Agentic AI Set to Reshape 40% of Enterprise Applications by 2026, new research finds

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As the Middle East accelerates its journey toward knowledge-based, AI-powered economies, enterprises across the region are at a crucial turning point in how they deploy technology. National initiatives like Saudi Vision 2030, the UAE’s National AI Strategy, and Qatar’s AI roadmap are pushing organizations beyond basic automation into the next frontier: autonomous, intelligent systems that collaborate, adapt, and scale on their own.

Against this backdrop, new research from Gartner Inc. points to a major shift in the enterprise software landscape. The firm forecasts that by 2026, 40% of enterprise applications will be integrated with task-specific AI agents, up from less than 5% today.

This trend signals a departure from individual productivity tools toward agentic AI systems capable of driving collaborative workflows and making autonomous decisions. Gartner believes that these capabilities will not only improve operations but also reshape how enterprises structure teams, manage data, and deliver services. The report estimates that agentic AI will account for nearly 30% of enterprise application software revenue by 2035, surpassing $450 billion, compared to just 2% in 2025.

According to Anushree Verma, Senior Director Analyst at Gartner, “AI agents are evolving rapidly, progressing from basic assistants embedded in enterprise applications today to task-specific agents by 2026 and ultimately multiagent ecosystems by 2029.” She added that this transformation will reposition enterprise applications from tools that support individual productivity to platforms that enable “seamless autonomous collaboration and dynamic workflow orchestration.”

A Critical 6-Month Window for CIOs

For enterprise technology leaders, the urgency is clear. Gartner emphasizes a three- to six-month window in which CIOs must define their strategy for agentic AI adoption. With the technology landscape nearing a tipping point, delaying action could leave organizations struggling to keep pace with early adopters.

Gartner outlines a five-stage evolution for agentic AI in enterprise applications, providing a strategic framework for organizations to follow as they scale their AI maturity.

AI Assistants for Every Application

By the end of 2025, almost every enterprise application is expected to have some form of embedded AI assistant. These assistants simplify tasks, enhance user interaction, and improve operational efficiency. However, they are not truly autonomous, as they still rely heavily on human input.

Verma warned that many organizations confuse AI assistants with full-fledged AI agents, a misconception she refers to as “agentwashing.” She explained, “AI assistants are the precursor to agentic AI. They simplify tasks and interactions for users but depend on human input and do not operate independently.”

To unlock the full potential of these tools, she noted that CIOs must prioritize integration via robust APIs. “Technology leaders must focus on creating seamless employee experiences by integrating AI assistants with robust APIs, enabling a shift from traditional application-centric interfaces,” Verma said.

Rise of Task-Specific Agents by 2026

The transition from assistants to agents will take shape in 2026, when Gartner predicts that 40% of enterprise applications will feature task-specialized AI agents. These agents will be capable of executing tasks, from routine development to complex incident response with minimal or no human involvement.

“As AI agents begin acting independently,” Verma explained, “leaders must ensure strong security and governance frameworks are in place.”

Multi-Agent Collaboration Within Applications

By 2027, enterprises will begin to see AI agents collaborate within single applications. Gartner expects that one-third of agentic AI implementations at this stage will involve multiple agents with different skills coordinating to manage complex workflows and data environments.

While today’s agents tend to be narrowly focused, collaborative agents will be more adaptable, continuously learning from real-time data and adjusting to changing conditions. To enable this kind of intelligent teamwork, Verma said that CIOs will need to “prioritize standardization and interoperability and adopt protocols that support seamless agent-to-agent communication.”

Cross-Application AI Ecosystems

Looking ahead to 2028, AI agents will begin to operate across application boundaries, dynamically collaborating to complete tasks without requiring users to interact with each application individually. This will create decentralized networks of intelligent agents capable of managing end-to-end business processes autonomously.

This transformation will also bring about significant implications for business models, requiring more transparent governance, dynamic pricing strategies, and stronger ethical oversight. Gartner estimates that by this point, a third of enterprise user experiences will move from traditional application interfaces to agentic front ends.

The Agentic “New Normal”

By 2029, agentic AI is expected to become a core part of enterprise operations. Gartner projects that at least 50% of knowledge workers will develop new skills to work with, govern, and even create AI agents on demand for complex workflows.

“As agentic AI matures,” said Verma, “standardized protocols and frameworks will enable seamless interoperability, allowing agents to sense their environments, orchestrate projects and support a wide range of business scenarios.” She added that “early adopters will set the standard for the new normal while others risk falling behind as humans begin relying on AI agents as much as their smartphones.”

Implications for the Middle East

For organizations across the Middle East, the Gartner findings offer both a challenge and an opportunity. As governments in the region prioritize AI as a strategic national asset, enterprises that embrace agentic AI early could position themselves as leaders in the next wave of digital transformation.

With the right investments in governance, infrastructure, and talent, businesses can leverage agentic AI not just to optimize internal operations, but to redefine customer experiences, launch new services, and drive regional competitiveness in the global digital economy.