By Philippe Deblois
In business, timing often determines who leads and who falls behind, and right now, that's especially important considering the impressive pace of change. Today, one of the most pressing changes comes with the rise of agentive AI. What began as an experiment in secondary areas of organizations is rapidly becoming central to business operations, shaping competitive advantage in the eyes of leadership. Just as cloud computing reshaped how companies expanded and operated, agentive AI is redefining how work gets done.
The progress of agentive AI marks a moment when conversations at the senior leadership level need to evolve from knowledge to strategy. Executives need to think about where agentive AI can generate immediate impact, how to test it responsibly, and how to prepare their organizations to scale its use over time.
To understand the power of agentic AI in business, it's necessary to understand that it goes beyond simply responding to commands. These systems execute tasks, anticipate needs, and connect workflows across platforms with minimal human intervention, within clear governance boundaries. This level of autonomy is what makes this technology a major advancement.
Companies across various sectors are testing tools, often with results that surprise even their own teams. As businesses face increasing pressure to do more with less, agentive AI presents an opportunity that cannot be ignored. For senior leadership, the message is clear: if teams aren't experimenting with agentive AI use cases, they risk falling behind. Encouraging exploration now is about building future resilience.
Why do teams come out winning?
One of the biggest reasons to prioritize agentic AI is its versatility. Unlike tools that only benefit specific departments, agentic AI transforms how all teams work. Operations that previously required manual supervision and intervention can now be performed autonomously. All teams in the organization can deliver faster, more agile service, reducing the resources needed to maintain quality standards. This broad applicability changes the strategic conversation. Agentic AI creates value simultaneously across multiple functions, from customer-facing operations to internal processes. This is one of the reasons why boardroom conversations have shifted from departmental technology decisions to planning company-wide transformation.
Companies need systems that unify security data, operational metrics, and business performance indicators on a reliable basis. Without this connected view, agency AI cannot generate reliable or accountable information at scale to support business decisions. Business leaders should plan enterprise-wide implementations, rather than testing AI in just one department.
The result is competitive advantages that accumulate at all stages of the business. Faster decision-making, better resource allocation, and more resilient operations are key advantages. When agents take over repetitive processes, teams gain time and focus, allowing them to concentrate on tasks and projects that drive long-term growth and success.
Companies that effectively integrate agentic AI will also see gains in innovation cycles, speed to market, and customer satisfaction. These results support departmental KPIs, but also shape overall performance metrics that are important to leadership, from revenue growth to shareholder confidence. The question for executives then becomes when they want to start reaping these benefits, rather than waiting until it becomes standard practice.
In this scenario, governance cannot be an afterthought. Autonomy without accountability brings risks. Leaders must establish clear guidelines and policies that balance innovation and risk management. Compliance and visibility into how an agent acts, so that teams can innovate with confidence, are key to success. Companies that establish governance structures early will move forward more quickly with confidence, while those that wait may find themselves constrained by risk-averse decision-making.
Agent AI should be a recurring theme on the agenda of every board member, as it provides a competitive advantage today while fostering the resilience companies will need in the future. Encouraging teams to experiment, identify practical use cases, and integrate agent AI into daily operations will help businesses stay ahead of the competition. Organizations that take these steps now, supported by a solid foundation and transparent governance, will set the pace for the future.
Philippe Deblois is the Global Vice President of Solutions Engineering at Dynatrace.
Notice: The opinion presented in this article is the responsibility of its author and not of ABES - Brazilian Association of Software Companies
