Why the real revolution isn't AI - it's meaning

"Peter Drucker saw this symbiosis first. He realized that the new industrial order would depend on a worker who produced ideas instead of widgets. The knowledge worker became the engine of prosperity, and management became the social technology that synchronized millions of minds. The modern firm was as much an invention as the transistor it depended on. Three decades later, Tom Peters caught the next wave."

"Both thinkers captured their moments, each explaining how machines reshaped management and management reshaped us. Now AI marks the third great inflection point. But this time the pattern breaks. Agentic AI doesn't just assist managers - it begins to replace them. It can coordinate schedules, allocate resources, even generate strategies faster than any human committee. The connective tissue of the modern firm is being rewritten in code."

"What remains distinctly human is not management, but imagination. The leadership that endures is adaptive and creative - the kind that thrives in ambiguity. A relief team improvising during a disaster, a founder balancing innovation with ethics, a general navigating conflicting missions: These are not algorithmic problems but human dilemmas. That's why the real revolution isn't AI itself but the space it exposes: a world where meaning, not management, becomes the organizing pri"

Since World War II, technology and management have coevolved, with each new computational leap producing new organizational forms such as bureaucracy, matrix structures, and project teams. The rise of the knowledge worker made management a social technology that synchronized countless minds and helped firms become inventions alongside machines. Desktop computing decentralized organizations into networks of project-based bursts of excellence. Agentic AI now threatens to replace managerial coordination by handling scheduling, resource allocation, and rapid strategy generation. Enduring human strengths will be imagination, adaptive leadership, ethical judgment, and meaning-making in ambiguous dilemmas.

Read at Big Think