According to a new Gartner study, 40% of enterprise applications are expected to feature task-specific artificial intelligence agents by 2026, with a significant increase from below 5% today.
This research outlines the evolution of agent AI in an enterprise environment, and as organizations speed up their digital transformation efforts, AI agents begin to increase individual productivity and restructure collaboration and workflow efficiencies. The findings emphasize that advances in talent interactions will set new standards for how teams work and systems are organized within the enterprise.
Rapid evolution
“AI agents have evolved from basic assistants embedded in today's enterprise applications to task-specific agents by 2026 and by 2029 into a multi-agent ecosystem,” said Anushree Verma, senior director analyst at Gartner.
The organization is currently at an inflection point in the development and deployment of agent AI. Gartner advises that Chief Information Officers are behind or have a major 3-6 month window to establish risk, or to establish risk, with a Chief Information Officer behind the peers who accept new agent AI capabilities early. This report suggests a focused approach across five stages of frameworks in the evolution of agent AI in enterprise settings.
Agent AI stage
The first stage will be characterized by AI assistants embedded in almost every enterprise application by the end of 2025. These assistants can help you translate previous inefficient applications into systems that automate tasks on behalf of users. However, these assistants still require human input and do not work independently. Gartner warns that the distinction between AI assistants and agents is often attributed to part of what is called “agent washing.”
Verma states, “CIOs and technology leaders need to focus on creating seamless employee experiences by integrating robust APIs with their AI assistants and enabling them to migrate from traditional, application-centric interfaces.”
By 2026, Gartner predicts that AI assistants will develop into agents with special task capabilities. At this stage, it is expected that 40% of enterprise applications will be integrated with these task specialty agents.
“As AI agents begin to act independently and begin handling tasks ranging from routine development to complex incident response without human involvement, leaders need to ensure strong security and governance,” Verma said.
Joint Agent
The third stage expected by 2027 will include joint AI agents running within the same application. Gartner predicts that one-third of current Agent AI implementations will consist of agents with different skill sets that collectively manage complex tasks in their application and data environments. While the industry is currently focusing on single purpose automation, Gartner expects a major impact on business from collaborative agents who can learn from data in real time and adapt as the situation evolves.
At this stage, Gartner emphasizes that technology leaders should consider adopting protocols that promote standardization, interoperability, and agent-to-agent communication.
Ecosystems and new business models
By 2028, the fourth stage will predict a network of specialized AI agents that can collaborate dynamically across different applications, allowing users to achieve their goals without interacting directly with each software. Gartner suggests that this could lead to changes in business models, increased transparency requirements, new pricing structures, and further emphasis on ethical standards and governance.
By 2028, Gartner estimates that a third of the user experience will move from using native applications to interacting with the agent's frontend. This is predicted to require a whole new business model to address the potential intermediation caused by these changes.
New normal
The fifth final stage, forecast for 2029, predicts that at least half of knowledge workers have acquired the new skills needed to create AI agents that can handle complex workflows in demand.
Verma states, “As agent AI matures, standardized protocols and frameworks allow seamless interoperability, allowing agents to sense the environment, coordinate projects, and support a wide range of business scenarios.
Gartner's analysis suggests that as agent AI is immersed in enterprise software and operations, organizations face new challenges and opportunities, particularly in terms of governance, security, and interoperability. Companies that deal with these areas quickly may be better positioned in an ever-growing environment where reliance on autonomous AI agents is continuing to grow.
