The Confederation of British Industry has urged the Government to make the rollout of artificial intelligence a national economic priority, arguing that Britain must move beyond pilots and scale the technology across firms and public services to secure higher wages, better jobs and stronger growth.
Execution gap risks leaving firms behind
The CBI, in partnership with consulting group Oliver Wyman, warns of an emerging “execution divide” between companies that are successfully embedding AI and those still in pilot mode. Their analysis highlights a stark gulf in early returns: 49% of firms leading on AI say they are meeting or exceeding expected returns, compared with just 15% of companies that have not scaled the technology.
“The next chapter of AI won’t just be defined by what we invent, but by how quickly we can put it to work at scale,”
The CBI wants government and business to adopt a shared mission for the next decade — an “adoption decade” — focused on practical delivery rather than experimentation. The organisation argues that the prize from doing so will not be technological alone but will show up in living standards and regional prosperity.
Practical steps to accelerate adoption
To close the execution gap the CBI is calling for a set of concrete interventions that would combine public policy with private-sector delivery. Recommendations include establishing a business-led delivery group to co-ordinate rollout, issuing a voluntary responsible-adoption code and pledge, and investing heavily in AI skills and literacy across the workforce.
- Set a ten-year national adoption agenda — the so-called “adoption decade”.
- Create a business AI adoption delivery group to co-ordinate action.
- Develop a voluntary responsible AI adoption code and public pledge.
- Invest in skills and a national standard for AI literacy.
- Design regulation that is easy to navigate to give firms confidence to invest.
The case for a co-ordinated approach is pragmatic: firms that scale AI successfully report much stronger returns, suggesting that Britain’s economic performance and the pay packets of workers could be influenced by how quickly companies move from testing to wide deployment.
What it means for wages, jobs and firms
The CBI frames AI not merely as a cost-saving technology but as a potential driver of higher productivity and higher-paying roles if adoption is paired with training and labour-market protections. Rapid, well-managed rollout could raise demand for different skills and create new roles in data, engineering and oversight, while firms that fail to adopt may suffer competitiveness shortfalls that translate into slower wage growth and weaker hiring.
However, the CBI’s prescription depends on action by both business and state. A voluntary code and industry pledge will only shift behaviour if companies believe implementation risks are manageable and that regulation is proportionate. Equally, workers will need confidence that retraining and transitions are supported, or political resistance will constrain adoption.
| Measure | CBI proposal |
|---|---|
| National focus | Declare an “adoption decade” to concentrate resources |
| Governance | Business-led delivery group to co-ordinate rollout |
| Standards | Voluntary responsible AI adoption code and public pledge |
| Skills | Investment in AI skills and a national literacy standard |
Policymakers face competing pressures. Legislators must balance the drive to unlock productivity with concerns over fairness, job displacement and ethical risks. The CBI’s approach is deliberately collaborative: it seeks to enlist firms in responsible deployment while asking Whitehall to create conditions that reduce frictions to investment.
For businesses, the message is straightforward: scaling AI correlates with stronger returns, and delay risks being left behind. For workers and unions the emphasis must be on skills and secure transitions to ensure adoption leads to better jobs rather than labour-market insecurity. For the Treasury and wider government the challenge is to translate a decade-long ambition into measurable milestones that tie investment and skills spending to clear outcomes for incomes and jobs.
How ministers respond will shape whether the UK seizes the economic opportunities from AI or watches rivals convert experimentation into sustained gains in productivity and pay.
