AI has already entered a new phase. Just under three years ago, Generative AI surprised us with its ability to produce content and its unprecedented speed of adoption. In 2025, Agentic AI represents an even greater leap: autonomous systems capable of reasoning, planning, and executing complex tasks on behalf of people and organizations. That’s why CEOs and business leaders must make it one of their top priorities this year.

The first step is understanding what we’re talking about and why it matters. Unlike traditional assistants, agents don’t just answer questions. They collaborate as virtual partners that understand context, make iterative decisions, access internal or external data, communicate with each other, and learn from experience to improve with every cycle.
This is not a passing trend—it’s a solid shift. In fact, Gartner estimates that by 2028, one-third of all business applications will include Agentic AI capabilities. We’re witnessing the emergence of a new operating model with the potential to reshape entire industries.
What agents can achieve
Practical applications are already visible and demonstrate how agents drive real business outcomes:
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Exponential productivity. By automating repetitive tasks and autonomously resolving time-consuming workflows, agents free up human talent to focus on strategic activities.
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Agility in critical processes. They can validate documents, reconcile invoices, or perform financial verifications in parallel, reducing downtime.
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Accelerated innovation. They autonomously analyze large volumes of data, identify trends, and create virtual prototypes in minutes.
We’re not talking about theoretical definitions here. Numerous use cases are already generating millions in savings, speeding up innovation, and significantly improving customer experience. Now is the time for CEOs and business leaders to explore which of these use cases apply to their organizations—or to develop their own and start realizing the benefits.
Why Agentic AI projects can fail
The potential is huge—but so are the risks. Many implementation attempts get stuck in pilots that never scale. Why does this happen?
One of the main reasons is the lack of solid foundations: without a robust data infrastructure or a rigorous production approach, the necessary context and accuracy for effective operation are missing.
Another key factor is the absence of a clear organizational strategy. Agentic AI doesn’t integrate automatically—it requires a defined roadmap, concrete business objectives, and governance capable of sustaining it over time. Hype alone isn’t enough; adoption must be aligned with business needs.
Cultural resistance should not be underestimated either. Teams may perceive agents as a threat if there isn’t transparent communication explaining their role, supported by training and upskilling programs. Finally, governance introduces another layer of complexity: the autonomy of agents requires new control models, with clear metrics, real-time monitoring, and well-defined accountability to ensure safe and responsible use.
In short, this is a technical, organizational, and cultural challenge.
Can success be ensured?
There are no silver bullets or magic formulas for guaranteeing success in an Agentic AI project—but best practices are beginning to emerge.
One key practice is to build upon the lessons learned from Generative AI—leveraging prior investments in data, security, and models. Another is to foster human-AI collaboration: agents should be seen as partners, not replacements.
Adopting flexibility and continuous learning is also essential, with dynamic processes, contextual playbooks, and rapid improvement cycles. Lastly, governance must be redesigned—with a board-level model that defines objectives, risk thresholds, and ongoing audits.
At Nubiral, we support business leaders throughout this process with a comprehensive approach—helping transform pilots into measurable business results, ensuring every implementation aligns with strategic objectives, has the right infrastructure, and fosters real adoption across the organization.
Conclusions
For CEOs and business leaders, the question is not whether to adopt Agentic AI—but how to do so strategically, responsibly, and effectively.
Organizations that start early, even with limited use cases, will be in a better position to learn, adapt, and scale successfully.
Is your organization ready to begin this journey into the future? We look forward to connecting with you—schedule your meeting today!