- Google Cloud and Accenture are building a 1,000-person AI team to deploy Gemini Enterprise.
- Microsoft, OpenAI, and Anthropic are expanding embedded AI engineering teams.
Google Cloud and Accenture have launched a new business group focused on deploying Gemini Enterprise inside customer organisations. The companies plan to establish a workforce of 1,000 forward-deployed engineers as part of the initiative.
The Accenture Gemini Enterprise Business Group will operate within the existing Accenture Google Business Group. It will bring together Accenture professionals certified on Gemini Enterprise, forward-deployed engineers, Google Cloud engineering staff, and industry specialists.
Enterprise AI scaling remains limited
Gartner reported on September 1st that only 22% of organisations surveyed had successfully scaled AI across multiple business units or adopted an AI-first approach. The survey covered 1,303 respondents from organisations with annual revenue of at least $50 million. Among functional leaders, 85% said they planned to increase AI spending in 2026 after allocating an average of 12% of their functional budgets to AI in 2025.
McKinsey’s 2025 global AI survey found that 88% of respondents said their organisations regularly used AI in at least one business function, but only about one-third had begun scaling their AI programmes. Separate McKinsey research published in March 2025 found that workflow redesign had the strongest relationship with EBIT impact from generative AI among the 25 organisational practices examined.
Forward-deployed engineers, or FDEs, work directly with customer teams on technology deployments. In AI projects, their work can include connecting models to company data and existing systems, adapting workflows, testing applications, and moving systems into production. Production deployments can also require access to proprietary data, governance controls, evaluations, and industry-specific requirements.
Accenture surveyed executives at 2,000 companies across 15 countries and nine industries and found that 64% said their businesses had moved beyond pilots into production across multiple functions or had started coordinated enterprise-wide AI efforts. Accenture’s assessment, however, found that only 7% had reached the level of data readiness it considers necessary to scale advanced AI.
The research identified siloed and low-quality data, limited business context, and missing tacit knowledge among the barriers. It also found that 72% of organisations lacked both trusted data of the required quality and standardised governance practices for advanced AI, while more than 80% said data-related risks at least occasionally caused them to delay, limit, or alter AI initiatives.
Reuters reported in February that companies attempting to deploy AI more broadly were encountering operational problems that models alone did not address. The report described efforts by OpenAI and consulting firms to connect AI agents with corporate data and applications and embed them into functions such as customer support, sales, and software development.
Google Cloud and Accenture said one of the new group’s priorities is moving customers from AI experimentation to enterprise-scale implementations. The companies said dedicated capability centres will support that work, while Accenture’s existing pool of nearly 50,000 Google Cloud-skilled professionals will provide a base for further Gemini Enterprise training and certification.
The group will work across the Gemini Enterprise portfolio. Google Cloud and Accenture said its work will include deployment frameworks, industry-specific applications, and dedicated capability centres, with teams supporting projects ranging from individual business units to organisation-wide implementations.
The companies pointed to an existing deployment at YouTube as one example. They said a Gemini Enterprise agent used during periods of higher demand for NFL Sunday Ticket increased customer sentiment by 11% and reduced average handling time by 37%.
AI vendors build embedded engineering teams
Google Cloud and Accenture are not the only companies expanding the use of engineers embedded with enterprise customers. Microsoft said in July that it had created Microsoft Frontier Co., an organisation comprising 6,000 industry and engineering specialists who will work directly with customers on AI systems.
Microsoft said it had tested the model during the previous year through more than 330 projects involving 164 customers. The teams work with customers to co-design and improve AI systems using company workflows, domain knowledge, and data. One project involved Novo Nordisk, where Microsoft’s forward-deployed engineers worked on an agent designed to analyse clinical data while meeting the pharmaceutical company’s compliance requirements.
Microsoft has also extended the model through consulting partnerships. In May, Microsoft and EY announced plans to invest more than $1 billion over five years in an initiative combining Microsoft forward-deployed engineers with EY industry professionals. The teams are intended to work on customer projects across functions including finance, tax, risk, human resources, and supply chains.
OpenAI has taken a different approach by establishing a separate business focused on enterprise deployment. The OpenAI Deployment Company, announced in May, is designed to place forward-deployed engineers inside organisations working on AI systems. OpenAI said those engineers will work with business leaders, operators, and frontline employees to identify use cases, redesign infrastructure and workflows, and build systems intended for regular operational use.
OpenAI also agreed to acquire applied AI consultancy Tomoro as part of the launch. The move follows its earlier work with consulting firms including Accenture, BCG, Capgemini, and McKinsey.
Reuters reported in February that OpenAI engineers would work directly with consultants to implement AI systems and train employees as companies sought to move beyond isolated pilots. The report also noted that OpenAI’s Frontier platform includes a context layer designed to connect corporate data and applications.
Reuters identified fragmented access to company information and existing systems as one of the obstacles enterprises faced when integrating AI agents into core business processes. The deployment work therefore includes connecting AI systems with data and applications already operating inside customer organisations.
Anthropic is also expanding deployment through its partner network. When it launched a services track for the Claude Partner Network in June, Anthropic said successful AI pilots did not necessarily result in systems suitable for ongoing business use. The company identified integration, evaluation, and changes to employees’ work as parts of the remaining deployment process.
Anthropic’s Claude Partner Network is backed by a $100 million investment in partner training, technical support, and related programmes. The company has also partnered with DXC Technology, which plans to train tens of thousands of Claude-certified forward-deployed engineers.
Those engineers will work inside customer organisations across sectors including banking, aviation, insurance, manufacturing, and government.
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