Google and Accenture Launch Joint Team to Put AI Engineers Inside Big Companies
Google holds just 6% of enterprise AI spending against rivals at nearly 40% each. A new unit training 1,000 dedicated engineers is its latest push to close the gap.
Key points
- Google Cloud and Accenture have formed the Accenture Gemini Enterprise Business Group, a joint unit that will embed engineers directly inside large companies to set up Google's AI tools.
- Google plans to train up to 1,000 Accenture engineers specifically to build custom AI applications on its Gemini platform.
- As of August 2025, Google accounts for roughly 6% of U.S. enterprise AI spending, compared to Anthropic at 43.5% and OpenAI at 39.7%, according to data from financial software firm Ramp.
- The move follows a $750 million partner-ecosystem commitment Google Cloud announced earlier this year, which placed Google's own engineers at Capgemini, Cognizant and Deloitte.
Google Cloud and Accenture, one of the world's largest technology consulting firms, have joined forces to create a dedicated unit whose sole job is putting engineers inside big companies and getting Google's AI up and running. First reported by TechCrunch AI, the unit is called the Accenture Gemini Enterprise Business Group.
The idea is straightforward. Google will train up to 1,000 Accenture engineers to work directly with corporate clients, building custom AI applications on Google's Gemini platform, Google's suite of large language model products (the technology behind AI chatbots and assistants).
Why does any of this matter to ordinary people?
For anyone whose employer uses outside technology consultants, this is where the rubber meets the road. Google, OpenAI, Anthropic and Microsoft have all spent enormous sums building AI systems. The hard part has turned out to be getting those systems to actually work inside real businesses.
That gap between "we bought some AI" and "the AI is saving us money" is what these so-called forward-deployed engineers, or FDEs, are meant to close. An FDE is simply an engineer who works on-site at a client company rather than at the technology firm's own offices, acting as a long-term guide rather than a one-time salesperson.
How far behind is Google?
Quite far, at the moment. The Ramp data tells a blunt story.
| Company | Share of U.S. enterprise AI spending (Aug 2025) |
|---|---|
| Anthropic | 43.5% |
| OpenAI | 39.7% |
| ~6% |
Meanwhile, Google Cloud's parent company, Alphabet, had accumulated $811 billion in purchase commitments and contractual obligations as of 30 June, an enormous financial bet that AI demand will grow fast enough to justify the spending on chips, data centres and power.
The new Accenture unit is Google's most direct attempt yet to generate that demand. Earlier this year Google Cloud pledged $750 million toward embedding its own engineers across multiple consulting firms, and struck a separate deal to place engineers inside the portfolio companies of investment firm CVC Capital Partners.
What happens next?
The FDE model is quickly becoming a competitive arena on its own. Accenture is not sitting still either: the firm launched a similar engineer-placement practice with Microsoft in March, one with workflow software company ServiceNow in May, and a joint programme with business software giant SAP in June.
Smaller, specialist firms are also moving in. Companies whose entire business model is embedding engineers inside organisations to build bespoke AI workflows, such as Ode (which works with Anthropic) and OpenAI's own The Deployment Co., are putting pressure on both the big tech companies and the large consultancies at the same time.
For employees at large organisations, the practical upshot is that AI tools are likely to arrive with more hands-on setup help than before. Whether that translates into genuine productivity gains, or just a faster rollout of tools that still do not quite fit, will depend on how well those engineers understand the actual work.
