Microsoft offers 60,000 employees the option to leave – what's behind the AI ​​transformation?

Why Microsoft is cutting jobs and investing heavily in AI despite record numbers

Microsoft's AI strategy is proving expensive – and is fundamentally changing the company

Microsoft is offering around 60,000 employees the option to leave the company voluntarily. This initially sounds like a massive reduction in staff – but the number only represents the pool of eligible employees. How many people will accept the offer remains to be seen. At the same time, the company is reporting record revenues and investing billions in data centers, AI chips, and cloud capacity. At first glance, this doesn't seem to add up. In fact, it reveals a profound transformation: Microsoft is aligning its workforce, cost structure, and revenue models for a future in which software is increasingly linked to the continuous need for computing power.

The economic challenge isn't simply about cutting staff or building as many AI systems as possible. Microsoft needs to prove that the additional revenue from cloud and AI services will sustainably outweigh the costs of infrastructure, energy, depreciation, and organizational changes. At the same time, a voluntary redundancy program carries risks: With experienced employees leaving, valuable knowledge can be lost, while the remaining teams will have to take on additional responsibilities.

Therefore, the decisive factor is not solely the number of employees who leave. What will matter is whether Microsoft can profitably utilize its infrastructure, whether customers will continue to pay for AI services, and whether the organization can be restructured to maintain productivity and quality. The severance package is thus not clear evidence of an economic crisis – but rather a visible sign of how comprehensively the company is restructuring its business model for the AI ​​age.

Microsoft's AI transformation: Why a record-breaking corporation is offering 60,000 employees the option to leave

Billions for machines, severance packages for people

Microsoft's voluntary redundancy program is not evidence of an economic downturn, but rather an expression of a profound restructuring: The company is combining strong growth with an increasingly capital-intensive AI strategy and a reorganization of its workforce. Around 60,000 employees can receive an offer of voluntary redundancy under certain conditions; this does not imply either 60,000 imminent departures or a corresponding cost savings.

The economically crucial question, therefore, is not simply how many people will leave Microsoft. The decisive factor is whether the company can transform its combination of computing power, software, expertise, and customer relationships in such a way as to generate sustainably higher added value. A severance package can facilitate this transition, but it can also destroy valuable knowledge. Billions in investment can create a long-term competitive advantage, but they can also tie up capital in assets whose profitability depends on utilization, power supply, technological development, and willingness to pay.

The central perspective of this analysis is therefore this: Microsoft is not simply trying to replace humans with AI. The company is reorganizing its cost structure, revenue streams, and competencies for a business model in which software is increasingly sold along with continuously consumed computing power. Whether this transformation succeeds will not depend on the size of the severance package, but rather on whether the additional revenue exceeds the total costs of the new infrastructure and the organizational adjustments.

60,000 eligible persons is not a reduction target

The program, presented on October 26, 2026, is aimed at eligible employees of participating organizational units in the USA, Canada, India, and the UK up to and including internal career level 70. The pool of approximately 60,000 potential participants represents about 26.9 percent of the most recently reported global workforce of 223,000 people. This figure describes the reach of an offer, not the likelihood of job loss, nor the extent of any planned workforce reduction.

Chief Human Resources Officer Amy Coleman sees the program as part of a revised approach to organizational change, designed to create greater flexibility and additional opportunities for career transitions. A decision on whether to accept the offer is expected in early December; participants are slated to leave by December 31, 2026. No firm target number of departures or overall budget has been publicly disclosed. This leaves the immediate financial implications unclear: without knowing the number of participants, individual package costs, future replacements, and transition expenses, it is impossible to calculate a reliable net savings figure.

The delineation of participating areas is also important. Certain sales organizations, as well as parts of marketing, engineering, and other functions, are not participating. This does not imply that individual employees in these areas have personally rejected the offer. The selection is made at the organizational level based on business priorities, customer commitments, and staffing needs. From an economic perspective, this indicates a controlled restructuring, not a blanket withdrawal from all business areas.

Growth does not protect against restructuring

The financial situation doesn't fit the image of a company that needs to secure its survival in the short term due to plummeting demand. In fiscal year 2026, which ended on June 30, Microsoft generated $331.8 billion in revenue and $155.2 billion in operating income. Revenue increased by approximately 18 percent, and operating income by approximately 21 percent. The reported figures result in an operating margin of approximately 46.8 percent, compared to 45.6 percent in the previous year.

This very strength, however, explains why management sees room for a preventative restructuring. A profitable corporation can finance severance packages, manage transitions, and simultaneously invest in new business models. It doesn't have to wait until a deterioration in its competitive position forces it to take hasty measures. However, this does not automatically justify every cutback: Economic success also increases the demands for a transparent balance between short-term efficiency and long-term performance.

The apparent contradiction between record results and staff reductions resolves itself as soon as a distinction is made between the company as a whole and its individual operations. Not every task grows in line with overall revenue. Not every hierarchical level contributes equally to the next stage of development. Simultaneously, the demand for certain skills may increase while other tasks require fewer personnel. Growth and declining staffing needs in selected areas can therefore occur concurrently.

The cash flow tells the counter-calculation

Particularly revealing is the free cash flow, which, simply put, is the money remaining after ongoing business operations and cash-generating capital expenditures. For April through June 2026, this cash surplus amounted to US$19.64 billion, approximately 23 percent lower than the previous year. This figure refers to the second calendar quarter, which is also Microsoft's fourth fiscal quarter of 2026, not the second quarter of Microsoft's fiscal year.

The underlying cash flows reveal the cause of the decline more precisely. Operating cash flow increased this quarter from $42.65 billion to $55.44 billion; at the same time, capital expenditures rose from $17.08 billion to $35.80 billion. Thus, ongoing operations generated significantly more cash, but additional capital expenditures grew even more. A decline in free cash flow should therefore not be equated with a decline in operating profitability.

Looking at the year as a whole, the same pattern emerges, albeit in a less pronounced form. Operating cash flow increased from $136.16 billion to $182.94 billion, while capital expenditures rose from $64.55 billion to $115.95 billion. This resulted in free cash flow of $66.99 billion, compared to $71.61 billion in the previous year, representing a decline of approximately 6.5 percent. The company continues to generate substantial financial surpluses but must allocate an increasing share of its funds to infrastructure development.

Software receives industrial fixed costs

The change is reflected in the investment ratio. Cash-effective capital expenditures amounted to approximately 34.9 percent of revenue in fiscal year 2026, compared to 22.9 percent in the previous year. Relative to operating cash flow, their share increased from approximately 47.4 to 63.4 percent. These figures capture the corresponding capital expenditure payments, not all economic infrastructure obligations, including all forms of leasing.

Microsoft remains a software and platform company, but is increasingly taking on the financial characteristics of an infrastructure operator. Data centers require buildings, network connections, power, cooling, servers, and continuous technical upgrades. A significant portion of these costs is incurred before customers fully utilize the provided capacity. This results in a time lag between capital expenditure and economic return.

The crucial resource is therefore no longer just the ability to develop and distribute software worldwide. It also includes the ability to provide physical capacity in a timely manner and operate it as efficiently as possible. This creates a different management challenge: it must coordinate demand, procurement, construction, commissioning, energy supply, and product development. Personnel costs remain important in this context; however, they are embedded within a significantly broader capital and cost accounting framework.

Accounting rules change the visible costs

A particularly important difference exists between actual investment activity and its representation in individual financial metrics. Microsoft initially projected capital expenditures of approximately $190 billion for the calendar year 2026. In July, this forecast was revised downward to about $175 billion, without a corresponding reduction in the underlying investment intentions.

The background to this is an extension, implemented at the beginning of fiscal year 2027, of the estimated useful life of data center and office buildings from 15 to 25 years. This is intended to classify more future data center contracts as operating leases rather than finance leases; finance leases are included in the aforementioned investment indicator, while operating leases are not. Therefore, the lower figure should not be interpreted as an equivalent real reduction in the infrastructure program.

For economic analysis, the entire future payment obligation is what counts, not just its allocation to a reporting item. Ongoing lease payments don't disappear just because they appear outside a specific investment metric. Similarly, the changed useful life affects buildings, not the technical life cycles of AI accelerators in general. Therefore, anyone wanting to assess the viability of the strategy must consider investment payments, lease obligations, depreciation, and ongoing operating costs together.

Faster chips reduce planning certainty

The technical composition of expenditures increases the demands on investment appraisal. In the fourth fiscal quarter of 2026, approximately two-thirds of the reported capital expenditures were for shorter-lived assets, primarily CPUs and GPUs; the remaining portion involved longer-lasting infrastructure. Therefore, a data center building and an AI accelerator are not economically the same type of asset, even if they are located at the same site.

For returns, the crucial factor is how long an investment delivers competitive performance at marketable costs. More powerful hardware, more efficient models, and improved software can reduce the cost per task. This helps Microsoft expand its capacity but can simultaneously increase price and upgrade pressures on older systems. Therefore, technical usability and economic competitiveness must be considered separately.

The rapid growth of fixed assets is already evident. The net book value of property, plant, and equipment increased to US$313.1 billion at the end of fiscal year 2026, up from US$205.0 billion in the previous year. Annual depreciation expenses rose from US$22.0 billion to US$34.3 billion. This wave of investment is therefore not only impacting current cash flow but also increasingly affecting future income statements.

Electricity is becoming a competitive factor

The AI ​​strategy is subject not only to financial but also physical limitations. An updated international energy projection for 2026 anticipates that global data center electricity consumption will increase from approximately 485 terawatt-hours in 2025 to around 950 terawatt-hours in 2030. This would then represent roughly 3 percent of global electricity demand; for AI-focused data centers, electricity consumption is expected to triple during this period. This is a global projection, not a consumption forecast for Microsoft.

Microsoft cites the availability of land, predictable energy, network components, and servers as prerequisites for operating and expanding its data centers. A purchased AI system can only generate economic benefits once the entire site is operational. Delayed network connections or component shortages can therefore extend the time to a return on investment, even if customer demand exists.

Location quality is therefore also a factor in the return on investment. Cheap energy alone is not enough if availability, grid stability, or commissioning are uncertain. Conversely, a more expensive location can be economically attractive if it can be used more quickly and better meets customer requirements. These dependencies limit the benefits of across-the-board cost-cutting programs: Lower personnel costs neither automatically accelerate grid connection nor eliminate technical supply bottlenecks.

Severance payments are advance renovation costs

A voluntary severance program defers expenses over time. Initially, severance payments and other benefits are incurred; later, ongoing personnel costs can decrease. Microsoft combines the new offering with financial support and assistance for career reorientation. Individual terms depend, among other things, on the applicable regulations and specific offers; a uniform, publicly stated amount is not available.

The economic analysis must go beyond the ratio of severance pay to annual salary. Potential follow-up costs include handovers, temporary double staffing, external service providers, new hires, onboarding, and productivity losses. Remaining teams may require additional support if tasks are not eliminated but merely distributed among fewer people. Therefore, the gross savings on a personnel cost center can significantly exceed the actual net savings.

Conversely, a well-designed program can be economically advantageous if tasks are permanently eliminated, decision-making processes are simplified, or employees are already considering a change of employer. The crucial factor is whether Microsoft actually reorganizes the affected activities. If an internal position is eliminated and its work is subsequently outsourced at a higher cost, a specific personnel statistic might improve, but not necessarily the overall profitability.

Voluntary participation creates a selection problem

The program extends from career level 70 into higher management levels and partially includes employees with Vice President titles; the previous retirement offer was limited to the Senior Director level. This creates the possibility of changing not only operational positions but also management and coordination structures. However, it is not yet known which levels will actually shrink and to what extent.

Voluntary programs carry an inherent selection risk: The company defines the eligible group, but employees decide for themselves whether to participate within that framework. People with good external opportunities may be more willing to leave. Employees with particularly valuable experience may find the offer just as attractive as those whose tasks can be more easily redistributed. Therefore, voluntary participation does not guarantee an economically optimal composition of departures.

This problem can only be partially managed by the number of participants. More important are knowledge transfer, succession planning, and the identification of critical customer and system knowledge. A small loss of key competencies can trigger greater follow-up costs than a significantly higher number of departures in less sensitive roles. Therefore, the quality of the remaining organization is more meaningful than simply the headcount.

The previous quota gives a false sense of security

Microsoft launched its first voluntary retirement program in April 2026; in July, it was revealed that more than 30 percent of eligible employees had participated. That same month, the company announced the elimination of approximately 4,800 jobs. The new program builds on the experience of the previous one but is aimed at a significantly broader and differently composed group of people.

Applying the previous acceptance rate to the approximately 60,000 currently eligible individuals would not be methodologically sound. A retirement offer for long-term employees triggers different decisions than a more general early retirement offer without the same life-stage focus. Age, career prospects, assets, family obligations, and job market opportunities all influence participation. Microsoft expects a significantly lower acceptance rate for the new program than for the previous retirement offer.

Furthermore, the various measures must not be added together to form a total figure without examining their timing and overlaps. Program scope, announced job cuts, and the number of employees on a given balance sheet date measure different things. New hires and internal transfers further alter the relationship. A reliable personnel balance sheet requires actual departures, new hires, and changes in responsibilities, not simply the addition of publicly reported headline figures.

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AI is changing jobs

Microsoft uses AI tools internally in areas such as programming, sales, and the supply chain. However, this does not necessarily imply a direct, one-to-one relationship between AI usage and the potential job losses. Back in July, the company distinguished between positions that would not be directly replaced by AI and workflows that would be fundamentally changed by AI.

This distinction makes economic sense. A job typically consists of several tasks: gathering information, preparing decisions, handling exceptions, communicating with customers, taking responsibility, and monitoring results. AI can accelerate individual components without reliably taking over the entire task. Only when workflows and responsibilities are redesigned can this lead to a permanently altered staffing requirement.

Productivity, therefore, cannot be equated with the number of texts or lines of code produced. More output can lead to additional testing effort, new sources of error, or higher subsequent technical costs. What matters are usable results per resource used, taking quality and risk into account. For Microsoft, this means that internal efficiency gains must be reflected in shorter development times, better products, or lower overall costs, not just in more intensive use of its own tools.

Productivity requires reliable metrics

Empirical studies argue against sweeping assumptions about the impact of generative AI. A study of 5,179 customer support employees found an average productivity gain of around 14 percent, with less experienced employees benefiting particularly strongly. The benefits were therefore not evenly distributed across all skill levels.

For experienced developers, however, a study based on tools and tasks from early 2025 showed longer processing times with AI support. These historical results cannot be directly applied to today's tools: The continuation of the study in early 2026 indicated potential accelerations, but due to selection and measurement issues, it did not allow for a reliable general estimate. This development underscores how quickly technological advances and methodological uncertainties can alter the assessment.

For corporate management, the consequence is clear: efficiency assumptions must be based on concrete workflows. Suitable key performance indicators (KPIs) include, for example, time to productive deployment, errors after publication, successfully resolved customer problems, or avoided supply chain disruptions. A personnel model that assumes a uniform increase in productivity in advance would obscure differences between tasks and experience groups. Only reliable measurements provide the basis for permanently redistributing capacities.

License slots lose their revenue monopoly

In parallel with its internal reorganization, Microsoft is changing its monetization strategy. The company is moving more towards a combination of user-based licenses and usage-based billing for its AI offerings. Usage-based billing has been introduced for GitHub Copilot; additional consumption-based components are also gaining importance in other product areas.

This has an economic basis. Traditional software could be widely distributed after its development, whereas AI requests require additional computing power. With an unlimited flat fee, intensive usage can increase costs more than revenue. A consumption-based component improves the ability to align revenue with actual infrastructure usage. However, it increases the need for customers to continuously monitor costs and usage.

In addition, there is a strategic safeguard. If customers with fewer employees perform the same or more work, a purely person-based licensing model can come under pressure. By also compensating for automated tasks and AI usage, Microsoft can profit from the growing digital labor, even if the number of human users doesn't increase accordingly. This doesn't guarantee higher profits, but it does shift the economic foundation from the pure workplace to a combination of workplace and machine activity.

Customers only pay for results

Usage-based pricing doesn't solve the problem of willingness to pay. Increased computing power is not an end in itself for customers. Automated processing is only economically attractive if its benefits outweigh the total costs. This includes not only software and computing power, but also integration, data preparation, training, monitoring, and the correction of erroneous results.

For an industrial company, the relevant benefits might lie in less downtime, more accurate planning, or faster technical documentation. In logistics, better scheduling, shorter processing times, or fewer exceptional cases could be crucial. Such applications are not profitable simply because a model is powerful. They must be integrated into real-world processes where the data, responsibilities, and consequences of errors are known.

Microsoft is thus faced with two interconnected return-on-investment tests. The customer must achieve a sufficient economic benefit from the use of AI. At the same time, Microsoft must maintain an attractive profit margin after covering computing, infrastructure, sales, and development costs. If these two aspects are confused, high usage figures can create a false impression of profitability that has not yet been achieved on one side of the business relationship. Sustainable growth only arises when both calculations are viable.

The demand is already real

The investment strategy is not based solely on an as-yet-unproven future expectation. Microsoft generated $214.4 billion in cloud revenue in fiscal year 2026, 27 percent more than the previous year; Azure exceeded $100 billion in annual revenue for the first time. However, these figures do not represent pure AI revenue but also include other cloud services. Therefore, they should not be interpreted as the direct monetization of the new AI investments.

A more concrete indicator of product demand is the more than 30 million paid Microsoft 365 Copilot seats at the end of the fiscal year, compared to around 20 million in the immediately preceding quarter. Paid licenses are a more economically meaningful indicator than mere registrations, but they don't yet demonstrate the intensity of use or the long-term customer value. For sustainability, renewals, actual usage, and the willingness to pay for additional services are crucial.

On the supply side, Microsoft commissioned a total of 88 new data centers in fiscal year 2026. This underscores the scale of its expansion, but it doesn't replace capacity or return on investment metrics: Data centers vary in size, equipment, and tasks. Therefore, economic analysis must distinguish between visible expansion figures and actual, productively usable capacity. Only the combination of available capacity and profitable customer utilization completes the investment cycle.

Growth alone does not protect a profit margin

The development of margins already reveals differing forces at play. In fiscal year 2026, the calculated gross margin fell from approximately 68.8 to 67.9 percent, while the operating margin increased. The higher proportion of direct service costs to revenue was thus more than offset by a lower proportion of other operating expenses. However, this does not reveal what specific proportion was attributable to staff reductions, product mix adjustments, economies of scale, or other efficiency measures.

In the fourth fiscal quarter of 2026, Microsoft's cloud gross margin was 65 percent, below the previous year's level; contributing factors included the higher Azure share, the expansion of AI infrastructure, and increased product usage. At the same time, revenue from Azure and other cloud services grew by 43 percent. Strong growth and margin pressure are therefore not mutually exclusive.

This leads to a sober assessment of the restructuring program. While lower personnel costs can support the operating margin, they don't replace the need for attractive profitability in the AI ​​products themselves. If each additional use generates too little contribution margin, the problem cannot be permanently solved by cutting costs in other areas. The central challenge remains developing infrastructure costs and prices in such a way that more business also generates more economic surplus.

Multiple models reduce individual dependencies

Microsoft provides cloud services for OpenAI, Anthropic, and other companies, offering customers access to models from various vendors. This position is strategically important because the company doesn't have to rely solely on a single AI model remaining consistently superior. Computing power, data platforms, identity management, security features, and enterprise applications can remain relevant even as model preferences shift.

Economically, this is a platform bet: Microsoft wants to profit from the use of intelligent systems, regardless of which vendor's model performs a particular task best. Developing its own models and chips simultaneously expands the possibilities for optimizing costs and performance across multiple technical layers. This allows the company to reduce its dependence on individual external suppliers without having to completely forgo their innovations.

The risks don't disappear. Large customers can possess considerable negotiating power, build their own infrastructure, or shift their demand between platforms. Model diversity protects against a specific technological dependency, but not automatically against price competition or weaker overall demand. The crucial question remains whether Microsoft offers an advantage through integration, reliability, and economic performance that will retain customers in the long term.

Order backlogs are not yet cash

At the end of fiscal year 2026, outstanding commercial performance obligations stood at US$678 billion, 84 percent higher than the previous year. The average term was approximately 2.3 years; roughly 30 percent was expected to be realized as revenue within the next twelve months. These figures demonstrate a substantial contractual demand base but do not equate to immediately available cash.

The composition of the order backlog is also important for this assessment. Excluding OpenAI, the growth in these commitments was 25 percent; the entire increase compared to the immediately preceding quarter came from customers outside the leading model companies. This suggests broader demand beyond individual large AI partners. However, a large order backlog alone says little about the margin remaining after the necessary investments.

The economic quality of a contract depends on pricing, duration, actual delivery volume, performance costs, and solvency. Long-term commitments can provide planning security but can also tie up resources. Therefore, for capital allocation, Microsoft must not only generate as much future revenue as possible but also prioritize those contracts whose expected return aligns with the capital invested and the risk assumed.

Four countries, different labor markets

The fact that the restructuring plan includes the USA, Canada, India, and Great Britain simultaneously argues against a simple narrative that only expensive locations are being replaced by cheaper ones. The list of countries does not demonstrate a shift in a specific direction, nor does it imply a uniform cost logic. It primarily shows that the restructuring affects several key personnel locations.

The decision to participate can have very different economic consequences depending on the country. Taxes, social security, medical coverage, residency status, and local employment opportunities can significantly alter the value of the same nominal offer. Therefore, a simple comparison of severance payments without considering these factors would be of little value. Furthermore, companies face varying labor laws and transitional arrangements.

A global personnel measure does not necessarily imply a general withdrawal from a country. A corporation can reduce administrative functions while simultaneously seeking specialists in security, infrastructure, or customer-facing implementation. Whether the overall workforce at a location changes depends on the interplay between departures and future hires. Therefore, the key indicator is the specific expertise within a business process, not solely the geographical location.

Fewer jobs need more knowledge transfer

A frequently underestimated cost factor is institutional knowledge. Experienced employees are familiar not only with documented processes but also with their exceptions: legacy technical issues, specific customer requirements, informal agreements, and the reasons behind past decisions. This knowledge cannot be fully reconstructed from job descriptions or existing documents. Especially in complex business systems, it can be crucial for reliable service delivery.

A voluntary program with a common exit date therefore requires careful handover planning. The period until the end of December is not only a decision deadline, but also a limited window for documentation, succession planning, and organizational disentanglement. If too many handovers are required simultaneously, the remaining organization may experience a temporary increase in workload. This is a potential implementation risk, not a consequence of the current program that has already been observed.

Alongside previous downsizing measures, Microsoft has utilized internal transfers, reporting more than 4,000 such moves within a year in July. This demonstrates that adjustments don't necessarily have to involve departures. Economically, internal training can be more cost-effective than losing existing expertise and subsequently recruiting externally. Whether it's worthwhile depends on how quickly new skills can be developed and what tasks will actually be needed in the future.

The capital market is not neutral

The personnel decision is taking place within a broader distribution of financial resources. In fiscal year 2026, Microsoft paid out approximately $26.45 billion in cash dividends and acquired its own shares worth $16.72 billion through reported share buyback programs. This totals approximately $43.16 billion; additional share buybacks to cover taxes on employee stock are not included in this narrower figure.

These figures make it clear that the issue is not simply whether funds are available. It also concerns priorities between infrastructure, personnel, research, cash reserves, and dividends. This does not mean that every share buyback is economically unsound. However, it does mean that staff reductions should not be explained solely by an abstract financial emergency when substantial funds are simultaneously being distributed to shareholders.

The appropriate economic question is which use will generate the highest risk-adjusted benefit in the long run. Additional AI capacity may be more valuable than an unchanged administrative structure. Conversely, an experienced specialist may be more valuable than prematurely acquired server capacity. Capital allocation must evaluate both using the same criteria: expected return, uncertainty, time commitment, and difficult-to-reverse losses.

The labor market bears transition costs

Even if a workforce restructuring is rational from a company perspective, it can incur societal costs. Severance payments improve the financial situation of departing employees, but they do not guarantee an equivalent new position or the continuation of their previous income. Professional experience can be valuable outside the previous company, but often needs to be transferred to a new organizational environment.

At the same time, the release of skilled professionals can benefit other companies. Medium-sized businesses, consultancies, or young technology companies could profit from expertise previously tied to a large corporation. However, this positive effect is a possibility, not an automatic compensation. It depends on the availability of receptive companies, suitable projects, and sufficient funding.

The overall economic impact cannot therefore be derived from a single corporate decision. AI can displace jobs, change existing professions, and create new demand. How these effects coincide depends on prices, competition, skills, and the speed of organizational adaptation. Microsoft's program is a relevant example of this transition, but not conclusive proof of a predetermined future for all knowledge work.

What the renovation will depend on

Three development paths are conceivable, although no reliable probabilities can currently be assigned to them. In the best-case scenario, usage and willingness to pay increase, computing costs per economically relevant result decrease, and Microsoft simplifies its organization without critical loss of knowledge. Then, high infrastructure investments and a smaller workforce in selected areas could combine to lead to increased value creation.

In a medium-term scenario, demand remains robust, but additional revenue is increasingly eroded by depreciation, energy, leasing, and price competition. The divestment program could then dampen operating cost growth without significantly improving overall profitability. In a worst-case scenario, capacity is built up too early, customers limit their consumption, and key expertise is lost. In this case, an initially successful cost restructuring would weaken the ability to profitably utilize the infrastructure.

Therefore, what should be observed are actual departures rather than the number of eligible employees, net savings rather than eliminated staff budgets, and economic utilization rather than mere AI activity. In addition, the development of free cash flow, full infrastructure commitments, customer retention, and product quality should be considered. Microsoft has the financial strength to actively manage the transition. However, proof of its economic quality lies not in the number of severance packages offered, but in consistently profitable services for which customers voluntarily and repeatedly pay.

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