In a revealing interview, Mustafa Suleyman, the CEO of AI at Microsoft, offered rare insights into Microsoft’s artificial intelligence strategy and why the company has intentionally chosen not to lead the race in building frontier AI models.

Instead of building the most advanced large language models the moment they become technically feasible, Microsoft is playing a strategic second, trailing three to six months behind the cutting edge. This deliberate delay, Suleyman argued, provides numerous business and technological advantages, particularly in terms of cost-efficiency and product alignment.

Off-Frontier Advantage: A Strategic Wait-and-Watch

Suleyman introduced a concept he calls “off-frontier” AI development. The term refers to building models that are just behind the absolute frontier — in other words, models that are three to six months behind those from companies like OpenAI or Anthropic.

“There’s a very clear benefit,” he said. “It’s cheaper to give a specific answer once you’ve waited and learned from the leading models. That’s actually our strategy — to play a very tight second.”

This approach allows Microsoft to avoid the exorbitant costs and intense R&D duplication involved in building state-of-the-art models from scratch while still staying close enough to remain competitive. According to Suleyman, the capital-intensive nature of developing the best model in the world isn’t always necessary if the same results can be achieved more efficiently and effectively just a little later.

AI Collaboration and Infrastructure: The OpenAI Dynamic

Microsoft has a deep and complex relationship with OpenAI, the maker of ChatGPT. The partnership has been immensely productive, allowing Microsoft to infuse OpenAI’s models into products like Bing, Windows, and Copilot.

However, tensions have begun to surface. Microsoft added OpenAI to its list of competitors in July 2024, a significant move that hints at the evolving dynamics between the two companies. Despite these tensions, Suleyman reaffirmed Microsoft’s long-term vision:

“It’s mission-critical that we are able to do AI self-sufficiently at Microsoft,” he said, noting that the company still plans to be deeply partnered with OpenAI until at least 2030.

Even with OpenAI's new collaboration with Oracle on the $500 billion Stargate project, Microsoft confidently stated that OpenAI had recently made a large new commitment to Microsoft Azure, the cloud infrastructure supporting many of OpenAI’s systems.

Copilot Evolution and AI Memory Features

One of Microsoft’s major AI achievements is Copilot, its productivity assistant integrated across products. Suleyman revealed that Copilot will soon have memory, allowing it to remember user preferences, past interactions, and important personal details — a significant leap forward in AI utility and user experience.

This feature mirrors ChatGPT’s own memory, which was introduced earlier by OpenAI and has since proven immensely popular. Microsoft’s version, however, is being tailored specifically for its ecosystem, enhancing Office apps, Teams, Windows, and other platforms with contextual memory-based interactions.

Smaller, Open Models and Efficient Scaling

Another prong of Microsoft’s AI strategy is the release of smaller, open-source models that can run on personal computers. These models don’t require powerful GPUs or massive server infrastructure, making them ideal for edge computing and wider adoption across smaller businesses and emerging markets.

These models are fundamentally different from OpenAI’s larger offerings, like the o1 reasoning model, which requires significant computational resources. Microsoft’s approach here focuses on accessibility, cost-efficiency, and customizability.

A Long-Term Vision Towards AI Independence

Suleyman was candid about Microsoft’s long-term objectives: to eventually become AI self-reliant. While the company will continue leveraging its powerful partnerships, particularly with OpenAI, the goal is to build robust internal capabilities that can support in-house model development and deployment at scale.

He acknowledged the challenges and costs associated with such a transition but emphasised that Microsoft is well-positioned with its strong AI team, extensive compute resources, and decades of experience in building enterprise-grade software and services.

“It’s very important that maybe we don’t develop the absolute frontier, the best model in the world first,” Suleyman said. “That’s very expensive to do and unnecessary to cause that duplication.”

This mindset highlights Microsoft’s rational and measured approach to the AI revolution: not racing to be first at all costs, but rather prioritising sustainable growth, practical innovation, and alignment with real-world applications.

Why This Strategy Matters

Microsoft’s AI direction under Suleyman reflects a mature phase in the AI arms race. Instead of rushing to compete with every frontier innovation, the company is opting for a more selective, efficient, and use-case-driven model of innovation.

This strategy allows Microsoft to:

• Optimise costs and avoid redundant R&D.

• Refine features based on early learnings from frontier models.

• Focus on deployment, user experience, and platform integration.

• Scale responsibly, with infrastructure that supports both high-end and lightweight models.

It’s a deliberate deviation from the hype-driven frenzy seen across the industry — and one that could allow Microsoft to not only remain a powerful AI player but do so on its own terms.

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