Microsoft plans to hire again with "more leverage" from AI tools

Microsoft will expand its workforce again after maintaining flat headcount throughout fiscal year 2025, but Chief Executive Officer Satya Nadella emphasized on November 1, 2025, that future hiring will come with "a lot more leverage" enabled by artificial intelligence tools deployed across the organization.

The software maker's employee base stood at 228,000 at the end of June 2025, unchanged from the previous fiscal year. Multiple rounds of layoffs reduced the total by at least 6,000 employees during that period. An additional 9,000 workers departed in July 2025 following the fiscal year close.

"I will say we will grow our headcount, but the way I look at it is, that headcount we grow will grow with a lot more leverage than the headcount we had pre-AI," Nadella stated during an appearance on the BG2 podcast with Brad Gerstner that aired November 1. The conversation included OpenAI CEO Sam Altman and covered the partnership between the two companies.

Unlearning and relearning workflows

Microsoft's approach centers on fundamentally redesigning work processes rather than simply adding AI capabilities to existing structures. Nadella described a transition period where employees must adapt to new ways of accomplishing tasks through AI-assisted workflows.

"It's the unlearning and learning process that I think will take the next year or so, then the headcount growth will come with max leverage," Nadella explained. The company aims to ensure all Microsoft employees can access AI features embedded in Microsoft 365 productivity software and the GitHub Copilot coding assistant.

These services draw on AI models from Anthropic and OpenAI. Nadella pointed to historical parallels in how organizations restructured workflows during previous technology transitions. Forecasting processes shifted from inter-office memos distributed by fax to collaborative spreadsheets shared via email when Microsoft Office emerged in the 1980s.

"Right now, any planning, any execution, starts with AI. You research with AI, you think with AI, you share with your colleagues," Nadella said. This represents a fundamental departure from traditional workflows where AI serves as an optional enhancement rather than the foundation of business processes.

The transformation affects how organizations structure roles and measure productivity. Employees gain agency to complete tasks previously requiring multiple team members or specialized expertise. Tasks that once consumed hours or days can compress into minutes when workers leverage AI capabilities effectively.

Cost structure and margin implications

Microsoft's headcount remained stagnant during a period when the company achieved significant revenue expansion. The 2022 fiscal year saw workforce growth of 22%, establishing a baseline that makes the subsequent freeze particularly notable. This divergence between revenue growth and headcount stability suggests AI tools are already generating measurable productivity gains.

The company reported 12% year-over-year revenue growth and demonstrated its widest operating margin since 2002 in results announced on October 30, 2025. Azure cloud infrastructure revenue jumped 40% despite constraints on available computing capacity, with Nadella acknowledging the company has been "short power and infrastructure for many quarters."

According to Amy Hood, Microsoft's Chief Financial Officer, demand keeps increasing faster than the company can expand capacity. Nadella expressed confidence that organizations mastering the pace of business process change to match AI capabilities will capture the largest efficiency gains.

Microsoft's strategy diverges from competitors pursuing more aggressive automation with less transparency about the displacement effects. Amazon announced 14,000 corporate employee cuts earlier in the week of October 28, 2025, with Senior Vice President Beth Galetti describing AI as "the most transformative technology we've seen since the Internet."

Network operations case study

Nadella cited a specific example demonstrating how AI tools enable small teams to accomplish work previously requiring much larger workforces. An executive leading Microsoft's network operations faced challenges managing fiber infrastructure for the company's expanding data center footprint.

The executive oversees coordination with approximately 400 different fiber operators worldwide. Each infrastructure incident requires navigating complex DevOps pipelines across multiple vendors and geographic regions. The scope includes a recently completed 2-gigawatt data center in Fairwater requiring extensive fiber connections.

"She basically said to me, there's no way I'll ever get the headcount to go do all this. Not forget even if I even approve the budget, I can't hire all these folks," Nadella recounted. The executive instead built AI agents to automate DevOps pipeline maintenance rather than requesting traditional headcount increases.

This example illustrates how AI deployment shifts from augmenting human workers to substituting for positions that would have been added in previous technology cycles. The executive maintained team size while dramatically expanding the infrastructure her organization manages and maintains.

Organizations must evaluate whether to deploy AI gains toward margin expansion or revenue acceleration through faster execution cycles. Microsoft appears positioned to capture both benefits as it scales AI capabilities across all business units while maintaining pricing power in core product lines.

Workforce composition and skill shifts

The transformation requires workers to develop new competencies around prompt engineering, AI supervision, and algorithmic workflow design. Traditional technical skills remain valuable but become table stakes rather than differentiators. Workers who cannot adapt to AI-mediated workflows face displacement as organizations restructure around these new capabilities.

Microsoft's emphasis on "unlearning" acknowledges that existing expertise can become impediments when fundamental assumptions about work processes change. Employees must abandon mental models built over decades of pre-AI work patterns. The company expects this transition to consume roughly one year before productivity gains from AI deployment reach their potential.

The timeline suggests Microsoft anticipates resuming headcount growth in late 2026 or early 2027, depending on how quickly employees master new workflows. This gradual approach contrasts with more aggressive automation strategies that prioritize immediate cost reduction over managed transitions.

Nadella positioned the current moment as analogous to the introduction of spreadsheet software, word processors, and email in the 1980s and 1990s. Those transitions required organizations to redesign business processes rather than simply automating existing paper-based workflows. The most successful organizations reimagined forecasting, document collaboration, and communication patterns rather than digitizing manual processes.

Impact on marketing and advertising operations

The workforce transformation carries particular significance for marketing professionals managing complex advertising campaigns and analytics infrastructure. Microsoft's decision to sunset its Xandr DSP by February 28, 2026, demonstrates how AI-driven consolidation affects specialized platforms.

AppNexus, which became part of Microsoft through the 2022 Xandr acquisition, provided unprecedented visibility into fee structures and money flows throughout advertising supply chains. The platform's commitment to transparency extended beyond fee structure to enable buyers to see exactly what fees were charged at each supply chain step.

Microsoft's shift toward "conversational, personalized, and agentic" advertising experiences reflects broader industry movement away from transparent, manually-controlled platforms toward AI-optimized black boxes. Organizations pursuing this direction prioritize outcome optimization over granular visibility into how systems achieve those outcomes.

This transition poses challenges for marketing teams built around detailed campaign analysis and supply chain cost verification. Professionals who developed expertise in programmatic supply chain transparency face uncertainty as platforms consolidate around proprietary AI systems that obscure rather than illuminate underlying mechanics.

The Xandr closure removes one of the few remaining platforms offering detailed breakdowns of where advertising dollars flow through programmatic supply chains. According to the Incorporated Society of British Advertisers, 49% of advertising spending never reaches publishers due to the complex intermediary chain in programmatic transactions.

Broader industry patterns

Microsoft's announcement aligns with workforce trends across major technology companies. The "Magnificent Seven" technology firms demonstrated minimal job growth over the past three years despite robust revenue expansion. Companies attribute these patterns partly to post-pandemic efficiency adjustments and partly to AI deployment.

Nadella acknowledged both factors but emphasized the structural nature of AI-enabled productivity gains. "The productivity curve does bend," he stated, describing fundamental changes to work and workflow rather than cyclical cost management. Organizations will accomplish more with fewer employees, forcing choices about whether to pursue margin expansion or revenue acceleration.

The Amazon layoffs announced on October 28, 2025, illustrate how different organizations navigate this transition. Galetti's memo to Amazon employees emphasized AI's transformative potential while announcing significant headcount reductions. The juxtaposition highlights tension between AI advocates' promises of enhanced capabilities and workers' experiences of displacement.

Industry observers note that aggregate employment effects remain uncertain. Historical technology transitions typically created more jobs than they eliminated, though often in different sectors and requiring different skills. Software development employment expanded dramatically as spreadsheets, databases, and other productivity tools became ubiquitous despite initial concerns about displacement.

The current transition may follow a similar pattern if AI deployment expands total addressable markets for software services faster than it compresses employment in existing functions. However, the speed and scope of change appear different this time, with AI affecting knowledge work broadly rather than specific manual tasks.

Productivity measurement and GDP implications

Nadella's description of "max leverage" suggests Microsoft anticipates dramatic improvements in revenue per employee metrics. The company already demonstrates industry-leading productivity given its market capitalization and employee base. Further improvements through AI deployment would establish new benchmarks for organizational efficiency.

This trajectory carries implications beyond individual company performance to broader economic productivity statistics. If large enterprises consistently generate more output from stable or shrinking workforces, aggregate productivity measurements should reflect these gains. However, distribution of those gains between labor compensation, corporate profits, and consumer surplus remains uncertain.

Gerstner, who manages technology investments at Altimeter Capital, described the emerging pattern as the "golden age of margin expansion." Companies can choose to retain efficiency gains as profit or redeploy them into faster growth initiatives. Microsoft appears positioned to pursue both paths given its dominance in cloud infrastructure and productivity software.

The company's fiscal 2025 results demonstrated this dynamic in action. Operating margins reached their highest level in over two decades while revenue growth sustained double-digit percentages. This combination typically proves difficult to maintain as organizations scale, yet AI deployment appears to relax traditional constraints on simultaneous margin expansion and revenue growth.

Implementation timeline and risks

Microsoft's one-year timeline for workforce adaptation appears optimistic given the scale of transformation required. Organizations must redesign not just individual workflows but entire business processes built over decades around human cognitive capabilities and communication patterns. This extends beyond training employees to use new tools into fundamental reconceptualization of how work flows through organizational structures.

The company's emphasis on "unlearning" acknowledges these challenges. Workers must abandon intuitions developed through years of experience with pre-AI processes. Managers must redesign performance metrics, incentive structures, and organizational hierarchies around AI-augmented capabilities rather than individual human expertise.

Implementation risks include uneven adoption rates across business units, resistance from employees facing displacement or diminished relevance, and potential quality degradation if AI systems fail to match human judgment in edge cases. Microsoft's gradual approach aims to mitigate these risks through managed transitions rather than forced disruption.

The company's decision to ensure all employees can access AI tools demonstrates commitment to bottom-up adoption rather than top-down mandates. This approach may slow initial deployment but could yield more sustainable transformation as workers discover organic use cases rather than following prescribed implementations.

Organizations observing Microsoft's experience will calibrate their own AI deployment strategies based on demonstrated outcomes. Success could accelerate industry-wide adoption of similar approaches. Failures or setbacks might prompt more cautious implementations focused on augmentation rather than wholesale process redesign.

Competitive dynamics and market positioning

Microsoft's AI-enabled workforce strategy strengthens its competitive position across multiple markets. The company leverages its partnership with OpenAI to access cutting-edge AI capabilities while maintaining control over integration into its product portfolio. This combination proves difficult for competitors lacking similar strategic partnerships or technical capabilities.

The $13 billion Microsoft invested in OpenAI through multiple rounds provides the company with approximately 27% ownership on a fully diluted basis, according to details discussed during the November 1 podcast. This stake could reach valuations exceeding $100 billion if OpenAI achieves expected growth trajectories.

Beyond equity value, the partnership provides Microsoft with exclusive access to stateless APIs on Azure through 2030 and revenue sharing arrangements that effectively subsidize Azure infrastructure investments. These structural advantages compound as both organizations scale their respective operations.

Nadella emphasized that Microsoft's cloud infrastructure benefits from operating the largest AI workloads globally. This operational experience generates learning curves and efficiency improvements difficult for competitors to replicate. Cost structures improve faster when managing the most demanding production workloads at scale.

The combination of technology access, operational learning, and infrastructure efficiency creates defendable competitive advantages. Organizations considering alternative cloud providers must evaluate not just current capabilities but trajectories as Microsoft compounds advantages through its OpenAI partnership and internal AI deployment.

Looking forward

Microsoft's workforce strategy offers a preview of broader labor market transformations as AI capabilities mature and diffuse across industries. Organizations that successfully navigate the transition from human-centric to AI-augmented workflows gain substantial competitive advantages through improved productivity and cost structures.

However, the approach raises questions about workforce displacement, skill requirements, and economic distribution of AI-generated productivity gains. Nadella's emphasis on "leverage" suggests Microsoft expects to capture significant value from AI deployment rather than passing all benefits to employees through higher compensation or consumers through lower prices.

The marketing and advertising industries face particular disruption as platforms consolidate around proprietary AI systems offering less transparency than legacy programmatic infrastructure. Professionals built their careers around supply chain visibility and manual optimization face uncertain prospects as systems optimize outcomes without revealing underlying mechanics.

Microsoft's experience over the coming year will provide valuable data points for other organizations calibrating their AI deployment strategies. Success could accelerate industry-wide adoption of similar workforce transformations. Challenges or setbacks might prompt more measured approaches balancing automation benefits against organizational disruption risks.

The company's flat fiscal 2025 headcount despite strong revenue growth suggests AI productivity gains already materialize in measurable forms. The next phase tests whether organizations can scale these gains while maintaining quality, innovation, and employee satisfaction in an AI-augmented environment.

Timeline

• 2019: Microsoft begins investing in OpenAI with initial $1 billion commitment
• 2022: Microsoft completes acquisition of Xandr from AT&T; fiscal year headcount grows 22%
• January 2025: OpenAI completes restructuring creating $130 billion nonprofit alongside public benefit corporation
• June 2025: Microsoft fiscal year ends with flat 228,000 headcount despite multiple layoff rounds removing at least 6,000 employees
• July 2025: Additional 9,000 Microsoft employees depart through workforce reductions
• October 28, 2025: Amazon announces 14,000 corporate employee cuts citing AI transformation
• October 30, 2025: Microsoft reports fiscal Q1 2025 results showing 12% revenue growth and widest operating margin since 2002
• November 1, 2025: Nadella announces workforce expansion plans with "a lot more leverage" from AI tools during BG2 podcast appearance
• February 28, 2026: Microsoft Invest (formerly Xandr) scheduled to discontinue operations
• Late 2026-Early 2027: Expected timeline for Microsoft to resume headcount growth following employee adaptation to AI workflows

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Summary

Who: Microsoft CEO Satya Nadella announced the workforce strategy during a November 1, 2025 appearance on the BG2 podcast hosted by Brad Gerstner, founder and CEO of Altimeter Capital. OpenAI CEO Sam Altman also participated in the discussion covering the Microsoft-OpenAI partnership.

What: Microsoft will resume workforce expansion after maintaining flat headcount at 228,000 employees throughout fiscal year 2025, but future hiring will come with "a lot more leverage" enabled by AI tools deployed across the organization. Employees must undergo an "unlearning and learning process" over approximately one year to master AI-augmented workflows before headcount growth resumes with maximum productivity leverage.

When: The announcement came on November 1, 2025, during a podcast that also covered the OpenAI partnership and broader AI infrastructure buildout. Microsoft's fiscal 2025 ended in June 2025 with the flat headcount. Nadella expects the workforce adaptation period to consume approximately one year, suggesting headcount growth could resume in late 2026 or early 2027.

Where: The changes affect Microsoft's global workforce of 228,000 employees across all business units. The podcast discussion took place following Microsoft's October 30, 2025 fiscal Q1 earnings announcement. The transformation impacts all Microsoft employees regardless of location, with the company ensuring access to AI tools in Microsoft 365 and GitHub Copilot across the organization.

Why: Microsoft pursues this strategy to achieve productivity improvements and cost structure advantages through AI deployment while maintaining competitive positioning in cloud infrastructure and productivity software markets. The company aims to capture efficiency gains from AI capabilities that enable smaller teams to accomplish work previously requiring much larger workforces, as demonstrated by the network operations executive who automated infrastructure management rather than requesting traditional headcount increases. This approach reflects broader industry trends as major technology companies achieve revenue growth with minimal employment expansion through AI-enabled productivity gains.