Report highlights rapid enterprise adoption of agentic AI while exposing critical gaps in governance, architecture, and risk control
OutSystems has released its global 2026 State of AI Development report, offering a comprehensive view into how enterprises are adopting and scaling artificial intelligence across their operations. The findings reveal a decisive turning point: organizations have moved beyond experimentation and are now deploying AI—particularly agentic AI—into production environments at scale. However, this rapid adoption is also introducing new layers of complexity, especially around governance, system architecture, and risk management.
The report indicates that 96% of surveyed enterprises are already using AI agents in some capacity, while an even higher percentage—97%—are actively exploring broader, system-wide agentic AI strategies. This level of adoption underscores a fundamental shift in enterprise technology strategy, where AI is no longer treated as an isolated innovation initiative but as a core component of operational infrastructure.
Agentic AI represents a significant evolution from earlier forms of artificial intelligence. Unlike traditional AI systems that primarily provide insights or recommendations, agentic AI systems are designed to autonomously execute workflows, make decisions, and adapt dynamically to changing conditions. These capabilities enable organizations to automate complex processes, reduce manual intervention, and improve responsiveness across a wide range of business functions.
The transition from pilot projects to full-scale deployment reflects growing confidence in the technology’s ability to deliver measurable business outcomes. Enterprises are increasingly embedding AI agents into mission-critical operations, from software development and IT management to customer service and financial processes. This shift is aligned with broader industry projections, including forecasts from Gartner, which suggest that by the end of 2026, 40% of enterprise applications will incorporate task-specific AI agents.
Despite this momentum, the report highlights a critical challenge: governance is struggling to keep pace with adoption. A striking 94% of organizations surveyed expressed concern about “AI sprawl”—the uncontrolled proliferation of AI tools, models, and agents across different teams and environments. This fragmentation is contributing to increased technical debt, operational complexity, and potential security vulnerabilities.
One of the underlying issues is the lack of centralized governance frameworks. While AI agents are being deployed across organizations, only a small proportion of enterprises have established unified strategies for managing them. As a result, many organizations are operating in fragmented environments where different teams adopt different tools, standards, and practices. This decentralization makes it difficult to ensure consistency, maintain security, and scale AI initiatives effectively.
The experience of McConkey Auction Group illustrates how some organizations are approaching this challenge. According to Scott Finkle, Vice President of Technology, the company began its AI journey with a focused, well-defined project aimed at delivering tangible business impact. This incremental approach allowed the organization to build internal capabilities and confidence before scaling its AI initiatives more broadly. By leveraging OutSystems’ Agent Workbench, McConkey Auction Group has been able to iterate on its implementations and develop a foundation for future AI-driven innovation.
The report also provides insights into the maturity of agentic AI adoption across different regions and industries. Countries such as Australia, Brazil, Germany, the Netherlands, the United Kingdom, and the United States are generally in intermediate stages of adoption, with many organizations actively deploying AI in production environments. In contrast, France is still in the earlier phases of its adoption journey.
Industry-wise, financial services and technology sectors are leading the way, driven by their need for advanced automation, data-driven decision-making, and regulatory compliance. These sectors are particularly well-suited to benefit from agentic AI, given the complexity and scale of their operations.
The impact of agentic AI is most pronounced in IT and software development functions, where efficiency gains and time-to-value can be directly measured. According to the report, 31% of organizations now consider AI to be integral to their development practices, while an additional 42% have embedded AI into specific stages of the software development lifecycle. These stages include coding, testing, deployment, and maintenance, where AI agents can automate repetitive tasks and provide real-time insights.
As organizations gain confidence in these systems, many are adopting a “human-on-the-loop” model. In this approach, AI agents operate with a degree of autonomy, executing tasks and making decisions independently, while human supervisors provide oversight and intervene when necessary. Currently, 52% of organizations report using this model, reflecting a shift toward more autonomous systems that still maintain a layer of human control.
Woodson Martin, Chief Executive Officer of OutSystems, emphasized that the convergence of software development and AI is reshaping how organizations build and deploy technology. He noted that the distinction between building software and building AI systems is rapidly disappearing, as modern applications increasingly incorporate intelligent, autonomous components.
According to Martin, the next phase of enterprise AI will involve the development of “systems of agents”—interconnected networks of AI agents that collaborate to perform complex tasks. While this approach offers significant potential for productivity gains, it also introduces new challenges in terms of coordination, architecture, and governance. Organizations must therefore invest in robust frameworks that can manage these systems effectively and ensure their reliability and security.
Architectural fragmentation remains a significant barrier to achieving this vision. The report found that 38% of organizations are using a mix of custom-built and pre-built AI agents, resulting in heterogeneous technology stacks that are difficult to standardize. This lack of standardization complicates integration efforts and increases the risk of inconsistencies and vulnerabilities.
Only 12% of organizations have implemented centralized platforms to manage their AI ecosystems, highlighting a substantial gap between adoption and governance. Most enterprises are still experimenting with different approaches, often varying by team, department, or geographic region. This experimental phase, while necessary for innovation, can lead to inefficiencies and challenges in scaling successful initiatives.
To address these issues, OutSystems has introduced a new framework known as Agentic Systems Engineering. This approach is designed to provide organizations with the tools and methodologies needed to build, manage, and evolve AI systems in a controlled and governed manner. By establishing standardized processes and architectures, the framework aims to reduce fragmentation and enable more consistent, secure deployments.
The report’s findings underscore the importance of balancing innovation with control. While the rapid adoption of agentic AI is driving significant benefits, including increased efficiency and improved decision-making, it also requires organizations to rethink their approach to governance, architecture, and risk management.
The survey methodology behind the report adds further credibility to its insights. OutSystems commissioned an independent third party to survey nearly 1,900 IT leaders across multiple regions, capturing a diverse range of perspectives on AI adoption. The survey, conducted between December 2025 and January 2026, examined not only adoption levels but also use cases, development approaches, and the challenges organizations face as they transition from pilot projects to full-scale deployment.
In conclusion, the 2026 State of AI Development report highlights a pivotal moment in the evolution of enterprise technology. Agentic AI is rapidly becoming mainstream, transforming how organizations operate and compete. However, the accompanying rise in AI sprawl and governance challenges indicates that the journey is far from complete. To fully realize the potential of AI, enterprises must develop cohesive strategies that integrate innovation with robust oversight, ensuring that their AI systems are not only powerful but also manageable, secure, and aligned with business objectives.
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