UK AI investment is rising fast - but fragmented adoption and shadow AI are cutting returns
22 October 2025 - London, UK. New research from SAP, produced with Oxford Economics, shows UK companies will spend an average of £15.94 million on AI this year, with investment expected to climb a further 40% over the next two years. The average firm reports a 17% return today (about £2.7 million) and expects ROI to reach 32% (£7.5 million) by 2027. Most executives (78%) expect a positive return within one to three years, and 52% say AI delivers value faster than any other technology.
Some of that return is forecast to come from agentic AI. UK businesses expect an 11% ROI from intelligent agents within two years, equivalent to £2.7 million, as agents begin to connect finance, supply chain, and workforce planning end to end.
The strategic gap: fragmented adoption
- 42% say investment is piecemeal
- 37% say it's department-led
- 15% say it's ad hoc
- Only 7% have a strategic, enterprise-wide plan
It's no surprise 70% of UK businesses are unsure whether AI is delivering its full potential. As one UK leader puts it, too many are still treating AI as a "technology project" instead of a business transformation. The opportunity is to rethink how the company operates, how people work, and how value is created for customers.
Shadow AI is a signal - but also a risk
Employees are moving fast. 68% of organisations say staff use unapproved AI tools at least occasionally. The costs are real: 44% have seen data or IP exposure and 43% report security vulnerabilities tied to shadow AI.
Training isn't keeping pace. 60% of companies say staff haven't completed comprehensive AI training, though 71% are starting to reskill or upskill. Leaders call for sanctioned tools, clear guidance, and safe spaces for experimentation. Psychological safety matters - employees need to ask questions, report issues, and learn without fear - while companies keep the right controls and ethical standards in place.
Value is showing up - if data, skills, and strategy click
- 36% report significant improvement in decision-making
- 34% see gains in customer engagement
- 31% report faster time to value
These outcomes matter in a service-led economy where knowledge and relationships drive growth. But without a clear strategy, strong data foundations, and the right skills, enthusiasm won't translate into sustained productivity or competitiveness. As one executive noted, too many teams are "filling a shopping basket with tools" rather than linking data, applications, and intelligence into one system and building end-to-end use cases.
Executive takeaways: turn momentum into measurable impact
- Set enterprise outcomes first. Pick 3-5 measurable targets (revenue, cost, cycle time, risk), assign owners, and fund against them - not isolated pilots.
- Prioritise cross-functional agents. Start with high-leverage flows (order-to-cash, forecast-to-fulfil, hire-to-assign) that span finance, supply chain, and workforce planning.
- Fix the data basics. Establish a common data model, quality checks, lineage, and access controls. Keep sensitive data out of prompts and enforce retention rules.
- Replace shadow AI with approved choices. Publish an acceptable use policy, provide vetted tools, log usage, and red-team critical use cases.
- Train by role, not by hype. Baseline everyone, then offer role-specific paths for sales, finance, operations, and IT. Consider structured programs to speed adoption. For curated options by role, see Complete AI Training.
- Build a practical governance stack. Model registry, human-in-the-loop for material decisions, audit trails, and incident response. Helpful guardrails: NCSC guidance on secure AI development and the ICO's AI and data protection guidance.
- Measure ROI and risk continuously. Track adoption, unit cost, cycle time, error rates, revenue lift, and model drift. Set clear "kill or scale" thresholds.
- Tighten vendor terms. Require data handling controls, IP indemnity, uptime SLAs, security attestations, and breach notification commitments.
Read the full report
The Value of AI in the UK: Growth, people & data
Methodology
Oxford Economics fielded an online survey (July-August 2025) of 1,600 senior executives across eight global markets, including 200 from the UK. The sample covered midmarket firms (500-1,500 employees) and enterprises (1,500+), with respondents at director level or above.
[1] Respondents estimated in USD. GBP figures use a 0.7381 exchange rate (Bank of England, 1 September 2025).
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