Artificial intelligence tools are accelerating a shift toward corporate self-reliance by enabling non-experts to perform highly specialized tasks in-house, significantly reducing the need for companies to outsource work to external professional services. According to a paper by Luis Garicano of the London School of Economics presented at the fall 2026 Brookings Papers on Economic Activity conference, specialized firms historically spread the high fixed costs of acquiring knowledge across multiple clients.
AI lowers these fixed costs. This shift directly threatens the business models of specialized firms employing 5.9 million people across six key occupations, including lawyers, accountants, software developers, and management analysts. Preliminary data from 2022 to 2025 shows a rapid decline in the share of these professionals employed by specialized external agencies. While niche firms will still handle highly complex, rare problems, the reduction in routine outsourced tasks risks creating a "broken ladder" for entry-level professionals. Consequently, educational institutions and regulatory frameworks must adapt to these shifting labor dynamics.
The integration of generative artificial intelligence within the Tempest future combat air system programme threatens to disrupt the traditional subcontracting ecosystem for specialised software verification. Historically, BAE Systems outsourced complex algorithmic auditing for flight-control software to boutique European software firms to distribute the high fixed costs of specialised technical expertise. By lowering these barriers, internal engineering divisions at Warton Aerodrome can now utilise tools like Microsoft Copilot to ingest and analyse proprietary codebase architectures in-house. This shift directly threatens the viability of niche defence software suppliers across the UK Ministry of Defence supply chain, potentially consolidating critical aerospace engineering capabilities within a single prime contractor.
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