Microsoft, AWS Expand Engineer Teams to Accelerate AI Returns
AWS and Microsoft aim to place thousands of their engineers within client companies to assist them in leveraging artificial intelligence, which has not yet generated profits in the corporate sector.
Microsoft revealed on Thursday the establishment of a division named Microsoft Frontier Company, supported by a $2.5 billion investment that unites 6,000 specialists and engineers.
The new Microsoft organization appears as competitor AWS, the top cloud provider globally, declared on Tuesday a comparable US$1 billion investment in a group named Forward Deployed Engineering, which is also responsible for sending thousands of engineers to assist clients.
The two cloud behemoths are addressing the identical issue: businesses are acquiring additional AI tools, yet those expenditures are not currently yielding clear benefits.
By the end of 2025, nearly 90percent of companies had implemented AI in at least one business area; however, 94percent indicated they did not see any substantial advantage from those investments, as reported by the consultancy McKinsey.
The research, released in late April, contended that simply providing AI tools to employees isn't sufficient – businesses must reconsider their entire work processes.
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Microsoft and AWS, which provide servers and software to numerous businesses globally, are wagering that their engineers can achieve results more quickly and effectively than the clients' internal teams.
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“The currency that clients frequently discuss at the moment is speed,” stated Francessca Vasquez, vice president of Frontier AI Engineering and Services at AWS.
Sri Elaprolu, Director of AWS’s GenAI Innovation Center, stated that the crucial aspect is to avoid the urge to prioritize the technology first.
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“Merely because an individual is enthusiastic about agentic AI, it doesn’t imply that agentic AI is the correct solution,” he stated to AFP during the AWS Summit conference in Washington. An incorrect approach involves imposing a technology on a problem instead of reverse-engineering to identify the proper steps needed to achieve the goal.”