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ZDNET’s key takeaways
- The autonomous business means new roles and requirements.
- Skilled tech professionals will help ensure agents are integrated.
- But course correctors and business collaborators hold the key.
AI is supporting the rise of the autonomous business, where some of the roles we take for granted today — from basic operational tasks to decision-making responsibilities — are fulfilled by agents that can discover, negotiate, and transact.
There’s widespread fear that this age of autonomy will mean less work for professionals, particularly in IT departments. However, as we saw recently, the future of work will require a careful blend of human expertise and AI capabilities, where professionals work effectively and productively with their agentic counterparts.
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So, what skills will help you excel in the agentic workplace of the future? The experts suggested that three types of professionals will be crucial: tech-savvy enablers, agentic course-correctors, and outcome-focused collaborators.
1. Tech-savvy enablers
While there’s great focus on agents working autonomously, Alex Read, senior enterprise product manager for data at energy provider EDF UK, recognized that making the most of AI requires strong in-house technical capabilities.
Read’s data team helps over 1,000 users across the business exploit agentic AI. His team sits at the core of a federated hub-and-spoke model, where data and digital professionals focus on technological enablement and business units concentrate on generating value.
“Context is king for AI,” he told ZDNET. “The role that we see our engineers performing with agentic and AI-assisted experiences is that they need a high skill base to build the surrounding capabilities that interact with these services.”
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His team uses Snowflake technologies, such as Semantic Tables and Horizon Data Catalogs, to define data assets and make them understandable to AI agents. The team then builds capabilities using Snowflake’s coding agent CoCo on top of its data platform.
One example is a tool that helps service center staff manage customer queries. His team has developed an agent using CoCo that pulls information from the Snowflake data platform and presents insights in the staff’s Slack messaging user interface.
“The engineer is performing the role of taking something that a tool like CoCo is producing, and then slightly enhancing it further, or maybe tailoring it to make it more accurate,” he said.
Sameer Vuyyuru, chief AI and product officer at Capita, is another digital leader exploring how his organization can exploit agentic technologies — and skilled professionals play a specific role in this process, too.
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Capita has built an AI Catalyst Stack that focuses on process observability and establishes how workflow automations can produce operational efficiencies.
Vuyyuru told ZDNET that these explorations led him to conclude that professionals must hone their technical capabilities now and find ways to think about how they blend their expertise with agentic tools to create next-generation services that produce business value.
“Start working with AI every day,” he said. “When we look at our thousands of employees, we’ve made a significant investment in giving every one of them access to AI tools. And the ones that have adopted AI, which is the vast majority, to my surprise, love it and use it daily.”
2. Agentic course correctors
However, while professionals can boost their productivity by using emerging technologies, agentic AI can’t be allowed to work in splendid isolation.
EDF’s Read said the best IT professionals work with subject matter experts with deep knowledge across the business to ensure agents work effectively.
“While I talk glowingly about tools like CoCo and Semantic Tables, we’ve still got the main experts out in the organization who’ve got 20 or 30 years of energy industry knowledge,” he said.
“Success is about applying that expert knowledge to help AI agents be more productive and accurate. Then, when there are technical challenges or maybe inaccuracies, you need someone who understands the technical and domain capability to course correct.”
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That sentiment was echoed by Stephen Wood, chief operating officer at Rathbones Asset Management, who told ZDNET that professionals in the agentic age — whether in the IT department or business functions — will need to shift toward a new way of working.
Gone are the messy, ad hoc structures of the traditional office where people work on tasks and strive to achieve project goals. In their place is a new series of relationships in which professionals oversee their agentic colleagues.
“If you look at the way humans work today, and the way that they work together, it’s not always that clean,” he said, referring to the complex nature of collaborative work processes.
“Now, what we really want is a world where we’ve got experts who know their stuff, they’re the humans in the loop, and they are the final oversight, the check-off.”
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Wood said that kind of oversight is a natural element in his highly governed and process-oriented business. However, he recognized that the transformation to an agentic workplace will present significant challenges for everyone.
“It’s going to be a very different way of doing things,” he said. “So, there’s going to be some friction, right? But the businesses and the people that survive are going to be the ones that embrace agentic AI, understand it, and want to drive it to the next level.”
3. Outcome-focused collaborators
Recognizing the potential power of AI is just the starting point. A strong sense of the long-term business objective is critical to embracing agents. Dan Cherowbrier, CTO at Formula E, said professionals with this sense of direction will excel.
“In my view, it’s someone who can clearly understand the outcome that they want to achieve,” he said, noting that people who hold these skills will help their organizations generate economic value from AI.
“The unsuccessful companies will be companies that take their existing processes built around humans, departments, and silos, and try to build agents to achieve their existing processes rather than achieve their desired business outcomes.”
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Cherowbrier gave ZDNET the example of software development, in which agentic AI has transformed traditional practices. Talented engineers focus their expertise on the beginning of the development process, pointing agents in the right direction rather than waiting until later in the process.
“If you think about that outcome in terms of writing an application, it used to be that the expertise came in last — the coding at the end, and the testing to an extent,” he said.
“Now with agents, that expertise needs to be at the front end in defining your requirements. If you can’t understand what you need to do from the outset, then I think you will struggle.”
Murali Swaminathan, CTO at technology specialist Freshworks, also focused on the importance of clearly defined business objectives.
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He suggested to ZDNET that skilled professionals ensure agents deliver the right outcomes before applying the technology to business processes.
“Make sure it’s really working, repeatable, and then turn the technology on,” he said. “Instead of trying to turn everything on and realizing that it’s not working, you should try a few things, get it right, build confidence and trust, and then roll the service out to everybody.”
Agents, therefore, will need careful guidance. And the good news for professionals, said Louise Newbury-Smith, head of UK&I at technology specialist Zoom, is that achieving tried-and-tested goals through the application of agentic technology will be very much a human-centered process.
“You’ve got to put yourself into your work,” she told ZDNET. “You’ve got to give something personally to whatever activities you’re doing and the goals that you’re looking to achieve. That’s about AI empowering, not replacing, the human. That approach, for me, is how everyone stays relevant and creates the future.”
