Layoffs in a Boom: Profits Up, Headcount Down
A striking disconnect is emerging across the software industry: record profits on one hand, large-scale layoffs on the other. Software company layoffs are no longer confined to struggling firms trimming costs in a downturn. Instead, profitable giants are announcing tech workforce reduction plans of 15–20% while emphasizing “faster, leaner” operations and an AI-first strategy. These companies are positioning AI job cuts as part of a strategic evolution, not a financial emergency. The common thread is a margin expansion strategy: executives explicitly talk about boosting operating margins and earnings per share, even as revenue grows. In practice, that means treating labor as a cost base to be structurally reset. AI is framed as the catalyst—promising higher productivity with fewer people—while shareholders are reassured that new automation-driven efficiencies will flow directly to the bottom line.
Intuit: Cutting 17% While Buying Back Stock and Raising Guidance
Intuit illustrates this new playbook starkly. The company cut 3,000 jobs—17% of its roughly 18,200-person workforce—after previously eliminating 1,800 roles in an earlier restructuring. Yet it reported quarterly revenue of USD 4.65 billion (approx. RM21.4 billion) and told investors it had spent USD 3.4 billion (approx. RM15.7 billion) on stock repurchases over nine months, with an additional USD 8 billion (approx. RM36.8 billion) authorized for buybacks. CEO Sasan Goodarzi insisted the move was “not about AI,” instead citing too many management layers and “coordination-heavy” roles in product, project management, and operations. He was explicit that “a big chunk” of the savings will go to margin expansion and earnings-per-share growth. At the same time, Intuit is refocusing on AI-enabled workflows and external AI partnerships, signaling that incremental revenue will increasingly come from software automation rather than additional headcount.
Meta: Job Cuts to Fund a Massive AI Spending Spree
Meta is taking a more overt AI-first route to tech workforce reduction. The company is axing about 8,000 jobs—around 10% of its global headcount—as part of a restructuring designed to bankroll as much as USD 145 billion (approx. RM667.8 billion) in capital expenditure on artificial intelligence. Engineers and product teams are bearing much of the impact, even as around 7,000 employees are redeployed to new AI-focused groups building agents and assistants across Meta’s apps and devices. Internal messaging frames the shift as moving to a flatter structure with smaller teams that can operate faster and with more ownership. Here, software company layoffs function less as a rescue measure and more as a way to redirect resources into long-horizon AI bets. The underlying logic is that a leaner workforce plus outsized AI infrastructure investment will position Meta for future dominance—and higher long-term returns.
Workday: Explicitly Decoupling Growth from Hiring
Enterprise software restructuring is following a similar pattern at Workday, but with unusual candor. After an earlier 8.5% cut of 1,750 positions, Workday now reports rising revenue of USD 2.54 billion (approx. RM11.7 billion) and net profit of USD 222 million (approx. RM1.02 billion), up from USD 68 million (approx. RM313.6 million). CEO Aneel Bhusri has stated his aspiration is to keep headcount “as close to flat for the year as possible,” even as the company sustains growth and expands margins. The lever is AI: Workday wants AI agents and its own software to “punch in” instead of hiring new recruits. In other words, productivity gains from AI will not translate into more jobs; they will translate into margin expansion. This approach crystallizes a broader shift: enterprise vendors now see revenue growth as something to be achieved with stable or shrinking staff, not larger teams.
AI as Cover for a New Labor Model in Software
Taken together, these moves signal a fundamental shift in how mature software companies view their workforce. Previously, growing subscription revenue often meant scaling sales, support, and engineering headcount in tandem. Now, AI transformation is enabling a decoupling: incremental revenue is expected to come from automated systems, not larger teams. Software company layoffs are framed as modernization or a pivot to system intelligence, but the economic logic is clear. Labor-intensive “coordination-heavy” roles and overlapping functions are being eliminated; hiring, where it occurs, is tightly concentrated in AI-aligned specialties. The workforce is increasingly treated as a cost center to be optimized for efficiency, rather than a resource that grows automatically with top-line expansion. As AI tools improve, the default assumption in many boardrooms appears to be: keep headcount flat—or lower—and let the machines drive the next leg of growth and shareholder returns.