UK businesses are making substantial investments in artificial intelligence, with an average spending of £15.94 million per company this year. This figure is expected to increase by 40% in the next two years, signaling a strong belief in the technology’s potential to drive growth and innovation. The commitment to AI is already yielding significant results, as companies are currently seeing a 17% return on their investment (ROI), a figure that is projected to nearly double to 32% by 2027.
This surge in AI investment is underpinned by a widespread optimism among UK executives, with 78% believing that AI will deliver a positive return within one to three years. In fact, more than half of business leaders (52%) report that AI provides returns faster than any other technology they have implemented. However, this rapid adoption is not without its challenges. The majority of AI programs in the UK are fragmented and lack a cohesive, enterprise-wide strategy. This piecemeal approach, coupled with the rise of “shadow AI” – the use of AI tools by employees without the company’s knowledge or approval – is creating security vulnerabilities and preventing businesses from realizing the full potential of their AI investments.
Investment Surge and ROI Projections
The UK’s AI ecosystem has experienced remarkable growth, with the number of AI companies increasing by 85% in the last two years to over 5,800. This expansion is reflected in the sector’s revenue, which has reached £23.9 billion, and its Gross Value Added (GVA) of £11.8 billion. The investment landscape is equally vibrant, with dedicated AI companies raising £2.9 billion in 2024, surpassing the previous record set in 2022. This influx of capital is not limited to tech startups; established businesses are also dedicating significant resources to AI, with the average company spending nearly £16 million this year alone.
The returns on these investments are already being realized. UK businesses report a current ROI of 17%, which translates to an average of £2.7 million per company. Projections indicate that this figure will grow to 32%, or £7.5 million, by 2027. These financial gains are driven by tangible improvements in business operations, including enhanced decision-making (36%), increased customer engagement (34%), and a faster time-to-value (31%). The confidence in AI’s ability to deliver is so strong that over half of UK executives consider it to be the most efficient technology for generating returns.
The Double-Edged Sword of Shadow AI
While the enthusiasm for AI is palpable, its implementation is often chaotic. The widespread use of “shadow AI,” where employees use unauthorized AI tools at work, highlights a significant disconnect between employee initiative and organizational strategy. A staggering 68% of employees are using these tools, driven by a desire to improve their productivity and efficiency. However, this unsanctioned use of AI comes with considerable risks. Almost half (44%) of businesses have already experienced data or intellectual property exposure as a result of shadow AI, and 43% report security vulnerabilities.
The rise of shadow AI is a clear indication that employees are eager to embrace the technology, but the lack of enterprise-wide adoption and training is creating a hazardous environment. Leila Romane, Managing Director of SAP UK & Ireland, notes that employees are “running ahead of their organisations, using AI tools because they see the opportunity, although they are not always aware of the risks involved.” To mitigate these risks and harness the energy of their workforce, businesses must provide sanctioned tools, create safe opportunities for experimentation, and invest in comprehensive AI training.
Strategic Implementation and Data Readiness
A Fragmented Approach
Despite the significant investments in AI, a cohesive, long-term strategy is alarmingly absent in most UK organizations. Only 7% of AI programs are part of an enterprise-wide strategic plan. The majority of implementations are described as piecemeal (42%), department-led (37%), or ad-hoc (15%). This fragmented approach is a major obstacle to realizing AI’s full potential, with 70% of UK businesses admitting they are unsure if the technology is delivering its maximum benefits.
Experts caution against treating AI as a mere “technology project.” Instead, it should be viewed as a holistic business transformation that reimagines how companies operate, how people work, and how value is created for customers. To achieve this, organizations must move beyond isolated use cases and develop a clear, strategic vision for AI that is aligned with their core business objectives.
The Importance of Data
A critical component of any successful AI strategy is a solid data foundation. However, the SAP study reveals that 73% of UK businesses are struggling with incomplete or insufficient data. Clean, well-governed data systems are essential for building reliable and effective AI models, particularly as companies look to implement more advanced agentic AI systems at scale. Umang Paw, CTO at PwC UK, emphasizes that data readiness is a significant barrier to large-scale AI adoption. “Many organisations have spent years collecting data but haven’t invested in making it AI-ready,” he states. The data is often siloed, inconsistent, or lacks proper governance frameworks.
The key to overcoming this challenge is to take a pragmatic approach. Instead of waiting for perfect data, organizations should start with their cleanest and most accessible datasets, prove the value of their AI initiatives, and then use those early wins to build momentum for broader data infrastructure investments.
The Rise of Agentic AI
As businesses mature in their AI journey, they are increasingly looking towards agentic AI to unlock new levels of value and efficiency. Agentic AI systems are designed to plan, execute, and collaborate across complex processes, moving beyond the fragmented, task-specific tools that are currently prevalent. These systems have the potential to automate multi-step manual processes at scale, improve planning and decision-making, and enhance coordination across different departments.
The anticipation for agentic AI is high, with 55% of UK business leaders stating that it will significantly influence their strategic planning in the next two years. The average UK business expects an ROI of 11% from intelligent agents within two years, which is equivalent to £2.7 million. However, realizing this value will depend on having integrated foundations of data, applications, and AI. As Brenda Brown, Chief Marketing Officer of AI at SAP, notes, “for enterprises, realizing that value will depend on integrated foundations of data, applications and AI.”
Workforce Transformation and the Skills Gap
The successful implementation of AI is not just a technological challenge; it is also a human one. A significant skills gap is hindering the progress of AI adoption in the UK. A recent IBM study revealed that while 66% of UK enterprises are experiencing productivity improvements from AI, nearly two-thirds have yet to tap into its full potential due to a lack of focus on workforce transformation and AI skills training. Shockingly, 60% of companies admit that their staff have not completed comprehensive AI training, leaving them ill-equipped to use the technology responsibly.
Addressing this skills gap is a critical priority. Businesses must invest in reskilling and upskilling their employees to ensure they have the knowledge and expertise to work alongside AI systems. This investment in people is not just about mitigating the risks of shadow AI; it is about empowering employees to become drivers of innovation and growth. As Leila Romane emphasizes, “AI investment must go hand in hand with people investment.”
Navigating the Challenges of Adoption
The path to successful AI adoption is fraught with challenges. In addition to the issues of fragmented strategies, poor data quality, and a persistent skills gap, businesses also face difficulties in quantifying the ROI of their AI initiatives. According to an IBM study, the high upfront investment costs (37%), the difficulty in attributing business outcomes solely to AI (35%), and the lack of skills or expertise (31%) are the biggest challenges organizations face when measuring the ROI of AI implementations.
To overcome these hurdles, businesses must ensure that their AI investments are tightly aligned with their core objectives, focusing on cost efficiency, revenue growth, and an enhanced customer experience. They must also establish strong governance frameworks to manage the risks associated with AI, such as unauthorized data sharing and algorithmic bias. By taking a strategic, holistic, and people-centric approach to AI, UK businesses can navigate the complexities of adoption and unlock the transformative potential of this powerful technology.