AI エージェント時代における専門家の価値維持と多能性人材の需要

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ZDNET's key takeaways

• Polymaths will be in high demand in the age of AI.
• These adaptable professionals will embrace agents.
• They will ally AI skills with deep subject expertise.

Experts recognize that agentic AI is changing the workplace. From the deployment of intelligent assistants to the rise of autonomous businesses, agents are expected to fulfill a range of activities traditionally carried out by professionals.

While there's agreement that agents will have a significant impact on operations, there's less consensus on the role humans will play in the agentic-enabled workplace of the future.

However, what's already clear is that the future of work will require a careful blend of human expertise and AI capabilities, with professionals working effectively and productively alongside their agentic counterparts.

Also: The new enterprise AI expert every company needs - and why

For Gerrit Kazmaier, president of product and technology at Workday, finding the right balance between human and AI agency presents new opportunities. He said earlier this year that agentic AI amplifies workers' strengths, allowing them to function as polymaths.

Experts suggest the term polymath has its roots in Ancient Greek and describes someone who excels in multiple fields.

In the age of agentic AI, as suggested by Workday principal strategist Julie Colwell in a recent blog post, the rise of the polymath is associated with a shift in labor demand away from specialists who know everything about a single domain to professionals with knowledge across multiple disciplines.

Also: How Workday and other software providers plan to survive AI

Kathy Pham, vice president of AI at Workday, also acknowledged the rise of the polymath and told ZDNET that professionals who can work with agents across multiple areas simultaneously will be crucial.

"These are the gaps that we need to fill, and maybe we can then redirect our energy to higher-value areas, because we've now automated the less valuable parts of our working lives that took our time," she said.

So, what will a successful polymath look like? Business leaders told us that two core characteristics will be crucial: adaptability to AI-enabled change and the confidence to make valuable decisions that agents can't.

Embracing agentic change

Chris Kairinos, senior director of global modern workplace technology, client services, and technology operations at A+E Global Media, recognized that the polymath-like capabilities of adaptability and flexibility will be crucial as agents continue to take hold.

"Everybody needs just to embrace technology," he told ZDNET, suggesting that a focus on expertise in one area is being replaced by the aptitude to work across many.

"I don't think you need to master technology, because I don't think there is a way to master it now," continued Kairinos, insinuating the key components of technology-enabled work are likely to change on what feels like an almost constant basis.

Also: The 3 types of people who will excel in the AI agent era, according to tech leaders

Kairinos used the analogy of a musical instrument to explain skills development in the AI era. Rather than learning to play a piano once, professionals must be able to tune their skills to embrace modified instruments quickly and effectively.

"It's as if 30 different keys are being added to a piano. The shape of the piano is changing; there are now three layers of keys on that piano, and there are an extra three pedals," he said.

"If the piano is changing all the time, how are you ever going to become a master? In those conditions, you can't. You've just got to be adaptable enough to be able to use it."

Such is the pace of change with AI, said David Minahan, director of digital, data, and technology at UK charity Young Lives vs. Cancer, that business leaders must create a learning and development strategy that acknowledges the demand for polymath-like capabilities.

Also: AI agents are your new colleagues - how to get the best results

But there's a twist. While tightly defined specialists are out, in-demand polymaths are unlikely to be expected to work across multiple functions.

"I think generalists are too broad," he told ZDNET, referring to the shift. "Specialists aren't required in most businesses anymore because AI leverages knowledge differently. For this reason, I've deliberately taken a strategy to create 'versatilists.'"

As AI completes repetitive and mundane work, Minahan said his versatilists should be comfortable applying their skills across many areas, such as discussions with business stakeholders to identify valuable digital transformation projects.

"I've got that approach in my internal strategy," he said. "Our people are expected to work across the tech stack. And it's a deliberate point: generalists aren't necessary, but versatility is."

Also: 40% of enterprises will scrap AI agents - 3 ways to ensure yours don't fail

Crucially, Minahan said his team can also see the benefits of becoming versatilists.

"There is a history in IT where people get pigeonholed in certain things, and it's difficult for them to move," he said. "So, I've created this language and pathway that means actually, if you're smart, you're motivated, and you're talented, you could do any of these things."

Adding extra value

Ankur Anand, group CIO at recruiter Harvey Nash, also recognized the importance of professional versatility.

Yes, becoming a polymath -- someone who can move beyond traditional role definitions into new areas -- resonates, but in a particular sense: the best professionals will use AI to extend their specific skills rather than becoming generalists across multiple areas.

"Every professional who's actually pulling ahead right now is an expert whose specialism has stretched to include directing, questioning, and correcting AI that works alongside them," he told ZDNET. "That split is different [from] becoming a jack of all trades, and it's a much more useful goal for anyone building a career around this shift."

Also: AI is causing cognitive fatigue. Here's how to work with more haste and less speed

Rather than juggling multiple careers, Anand suggested successful professionals will use AI to boost their current working practices.

The key to success will be whether your expertise is deep enough to know when an agent is making the wrong choices.

He gave the example of technology firm Snowflake, where on an average day, engineers work with multiple agents. One head of engineering spends 20 to 30 hours a week directing five agents, reviewing their design choices, and deciding when code is good enough to ship.

"His deep technical background is exactly what lets him catch the agents when they get something wrong," said Anand. "Someone with only a shallow, general grasp of engineering would have nothing solid enough to check the agents' work against."

Also: Forget productivity: Here are 5 strategic shifts that drive real AI value

As these highly skilled polymaths become the norm, versatility won't just be a core skill for IT professionals.

Minahan said responsibilities in all functions will change as employees work alongside agents.

"For lots of organizations' operational aspects, whether that's in sales, marketing, HR, finance, administration, service delivery, or product creation, you will have an expanse of people possibly in very different job descriptions in a few years as part of a versatile workforce, leveraging tools like AI for specific knowledge and insight," he said.

Anand can see this pattern emerging in his own industry, recruitment. Yes, an AI sourcing tool can scan thousands of candidate profiles against a job spec faster than any person. However, the placements that matter, the senior technical hires and the roles with genuinely scarce skills, still come down to a consultant who's spent years inside one specific market, knowing what skills and experience work best for the hiring manager's needs.

In short, the best polymaths will be the professionals who use their experience to add the valuable human touch that no AI can provide.

"They're the specialists who know a candidate who looks like a moderate match on paper might be the far better fit, while one who ticks every box on the spec sheet would walk out within six months," said Anand.

"That judgment is built from pattern recognition earned over years in a narrow field. No AI tool builds it for you, and no amount of general knowledge substitutes for it."