Exactly, AI is not just about technology application, but above all about business design: “What differentiates agentic AI from prior automation waves is its potential to allow organizations to fundamentally rethink the way core processes are designed, executed, and governed.”
While generative AI focused primarily on productivity gains, which did not materialize (see the “Gen AI Paradox“), agentic AI goes further:
“Agentic AI is not just a productivity tool. It is a new revenue engine—a strategic lever that could reshape cost structures, organizational models, and leadership KPIs. By automating workflows, enhancing quality control, and driving innovation, agentic AI enables companies to reengineer end-to-end processes, supporting new business models, such as outcome-based contracts and performance as a service. First movers stand to create lasting differentiation in markets where speed, intelligence, and adaptability are increasingly nonnegotiable.”
However, this requires a new TOP (technological, organizational, personnel) infrastructure:
“The agentic AI mesh [..] functions as the orchestration layer that enables complex agent ecosystems to scale effectively, operate safely, and evolve over time. The agentic AI mesh brings together both proprietary and off-the-shelf agents within a unified architecture, allowing them to collaborate, share context, and delegate tasks while accessing enterprise and commercial off-the-shelf systems.”
On top of the TOP infrastructure, we need AI business solutions:
“It requires visionary leadership, investment in scalable foundations, and a willingness to redesign end-to-end value chains around digital agents.”
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