A BofA analyst says Microsoft's full-stack strategy and custom chips are driving superior AI economics

Microsoft's custom Maia 200 chip reduces AI-workload operational costs by up to 40% compared with traditional Nvidia hardware.

Investor concerns about software-sector weakness and artificial-intelligence overspending are retreating, providing a boost to shares of Microsoft.

But the rally is just beginning, according to Bank of America analyst Tal Liani, who believes the company's AI strategy is increasingly resembling a full-stack portfolio that's delivering impressive economics.

In a Tuesday note, Liani maintained his buy rating on Microsoft shares (MSFT) and raised his price target to $600, from $500 previously, implying roughly 20% upside from current levels.

Microsoft's winning strategy doesn't come from owning the best model, but rather routing user requests in the most efficient manner across Microsoft AI and third-party providers, according to the analyst.

By employing a mix of internal and external models, "Microsoft can reserve the largest and most expensive models for complex tasks while serving high-volume, product-specific workloads more efficiently," Liani wrote.

Shares of Microsoft have risen nearly 30% since the end of July. Last week, the stock posted its best six-day stretch since October 2025.

The momentum comes after an impressive fiscal fourth-quarter earnings report. Microsoft's cloud-computing division, Azure, saw revenue growth expand 43% year over year, and management's guidance of 45% growth for the current quarter surpassed Wall Street expectations.

Liani pointed out that paid Copilot seats exceeded 30 million, with net new additions more than doubling quarter over quarter.

Key to the company's AI strategy is its diversified collection of models that provides users with a tailored experience, he noted.

"Microsoft is building a broad portfolio of internal and external models, allowing customers to use the most cost-effective model for each task, while governing users actions," Liani said. "Not every workload requires a complex and expensive frontier model, and Microsoft's approach helps optimize performance while reducing token consumption."

He highlighted that Microsoft's specialized MAI-Code-1-Flash delivers comparable performance to GPT-5.6 for common Excel tasks at a cheaper price point.

Critically, a model-agnostic approach means that Copilot's value does not "depend exclusively" on Anthropic, OpenAI or any other model provider, Liani pointed out.

Beyond the model layer, Microsoft is also investing in hardware efficiencies. "Engineering improvements across Microsoft's CPU and GPU fleet, combined with software optimization, increased throughput for Copilot workloads by 4x since the beginning of the year," which has allowed Microsoft to monetize its capacity in a supply-constrained environment, Liani wrote.

Similar to other hyperscalers, Microsoft is investing in custom silicon to bring down inference costs. Its Maia 200 chip, which powers Microsoft AI models, are up to 40% cheaper to operate compared with traditional Nvidia (NVDA) hardware.

As Microsoft brings more capacity online, Liani predicts that Azure can grow 41.8% in fiscal 2027, up from 39.9% in fiscal 2026.

"Continued execution on the capacity buildout, faster deployment and greater efficiency increase our confidence in Microsoft's ability to sustain Azure growth," he said.

-Christine Ji