In recent weeks, the debate over the accuracy of OpenAI’s GPT-5 model has reignited conversations about AI. Some voices question whether it represents a disruptive leap or whether its impact is being overstated. It mirrors what’s happening across the market: when enthusiasm runs too high, the risk of disappointment multiplies.
Over the past two years, GenAI has gone through one of the most exaggerated hype cycles in tech history. Its power to transform content creation, productivity, and even business models seemed limitless. And unlike other innovations, there was barely any time to cross the well-known “trough of disillusionment” in Gartner’s Hype Cycle. Before the tide ebbed, an even bigger one arrived: AI agents.
Today, nearly every new product or service introduced to the market is being branded as “agentic.” Both major tech vendors and emerging players have doubled down. If GenAI promised to revolutionize how we work, AI agents offer something more ambitious: rethinking how companies operate as a whole. Why limit ourselves to automating current processes if we can transform entire value chains?
Phases of adjustment, realism, and consolidation
Before we fully travel GenAI’s learning curve—with its lessons, failures, and proven wins—we’re being offered a second, even steeper roller coaster. Experience, however, shows that no technology achieves real impact without first going through phases of adjustment, realism, and consolidation. The risk is clear: a wave of mistrust could surface at the first disappointment, leading to budget cuts and the slowdown of strategic initiatives precisely when companies most need to build internal capabilities.
That’s why we need to separate the short-term buzz from the deeper trends shaping the market. The potential of Agentic AI is real. Its impact may not arrive as quickly as some claim, and we may go through a correction phase in the coming months, but the course is already charted. In terms of business process design, the operation of global value chains, and the creation of digital assets to differentiate ourselves with customers and competitors, intelligent agents will drive real transformation.
Concrete use cases that bridge the gap from theory to real-world operations are rapidly multiplying. Consider, for example, agents capable of orchestrating heterogeneous systems to execute complex end-to-end administrative tasks in back-office operations. Or customer-service agents that go beyond answering questions to make decisions, escalate incidents, and personalize interactions in real time. Or agents dedicated to the supply chain that anticipate logistics disruptions, negotiate with suppliers, and recommend corrective actions.
These cases demonstrate that this is not about “advanced chatbots,” but about a new operational intelligence layer redefining how organizations create value.
The future is agentic
Even if skeptical or critical voices emerge, the recommendation for large enterprises is clear: keep investing. Agentic AI represents an irreversible technological and business metamorphosis. It’s essential to move beyond abstract promises and focus on specific use cases with tangible business impact—always within a solid framework for agent governance.
That framework includes data quality and management (RAG, embeddings, chunking, context management), guardrail design, and security policies that control autonomy without compromising reliability or regulatory compliance, along with human-in-the-loop oversight for strategic decision cycles.
The future will be agentic—not built on hype, but on strategic vision, disciplined execution, and robust governance.
How ready is your organization to embrace Agentic AI? Contact me with any questions — Pablo Sáez | LinkedIn