McKinsey & Company has announced that it now operates an astonishing network of 25,000 artificial intelligence agents—a figure that underscores the firm’s aggressive pursuit of technological leadership in the consulting world. Yet this impressive number has also reignited an ongoing industry conversation about what truly defines success in the era of intelligent automation: the scale of deployment or the value each AI system brings.
While McKinsey emphasizes the breadth of its AI ecosystem, presenting it as evidence of innovation capacity and digital maturity, competitors such as Ernst & Young (EY) have challenged the notion that bigger automatically means better. According to EY’s head of global engineering, the real transformative potential of AI arises not from thousands of dispersed agents working in parallel, but from a smaller, carefully curated set of intelligent systems that generate meaningful impact. In other words, efficiency, depth, and integration may matter more than sheer numerical expansion.
This debate reveals an essential tension shaping today’s consulting landscape. Firms like McKinsey are racing to showcase technological prowess and to meet client demand for AI-enabled solutions across markets and sectors. At the same time, organizations such as EY suggest that strategic precision—investing in fewer but more capable AI tools—can yield stronger performance, reduce redundancy, and concentrate innovation on core business outcomes. Both perspectives shed light on a broader dilemma facing enterprises worldwide: how to balance ambition for scale with the discipline required to ensure sustainable, high-quality results.
In practice, scale can certainly deliver benefits. Having tens of thousands of AI agents allows McKinsey to experiment across a vast range of processes—from data analytics and client services to internal operations. Such diversity fuels learning, accelerates adaptation, and strengthens institutional expertise in data-driven decision making. But EY’s argument for selectivity carries equal merit: a limited collection of sophisticated systems, refined through continuous improvement, can often outperform a massive portfolio of experimental tools that lack deep optimization or strategic alignment.
As the consulting sector continues to modernize, this dialogue between quantity and quality is likely to intensify. The real question for executives and digital leaders is whether success in AI transformation will be measured by how many tools a company can claim—or by how effectively those tools reshape business performance, creativity, and human decision-making. The emerging consensus hints at a future where both dimensions coexist: scale will supply innovation velocity, while focus will anchor lasting value.
Ultimately, the conversation spurred by McKinsey’s 25,000 agents is less about rivalry and more about redefining excellence in digital transformation. It invites every organization to reconsider not just how many AI systems it builds, but how intelligently they are designed to complement human expertise, solve complex challenges, and sustain a competitive edge in an increasingly algorithmic economy.
Sourse: https://www.businessinsider.com/mckinsey-ai-agents-ai-adoption-consulting-ey-pwc-2026-2
