level jobs: the pipeline question the report flags as urgent
The Early Careers Jobs Alliance and the £200m TechFirst programme both point at the same problem: young people need real pathways into AI-enabled work, not just exposure to it. We’d welcome the chance to align that pipeline work more directly with the Alliance as it scales beyond its initial Digital and Technologies focus.
What we’d ask government to take from this
The report rightly says sector-specific, peer-led interventions outperform economy-wide ones, and that piloting before scaling avoids costly failure. We’d add one thing from a year on the ground: the fastest way to close the adoption gap isn’t more guidance documents, it’s putting people through the experience of building something real, with support, until it ships. That’s a measurable, repeatable model, and we’d welcome the chance to bring it into the AI Champions’ next phase of work.