Gartner’s best case scenario projection predicts that agentic AI could drive approximately 30% of enterprise application software revenue by 2035, surpassing $450 billion, up from 2% in 2025.
Gartner sees five stages of Agentic AI evolution
This diagram needs some explanation - here's my understanding from Gartner's press release in August 2025.
Stage 1: AI Assistant
| Gartner's prediction | By the end of 2025 most enterprise applications will have embedded assistants. |
| Gartner's explanation | They simplify tasks and interactions for users but depend on human input and do not operate independently. |
| Arthur's interpretation | Perhaps the application interface permits a user to type in an instruction into a bot interface and the app responds, rather than clicking through multiple pages eg 'Show me an exception report for all grocery orders received since 5pm yesterday.' |
| Arthur's assessment | 'Most'?? This definitely didn't happen! Perhaps 10% by the end of 2026?? |
Stage 2: Task-Specific Agent Applications
| Gartner's prediction | Up to 40% of enterprise applications will include integrated task-specific agents by 2026, up from less than 5% today. |
| Gartner's explanation |
These AI agents have the capacity to operate and perform complex,
end-to-end tasks. An example is an AI-driven cybersecurity threat response agent that scans network traffic, system logs and user behavior patterns in real time. The agent then assesses and initiates a response as appropriate. |
| Arthur's interpretation |
Applications (perhaps from a single vendor?) can perform multi-step operations autonomously. What's the difference from today? Applications can follow a rules-defined process flow today. I think the new shiny thing is that the app can use AI to determine the process flow?? |
| Arthur's assessment | Perhaps 10% by the end of 2026?? And it's likely that it is the
same 10% as have achieved Stage 1. |
Stage 3: Collaborative AI Agents Within an Application
| Gartner's prediction | By 2027, Gartner predicts one-third of agentic AI implementations will combine agents with different skills to manage complex tasks within application and data environments. |
| Gartner's explanation |
Collaborative agents will offer more adaptable and scalable solutions by learning from real-time data and adjusting to new conditions. |
| Arthur's interpretation |
Some predictive or forecasting capabilities that use Machine Learning |
| Arthur's assessment | Err, I think this is an inevitable benefit from Stage 2 implementation?? |
Stage 4: AI Agent Ecosystems Across Applications
| Gartner's prediction | By 2028, AI agent ecosystems will enable networks of specialized agents to dynamically collaborate across multiple applications and multiple business functions, allowing users to achieve goals without interacting with each application individually. |
| Gartner's explanation |
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| Arthur's interpretation |
There will be an approved list of AI Agents (from multiple
vendors) that are permitted to collaborate together. Most likely I
envisage a marketplace where vendors list their agents and their
capabilities and customers pick and choose which can Apps can play
together and in what circumstances. |
| Arthur's assessment | Actually, I think there will be a completely new breed of
ecosystems that are native agentic AI first. (Indeed as a founding
member of the management team at Fetch.AI, I would say that
these ecosystems exist already.) Here's an announcement about the formation of the Agentic AI Foundation (AAIF) in December 2025 to do just that: Here's TechCrunch's description: Anthropic is donating its MCP (Model Context Protocol), a standard way to connect models and agents to tools and data; Block is contributing Goose, its open source agent framework; and OpenAI is bringing AGENTS.md to the table, its simple instruction file developers can add to a repository to tell AI coding tools how to behave. You can think of these tools as the basic plumbing of the agent era.The key question is how will successful will this new approach be and how will existing Enterprise Software providers respond? Students of disruptive innovation theory (like me!) are watching with great interest! |
Stage 5: The “New Normal” for Democratized Enterprise Apps
| Gartner's prediction | Gartner predicts that by 2029, at least 50% of knowledge workers
will develop new skills to work with, govern or create AI agents on
demand for complex tasks. |
| Gartner's explanation |
As agentic AI matures, standardized protocols and frameworks will
enable seamless interoperability, allowing agents to sense their
environments, orchestrate projects and support a wide range of
business scenarios Agents will be created on the fly by humans and humans and AI will collaborate in new ways. |
| Arthur's interpretation |
I'm not sure what to think about this: I do think that
most knowledge workers will use an AI agents to help them with
complex tasks on a one-off basis. Whether many enterprise employees will enable an AI agent to exist permanently to achieve an objective (an objective that goes beyond improving their personal productivity) I struggle with for reasons of control, security, liability, cost. As a result, I think creating enterprise AI agents will be a specialist role within an enterprise. |
| Arthur's assessment | Nope, I don't think that this will happen in the way that Gartner articulates. |
