Could the race toward artificial intelligence and quantum supremacy be rewriting the corporate workforce faster than expected? If so, then IBM’s latest move-announcing it will cut a “low single-digit percentage” of its 270,000 global employees before year’s end, which could mean several thousand jobs-would suggest the answer is yes. Yet while executives frame the decision as a routine “rebalance,” the timing and context point to a deeper strategic transformation: a shift toward AI-driven efficiency and next-generation computing.
IBM’s chief executive, Arvind Krishna, is refreshingly candid on the question of automation: AI agents have already replaced the work of some 200 human resources staff, freeing up capacity to hire more programmers and salespeople. Part of a broader corporate pattern, AI-driven workforce automation is cutting white-collar roles, particularly in areas where productivity gains can be captured with minimal disruption to customer-facing operations. Only 11 per cent of US companies report actively reducing headcount as a result of AI, according to data from Goldman Sachs, but that rises to 31 per cent in the tech, media and telecom-end sectors where adoption is fastest.
The pace of change is striking: “The pace of adoption of this technology is going a little bit faster… the short-term disruption might be a little bit higher.” said David Solomon, CEO of Goldman Sachs. IBM’s own trajectory reflects that acceleration. Beyond AI, the company is making big bets on quantum computing in a race to beat Google, Microsoft, and a cluster of startups in constructing machines that can do calculations beyond the capabilities of the best classical systems. Its roadmap calls for a quantum-centric supercomputer by 2025 with more than 4,000 qubits, using modular architectures such as the IBM Quantum System Two, itself capable of supporting up to 16,632 qubits. At that scale, utility-grade workloads would be possible in optimisation, AI, and complex simulations.
The engineering challenges are extreme: Quantum processors that can maintain coherence in qubits, correct errors at scale, and operate in cryogenic environments at near absolute zero are needed. IBM’s Heron processor marked progress toward higher circuit quality, targeting the ability to run 5,000 gates with parametric circuits. A related focus is middleware automation, in order to be able to bridge quantum and classical computing for enterprise applications. Krishna has said that quantum computing will be a differentiator for businesses, enabling algorithms in materials science and chemistry impossible with classical systems.
None of this technology investment in AI or quantum infrastructure is very different from what’s occurring at other tech giants. Amazon Web Services recently unveiled the Ocelot chip to drive down error correction costs by as much as 90%, while Google touts its Willow chip for logical qubit scaling. Microsoft’s topological qubit-based Majorana 1 processor is designed for scaling up to a million qubits. Each one is targeted at the exact same end result: fault-tolerant quantum systems that solve the problems of the classical device. For IBM, the workforce changes are not isolated cost-cutting measures but represent a conscious reallocation of talent into these growth areas. The company saw software revenue soar 10% last quarter, driven by demand for AI services.
IBM’s SVP and CFO James Kavanaugh pointed to IBM’s “integrated tech stack” and more than 1,000 client engagements on generative AI this fiscal year. Deals like these signal that enterprise-grade AI is not some laboratory experiment but a commercial fact that’s changing corporate structures. But, already, a human effect is clear. AI could displace half of entry-level white-collar jobs and drive unemployment rates as high as 20% in the near term, Anthropic CEO Dario Amodei has said. Federal Reserve Chair Jerome Powell says “a significant number of companies” are either cutting staff or pausing hiring because of AI.
In IBM’s case, the cuts are heavier in areas where automation makes a measurable difference. The competitive stakes in quantum computing add urgency to this IBM restructuring. Achieving quantum advantage-the point at which quantum machines solve problems infeasible for classical systems-could reshape entire industries. Scalability, error rates, and integration remain major challenges, and the race is at least as much about engineering breakthroughs as corporate strategy. IBM’s layoffs, then, are less a response to market pressures than a recalculation for a future in which AI agents and quantum processors are central to its value proposition.
