This piece draws on "Imagining the Future Enterprise", an article by our co-founder Tarek Nseir for the Forbes Technology Council, December 2025.
AI is starting a new industrial revolution, one that amplifies human expertise rather than simply automating tasks. Our co-founder Tarek Nseir calls this the future enterprise, an organisation that is data-driven, modular and quick to decide, with people at the centre of how value is created. It captures what a company's best people know and builds it into how the work is done, an advantage competitors cannot easily copy. The shift is as much cultural and architectural as technological, and Tarek's argument in Forbes is that it is within reach now.
Why do so many enterprise AI projects miss their goals?
In our research, only about half of UK businesses using consultants for AI work achieved what they set out to, and only 45% set success metrics at all. The reason most often cited for missed targets was the consultant's focus on the technology rather than the outcome. When progress is measured by whether the system is live rather than whether the business is better off, projects can ship and still fail.
Money is not the constraint. The UK's largest enterprises put £66.1bn into this support, yet too much of it goes on building technology rather than changing how work is done and how value is created.
What separates the projects that deliver from the ones that don't?
Two things. The teams that succeed decide what outcome they are measuring before they build, so success is defined in business terms from day one. And they treat AI as a multiplier of human expertise rather than a replacement for it.
That second point has evidence behind it. A 2023 Harvard Business School field experiment with Boston Consulting Group, testing consultants using GPT-4, found they completed tasks around 25% faster and produced work more than 40% higher in quality, by amplifying skilled people rather than removing them. That advantage compounds, because it is built on your people and your context, which cannot be bought off the shelf.
What does amplifying expertise actually look like in practice?
It starts with data models that capture more than operational records. The future enterprise links operational data to the context, decisions and expertise around each interaction. In sales, that means connecting customer data with the judgement of the salesperson handling it, joining up CRM, ERP and knowledge management so human insight stays in the flow rather than lost around it.
Built well, this creates continuous learning loops. When a strong performer finds a better approach, it becomes part of the organisation's collective intelligence, available to both people and AI. Decisions that once took weeks can then happen in minutes, because the expertise sits where the work happens.
What has to change beyond the technology?
Culture, leadership and trust matter more than tooling. Leaders have to reconsider how the business works and how it makes money, and reward the people who pioneer new ways of working rather than those who keep the old ones going. Benchmarking AI-augmented performance against traditional output shows where amplification genuinely adds value.
Underneath it all sits trust. Organisations that raise AI use gradually while monitoring accuracy build it with employees, clients and the wider public, provided people stay in oversight of the system.
"Competitors may copy your tools, but not your institutional knowledge or compounded learning." — Tarek Nseir, Forbes Technology Council
This piece draws on Tarek Nseir's Forbes Technology Council article, "Imagining the Future Enterprise".
