admin The moves mark a shift from selling access to chatbots and application programming interfaces towards embedding engineers, consultants and workflow specialists inside companies that want AI to reshape operations rather than sit on the edge of office software. Both companies are trying to solve the same problem facing large organisations: many executives see clear promise in generative AI, but struggle to convert pilots into secure, measurable and scalable systems.
OpenAI has launched the OpenAI Deployment Company, a majority-owned unit backed by more than $4 billion in initial investment. The venture is structured as a multi-year partnership with 19 global investment firms, consultancies and systems integrators, led by TPG, with Advent, Bain Capital and Brookfield among the co-lead founding partners. Bain & Company, Capgemini and McKinsey & Company are also part of the wider partnership network.
A central part of the plan is OpenAI’s agreement to acquire Tomoro, an applied AI consulting and engineering firm founded in 2023 in alliance with OpenAI. Tomoro is expected to bring about 150 forward deployed engineers and deployment specialists into the new unit once the transaction clears customary closing conditions. Its client base has included Tesco, Virgin Atlantic, Mattel, Red Bull and Supercell, giving OpenAI a ready team with experience in enterprise environments where reliability, governance and business continuity are critical.
Anthropic has moved along a similar path through a joint venture focused on enterprise AI services, with Blackstone, Hellman & Friedman and Goldman Sachs as founding partners. The venture has been reported at a valuation of about $1.5 billion, with substantial commitments from Anthropic and key private equity partners. Other backers linked to the initiative include Apollo Global Management, General Atlantic, GIC, Leonard Green and Sequoia Capital.
The launches show that frontier AI companies are no longer content to leave implementation entirely to traditional technology consultancies. Their argument is that deeper access to model roadmaps, safety systems and product teams can help customers build AI tools that improve as the underlying models advance. For businesses, the attraction is faster movement from experiments to working systems across finance, legal, customer service, software engineering, supply chains and internal knowledge management.
Enterprise adoption data has added urgency to the race. Among businesses tracked through corporate spending patterns, Anthropic moved ahead of OpenAI in April, with adoption at 34.4 per cent compared with OpenAI’s 32.3 per cent. The figures do not capture every corporate contract, but they underline a broader shift in which Claude has gained traction among teams using AI for coding, research, document analysis and professional workflows.
OpenAI still has the stronger consumer brand through ChatGPT and a large base of business users across its products and APIs. It says more than one million businesses have adopted its tools, and its deployment company is designed to help organisations redesign infrastructure and workflows around AI systems that can reason, act and deliver measurable results. The company’s approach is to place specialised engineers alongside business leaders, operators and frontline teams to select high-value use cases, connect models to internal data and controls, and build systems that can run in daily operations.
Anthropic’s enterprise pitch has centred on reliability, safety and usefulness in information-heavy work. Its Claude tools have expanded into legal and business functions, including plug-ins and workflow features intended to support lawyers, finance teams, researchers and software developers. The company has also broadened its reach to smaller businesses through Claude for Small Business, which connects with tools such as QuickBooks, PayPal, HubSpot, Canva, DocuSign, Google Workspace and Microsoft 365.
The new deployment arms are likely to unsettle established IT services firms, which have positioned themselves as the natural bridge between AI platforms and corporate customers. System integrators and consulting companies still bring scale, sector knowledge and long relationships with chief information officers, but model developers now want a larger share of the implementation layer where revenue, customer lock-in and operational data are concentrated.
