
Microsoft announced the "Microsoft Frontier Company" (MFC) on
Tuesday as a new operating business focused on delivering artificial intelligence (AI) support for its clients through enterprise AI engineering expertise.
The move follows a trend
of major companies such as Amazon Web Services, OpenAI and others that design and train AI systems including large language models (LLMs).
Rodrigo Kede Lima will lead MFC
as president, bringing about 30 years of experience. For the past six at Microsoft, Kede Lima has led enterprise-wide change in sales for the Americas and Asia.
His experience in helping
customers and partners traverse technology shifts enables him to understand how platform innovation, engineering and partner ecosystem collaboration combine to drive growth, Judson Althoff, CEO of
Microsoft Commercial Business, wrote in a blog post.
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MFC will have more than 6,000 industry and engineering experts to "embed" in customer locations who will "co-design, co-innovate, deploy
and continuously improve AI systems" based on measurable business goals and outcomes for clients.
"Companies need to establish an intelligence platform so their unique IQ — their
proprietary data, expertise, workflows and decision-making processes — compounds over time from within," Althoff wrote. "They need a trusted platform that allows them to observe, govern, manage
and secure AI solutions across every layer of the technology stack, using FinOps to assess their ROI."
MFC will focus on transforming businesses for clients using AI. The division's employees
will work closely with Accenture, Capgemini, EY, KPMG, PwC, and others in which Microsoft has formed partners.
As part of the project, Althoff explained how MFC will protect a customer's IQ,
an enterprise intelligence layer designed to provide AI agents and Microsoft 365 Copilot with context such as people's work, business data, and knowledge.
It acts as a layer of content that
pulls in and unifies real-time data signals across the company.
None of the client's data and the company's intellectual property will be used to train models in ways that commoditize what
differentiates them in their industry.
Consulting firm Deloitte calls this "multidimensional" outsourcing.
Findings released in May from a Deloitte survey of more than 500 global business and technology executives found that 70% of organizations reported bringing previously outsourced work in-house
during the last five years to strengthen internal capabilities, improve service quality, and minimize vendor mark-ups.
With 92% of organizations Deloitte surveyed reporting that they are integrating or planning to integrate AI into service
delivery, many are now adopting a “digital workforce” strategy, drawing on both human and AI capabilities while embracing practices including robotic process automation and machine
learning.
Integrating advanced AI throughout an enterprise is not easy, especially when relying on existing in-house capabilities.
The role of next-generation managed service providers
can work alongside in-house teams to support and provide information about technologies like agentic AI, according to Deloitte.
Today's announcement from Microsoft more than doubles the
investment by Amazon Web Services announced earlier this week when
AWS launched a $1 billion initiative to embed Forward Deployed Engineering (FDE) teams in client companies to accelerate artificial intelligence (AI) adoption.
Unlike Microsoft, AWS named
major partners like the National Football League (NFL), and Southwest Airlines.
AWS is working with the NFL to support its millions of fans who want to consume football content throughout the
year, including during the offseason.
In May, the OpenAI Deployment Company
launched with the goal to help organizations solve business processes throughout their enterprise when deploying and using AI.
OpenAI's new business was made possible by its
acquisition of Tomoro, an applied AI consulting and engineering firm that helps enterprises turn AI into operational advantage, also announced today. The acquisition will bring 150 experienced
engineers and specialists to OpenAI.
All of the
outsourcing services will embed engineers specializing in AI deployment into client businesses, similar to the way original equipment manufacturers (OEM) embed their employees in companies like Apple,
which outsources its hardware manufacturing of the iPhone, tablets and laptops.