The UK has established a distinctive position in the global AI landscape, driven by rapid firm formation and strategic investment. However, the interplay between AI specialisation, local socioeconomic conditions, and firm performance remains underexplored. This study analyses a comprehensive dataset of UK AI entities (2000 - 2024) from Companies House, ONS, and glass.ai. We find a strong geographical concentration in London (41.3 percent of entities) and technology-centric sectors, with general financial services reporting the highest mean operating revenue (33.9 million GBP, n=33). Firm size and AI specialisation intensity are primary revenue drivers, while local factors, Level 3 qualification rates, population density, and employment levels, provide significant marginal contributions, highlighting the dependence of AI growth on regional socioeconomic ecosystems. The forecasting models project sectoral expansion to 2030, estimating 4,651 [4,323 - 4,979, 95 percent CI] total entities and a rising dissolution ratio (2.21 percent [-0.17 - 4.60]), indicating a transition toward slower sector expansion and consolidation. These results provide robust evidence for place-sensitive policy interventions: cultivating regional AI capabilities beyond London to mitigate systemic risks; distinguishing between support for scaling (addressing capital gaps) and deepening technical specialisation; and strategically shaping ecosystem consolidation. Targeted actions are essential to foster both aggregate AI growth and balanced regional development, transforming consolidation into sustained competitive advantage.

翻译：英国凭借快速的企业创立与战略性投资，已在全球人工智能格局中确立了独特地位。然而，人工智能专业化、地方社会经济条件与企业绩效之间的相互作用仍未得到充分探究。本研究分析了来自 Companies House、英国国家统计局和 glass.ai 的英国人工智能实体综合数据集（2000-2024年）。我们发现存在强烈的地理集中性，伦敦（占实体的41.3%）和技术密集型部门尤为突出，其中一般性金融服务报告了最高的平均营业收入（3390万英镑，n=33）。企业规模和人工智能专业化强度是主要的收入驱动因素，而地方因素——三级资格认证率、人口密度和就业水平——则提供了显著的边际贡献，凸显了人工智能增长对区域社会经济生态系统的依赖性。预测模型预计到2030年部门将扩张，估计实体总数将达到4,651家[4,323 - 4,979，95%置信区间]，同时解散率呈上升趋势（2.21% [-0.17 - 4.60]），表明该部门正转向较慢的扩张与整合阶段。这些结果为实施因地制宜的政策干预提供了有力证据：在伦敦以外地区培育区域人工智能能力以降低系统性风险；区分对规模化（解决资本缺口）的支持与深化技术专业化；以及战略性地引导生态系统整合。采取有针对性的行动对于促进人工智能的总体增长与区域平衡发展、将整合转化为持续的竞争优势至关重要。