The recent IDC Spotlight paper on building autonomous agents couldn't have come at a more pivotal moment. We are now flying into 2026, and the race to deploy AI agents has shifted from an experimental novelty to a strategic imperative.
IDC's forecast that by 2028, 1.8 billion agents will be in operation isn't just a number—it's a wake-up call. When the report states that "by 2026, over 60% of enterprises are expected to deploy agentic AI in at least one business function," it confirms what we're seeing across industries. The question is no longer if organizations will adopt autonomous agents, but how quickly they can build and deploy them at scale.
As I speak with technology leaders across industries, two themes consistently emerge as critical success factors for this transition: speed of implementation and robust security frameworks. Let me share some thoughts on why these matter so profoundly.
In today's competitive landscape, implementation speed isn't merely about efficiency—it's about survival. Organizations that can rapidly develop, test, and deploy AI agents will fundamentally outpace those constrained by traditional development timelines. I've observed that enterprises are increasingly frustrated by the typical barriers to AI implementation: lengthy development cycles, overly technical interfaces, lack of transparent pricing, and infrastructure limitations. These aren't just inconveniences—they represent real business opportunities lost to time.
The organizations seeing the greatest success are taking a different approach. They're adopting integrated development environments that compress implementation timelines, allowing them to respond to market changes in near real-time.
At Vertesia, we've built our platform with speed as a foundational principle. When enterprises tell us they need to deploy agents in days, not months, we understand that urgency is directly tied to market advantage. Our low-code platform accelerates development by eliminating the complexity that plagues traditional AI implementation.
The report rightfully emphasizes that "safety, compliance, and risk management are non-negotiable." As AI agents gain more autonomy and access to sensitive systems, security cannot be an afterthought. What makes this particularly challenging is that many organizations still view speed and security as opposing forces. My conversations with CIOs consistently reveal this tension: teams feel pressured to choose between moving quickly or implementing robust protections.
However, leading organizations are adopting architectures where security is embedded throughout the development lifecycle, allowing for both speed and protection. This integrated approach is becoming essential as autonomous agents interact with increasingly sensitive systems and data.
One of the most insightful observations from the IDC report reflects what I'm seeing across the industry: the tool-by-tool approach to AI implementation is creating unsustainable complexity. The initial wave of AI adoption led many organizations to assemble collections of specialized tools. While this approach offered flexibility, it created significant integration challenges and maintenance burdens. Each new AI initiative further compounds this complexity.
Forward-thinking organizations are pivoting toward unified platforms that integrate the entire AI development lifecycle. This approach reduces technical debt while dramatically simplifying governance—critical factors as organizations scale from one agent to dozens or hundreds. As the report states, "Early adopters of unified agent builder platforms will gain significant reductions in cost, complexity, and maintenance."
At Vertesia, our platform approach means everything works together by design. Our API-first architecture ensures seamless integration with existing systems. Our advanced RAG capabilities—with intelligent content preparation and semantic chunking—are built directly into the platform, not bolted on as an afterthought. Our autonomous agent builder provides pre-built tools for everything from parallel workstreams to spreadsheet manipulation, allowing developers to focus on business problems rather than infrastructure.
Perhaps one of the most insightful points in the IDC report is that "47% of enterprises say the generative AI skills gap will delay new product and service development." This talent shortage represents a very real constraint on innovation.
Our response has been to design a platform that expands who can participate in agent development. By creating intuitive, low-code interfaces that empower both technical and business users, we're helping organizations multiply their AI-capable workforce. Domain experts can directly contribute to agent design without waiting for scarce technical resources.
As we look ahead, I'm convinced the organizations that will thrive are those that can rapidly iterate on their agent capabilities. The first wave of deployment is just the beginning—the real advantage comes from continuous improvement.
The IDC report concludes that "those organizations able to rapidly build and deploy agents to automate business processes will gain a competitive advantage." I would add that this advantage compounds over time—each improved process creates space for further innovation, each successful agent deployment builds organizational confidence and capability.
For IT leaders navigating this transformation, the path forward requires both strategic vision and practical execution. Begin by identifying high-value, well-defined processes where agents can deliver immediate impact. Use these initial projects to build organizational capability and confidence. But don't stop there—we recommend choosing a platform as the foundation that will allow you to scale across your enterprise.
The autonomous agent revolution represents one of the most significant shifts in how we conceive of work and business processes. By embracing a unified platform approach that prioritizes both speed and security, organizations can do more than just participate in this revolution—they can lead it.