United Kingdom: AI revenue grew 68% in one year to £23.9 billion; employment jumped 33% to over 86,000 jobs; and foreign direct investment exceeded £15 billion in 2024 alone.

Dissecting the UK’s 2024 Artificial Intelligence Sector Study – Progress, Pitfalls, and Policy Paths Forward

by ChatGPT-4o

Introduction

The UK Government’s Artificial Intelligence Sector Study 2024 is a data-rich, expansive overview of the current AI landscape in the UK. With insights drawn from 298 surveyed AI companies, 52 in-depth interviews, and secondary data from sources like Companies House and Beauhurst, it provides a quantitative and qualitative assessment of the sector’s size, trajectory, challenges, and opportunities. The report paints a picture of dramatic growth—AI revenue grew 68% in one year to £23.9 billion; employment jumped 33% to over 86,000 jobs; and foreign direct investment exceeded £15 billion in 2024 alone.

But beneath these impressive numbers lie critical complexities, subtle controversies, and strategic blind spots—particularly for rights owners, creators, regulators, and AI makers operating within or adjacent to the UK. This essay unpacks the most surprising, controversial, and valuable statements in the report, offers critique, and closes with tailored recommendations for global stakeholders.

I. Most Surprising, Valuable, and Controversial Findings

1. Explosive Growth – But Concentrated

The sector has grown “150 times faster than the UK economy at large,” with AI now contributing £11.8 billion in GVA. However, 85% of this revenue is generated by large companies, most of which are diversified and not “dedicated” AI companies. This concentration raises critical questions about who truly benefits from AI’s expansion—startups and SMEs or established conglomerates that are repackaging existing offerings as AI?

2. AI Relabelling vs Genuine Innovation

The report admits that much of the revenue growth “inevitably includes an element of product and service relabelling (e.g., from software development and data analytics to artificial intelligence)”. This candid observation points to a significant risk of market distortion. It also raises doubts about how much real AI innovation is occurring, as opposed to opportunistic branding.

3. Import Dependence on AI Infrastructure

Despite its aspirations for digital sovereignty, the UK remains heavily dependent on foreign AI infrastructure, especially cloud computing and foundation models. Interviewees were skeptical about the feasibility of sovereign AI development due to capital constraints and recommended maintaining international partnerships instead.

4. Inward Investment ≠ Local Empowerment

Though £15 billion in FDI arrived in 2024, mainly from U.S. tech giants like Amazon, CoreWeave, and Google, there’s a risk that the UK is becoming a serving ground for global players rather than nurturing its own foundational AI capabilities. Many international firms simply set up sales or R&D offices, without deep integration into the UK’s academic or SME ecosystem.

5. Limited Scale-Up Capital and Talent Mobility

Stakeholders universally agree the UK is good at nurturing startups but poor at helping them scale beyond Series A. Capital bottlenecks, regulatory hurdles, and limited investor expertise in late-stage AI all stifle growth.

6. Exports of AI Services Surge, Hardware Exports Fall

AI-related services exports have doubled since 2018 to £33.2 billion, suggesting UK-based AI software and SaaS are increasingly in demand. Yet hardware exports have declined—illustrating a narrowing specialisation in soft (vs. hard) AI capabilities, which could leave the UK vulnerable to supply chain shocks and foreign control over compute infrastructure.

II. Points of Disagreement and Critique

1. Too Little on IP, Copyright, and Creator Rights

A glaring omission is any analysis of the intellectual property (IP) implications of AI growth. Nowhere does the report address the legal grey zones around AI training datasets, model outputs, or the licensing of third-party content. Given the global wave of lawsuits from creators, authors, and rights owners, this oversight is both surprising and troubling.

2. Absence of Environmental Costs

The environmental footprint of AI infrastructure—especially power-hungry data centers—is not mentioned. In a report that tracks import/export of CPUs and GPUs, it is baffling not to include sustainability, energy usage, or emissions concerns. This is especially relevant as the UK promotes itself as a global AI hub.

3. Overly Optimistic Outlook on “Growth”

The report presents business sentiment as highly bullish: 90% of respondents expect revenue growth. However, it fails to interrogate whether this confidence is speculative hype, inflated by the GPT boom and media frenzy, or grounded in sustainable business models.

4. Lack of Diversity Metrics

There is no discussion of gender, racial, or socio-economic representation within the AI sector. This weakens the report’s ability to inform inclusive innovation policies and ignores one of the UK’s stated AI priorities: equitable tech development.

5. Relabelling Undermines Longitudinal Comparisons

The acknowledgment that “AI” labels have proliferated in marketing and websites undermines the credibility of longitudinal sector growth comparisons. More stringent criteria were applied in 2024, but this still leaves open questions about how consistent and reliable the growth metrics truly are.

III. Recommendations for Key Stakeholders

🧠 For AI Makers (UK & Global)

• Avoid AI-washing: Resist rebranding existing services as "AI" without genuine innovation. This inflates expectations and regulatory scrutiny.

• Respect IP: Establish transparent licensing agreements for training data, particularly with publishers, authors, and creators. Failure to do so risks litigation and reputational harm.

• Invest in GVA, not just valuations: Focus on AI use cases that provide societal value and economic productivity, not just inflated market caps or hype cycles.

• Plan for compute and sovereignty risks: Reduce overreliance on U.S. cloud platforms and build resilience via multi-cloud or edge strategies.

🏛️ For Regulators in Other Countries

• Adopt sector-specific data collection strategies: The UK’s methodical distinction between “dedicated” and “diversified” AI firms could be replicated to better understand AI’s true economic footprint.

• Balance FDI with digital sovereignty: While attracting global players is beneficial, ensure domestic innovation ecosystems aren’t cannibalized by multinational dominance.

• Incorporate IP, fairness, and environmental KPIs: Future studies must capture how AI affects creators’ rights, environmental goals, and social equity.

🧾 For Rights Owners, Authors, and Creators

• Demand transparency in AI training: Push for legal and technical mechanisms (e.g., Model Provenance Disclosures, opt-out registries) to control how your works are used in training AI systems.

• Negotiate licensing deals early: As diversified AI firms scale, especially those in publishing, entertainment, or media, creators should assert their rights to compensation and attribution.

• Collaborate with sector studies: Engage with government and researchers to ensure that AI impact assessments reflect your interests—not just those of tech developers.

🧩 For UK Government and DSIT

• Include ethical, environmental, and IP dimensions in future studies.

• Track AI’s impact on workers, jobs, and equity —not just GDP.

• Bridge the gap between early-stage success and scale-up stagnation, potentially via targeted pension fund investments, sovereign investment vehicles, or a national AI scale-up fund.

• Promote trusted AI export brands: Support UK AI firms in becoming globally trusted by embedding ethical standards into their design, development, and governance.

Conclusion

The AI Sector Study 2024 is a commendable, methodically crafted analysis that shows the UK leading in AI innovation, startup vitality, and export growth. But the report’s blind spots—especially around IP rights, ethical safeguards, and environmental impact—must be urgently addressed.

AI’s future will not be written by GDP figures alone. The legitimacy of this growth depends on whether it respects creators, shares benefits equitably, and aligns with sustainable and inclusive governance. For that, all stakeholders—regulators, developers, investors, and creators—must act now, not later.