Agentic AI’s rise is making the enterprise architect role more fluid

In a previous feature about enterprise architects, gen AI had emerged, but its impact on enterprise technology hadn’t been felt. Today, gen AI has spawned a plethora of agentic AI solutions from the major SaaS providers, and enterprise architecture and the role of enterprise architect is being redrawn. So what do CIOs and their architects need to know?

Organizations, especially their CEOs, have been vocal of the need for AI to improve productivity and bring back growth, and analysts have backed the trend. Gartner, for example, forecasts that 75% of IT work will be completed by human employees using AI over the next five years, which will demand, it says, a proactive approach to identifying new value-creating IT work, like expanding into new markets, creating additional products and services, or adding features that boost margins.

If this radical change in productivity takes place, organizations will need a new plan for business processes and the tech that operates those processes. Recent history shows if organizations don’t adopt new operating models, the benefits of tech investments can’t be achieved.

As a result of agentic AI, processes will change, as well as the software used by the enterprise, and the development and implementation of the technology. Enterprise architects, therefore, are at the forefront of planning and changing the way software is developed, customized, and implemented.

In some quarters of the tech industry, gen AI is seen as a radical change to enterprise software, and to its large, well-known vendors. “To say AI unleashed will destroy the software industry is absurd, as it would require an AI perfection that even the most optimistic couldn’t agree to,” says Diego Lo Giudice, principal analyst at Forrester. Speaking at the One Conference in the fall, Lo Giudice reminded 4,000 business technology leaders that change is taking place, but it’s built on the foundations of recent successes.

“Agile has given better alignment, and DevOps has torn down the wall between developers and operations,” he said. “They’re all trying to do the same thing, reduce the gap between an idea and implementation.” He’s not denying AI will change the development of enterprise software, but like Agile and DevOps, AI will improve the lifecycle of software development and, therefore, the enterprise architecture. The difference is the speed of change. “In the history of development, there’s never been anything like this,” adds Phil Whittaker, AI staff engineer at content management software provider Umbraco.

Complexity and process change

As the software development and customization cycle changes, and agentic applications become commonplace, enterprise architects will need to plan for increased complexity and new business processes. Existing business processes can’t continue if agentic AI is taking on tasks currently done manually by staff.

Again, Lo Giudice adds some levity to a debate that can often become heated, especially in the wake of major redundancies by AI leaders such as AWS. “The view that everyone will get a bot that helps them do their job is naïve,” he said at the One Conference. “Organizations will need to carry out a thorough analysis of roles and business processes to ensure they spend money and resources on deploying the right agents to the right tasks. Failure to do so will lead to agentic technology being deployed that’s not needed, can’t cope with complex tasks, and increases the cloud costs of the business.

“It’s easy to build an agent that has access to really important information,” says Tiago Azevedo, CIO for AI-powered low-code platform provider OutSystems. “You need segregation of data. When you publish an agent, you need to be able to control it, and there’ll be many agents, so costs will grow.”

The big difference, though, is deterministic and non-deterministic, says Whittaker. So non-deterministic requires guardrails of deterministic agents that produce the same output every time over the more random outcomes of non-deterministic agents. Defining business outcomes by deterministic and non-deterministic is a clear role for enterprise architecture. He adds that this is where AI can help organizations fill in gaps. Whittaker, who’s been an enterprise architect, says it’ll be vital for organizations to experiment with AI to see how it can benefit their architecture and, ultimately, business outcomes.

“The path to greatness lies not in chasing hype or dismissing AI’s potential, but in finding the golden middle ground where value is truly captured,” write Gartner analysts Daryl Plummer and Alicia Mullery. “AI’s promise is undeniable, but realizing its full value is far from guaranteed. Our research reveals the sobering odds that only one in five AI initiatives achieve ROI, and just one in 50 deliver true transformation.” Further research also finds just 32% of employees trust the organization’s leadership to drive transformation. “Agents bring an additional component of complexity to architecture that makes the role so relevant,” Azevedo adds.

In the past, enterprise architects were focused on frameworks. Whittaker points out that new technology models will need to be understood and deployed by architects to manage an enterprise that comprises employees, applications, databases, and agentic AI. He cites MCP as one as it provides a standard way to connect AI models to data sources, and simplifies the current tangle of bespoke integrations and RAG implementations. AI will also help architects with this new complexity. “There are tools for planning, requirements, creating epics, user stories, code generation, documenting code, and translating it,” added Lo Giudice.

New responsibilities

Agentic AI is now a core feature of every major EA tool, says Stéphane Vanrechem, senior analyst at Forrester. “These agents automate data validation, capability mapping, and artifact creation, freeing architects to focus on strategy and transformation.” He cites the technology of Celonis, SAP Signavio, and ServiceNow for their agentic integrations. Whittaker adds that the enterprise architect has become an important human in the loop to protect the organization and be responsible for the decisions and outcomes that agentic AI delivers.

Although some enterprise architects will see this as a collapse of their specialization, Whittaker thinks it broadens the scope of the role and makes them more T-shaped. “I can go deep in different areas,” he says. “Pigeon-holing people is never a great thing to do.”

Traditionally, architecture has suggested that something is planned, built, and then exists. The rise of agentic AI in the enterprise means the role of the enterprise architect is becoming more fluid as they continue to design and oversee construction. But the role will also involve continual monitoring and adjustment to the plan. Some call this orchestration, or perhaps it’s akin to map reading. An enterprise architect may plan a route, but other factors will alter the course. And just like weather or a fallen tree, which can lead to a route deviation, so too will enterprise architects plan and then lead when business conditions change.

Again, this new way of being an enterprise architect will be impacted by technology. Lo Guidice believes there’ll be increased automation, and Azevedo sides with the orchestration view, saying agents are built and a catalogue of them is created across the organization, which is an opportunity for enterprise architects and CIOs to be orchestrators.

Whatever the job title, Whittaker says enterprise architecture is more important than ever. “More people will become enterprise architects as more software is written by AI,” he says. “Then it’s an architectural role to coordinate and conduct the agents in front of you.” He argues that as technologists allow agents and AI to do the development work for them, the responsibility of architecting how agents and processes function broadens and becomes the responsibility of many more technologists.

“AI can create code for you, but it’s your responsibility to make sure it’s secure,” he adds. Rather than developing the code, technology teams will become architecture teams, checking and accepting the technology that AI has developed, and then managing its deployment into the business processes.

With shadow AI already embedded in organizations, Whittaker’s view shows the need for a team of enterprise architects that can help business align with the AI agents they’ve deployed, and at the same time protect customer data and cybersecurity posture.

AI agents are redrawing the enterprise, and at the same time replanning the role of enterprise architects.