For decades, businesses prized expertise. Engineers coded, analysts crunched numbers, writers crafted content – each “specialist” quietly optimising a slice of the workflow. But as generative AI and software agents mature, this model is breaking down. Today 56% of workers already use AI in their jobs , and many expect fundamental shifts: 58% believe their skill sets will change dramatically in the next five years . In other words, the old balance of deep “plugs-and-play” experts may no longer be enough. We’re at a point of curiosity: can generalists – people with broad, adaptable skills – gain the upper hand when AI can do so much of the specialist work?

GenAI is Democratising Expertise

Generative AI is rapidly lowering barriers to expertise. In practice, this means a marketer with no coding bootcamp can generate bug-free code via an AI like Claude Code, and a non-designer can produce professional graphics using tools like Canva and Jasper. Even data analysis is shifting: AI-augmented tools (e.g. Tableau with AI or Power BI) turn raw numbers into insights for business users without data science degrees. In short, many specialist jobs are becoming “AI-exposed,” enabling a single worker – often a generalist – to wear multiple hats.

• Code by non-coders: Platforms like Anthropic’s Claude Code let anyone describe the program they want and get production-ready code snippets.
• Design by non-designers: AI-driven apps (e.g. Canva, Jasper) empower team members to craft marketing designs or blog posts without expert training.
• Data by non-analysts: Business intelligence tools with AI turn complex datasets into dashboards and suggestions, so managers can make data-driven decisions without deep statistical expertise.

This isn’t just hype. PwC notes that generative AI “can be operated using simple everyday language with no technical skills required,” turning knowledge work into something akin to conversation . As generative tools handle more routine tasks, human employees effectively merge specialist duties into their broader roles. The result: a growing premium on who can connect the dots, not just what technical skills they have.

Enter the AI-Augmented Generalist

What does this shift look like in practice? Thought leaders predict a new “ultra-generalist” role. These are people who oversee teams of both humans and AI agents, coordinating complex workflows. For example, imagine an AI recruiting agent that not only scans resumes but also schedules interviews, largely autonomously . In that world, the valuable human is not the resume-screening specialist, but the generalist who manages the human+AI hiring process end-to-end. As one expert writes, these “jack- of-all-trades” generalists will become uniquely capable of running hybrid teams – and thus increasingly valuable .

At the macro level, the numbers are striking. Cognizant predicts 90% of jobs will be affected by GenAI in the next decade . A Cisco/Accenture report echoes this, noting that entry- and mid-level tech roles are on the front lines of AI transformation, with many jobs redefining what skills matter . By contrast, pure specialists – even highly trained AI engineers – may see only parts of their work change. PwC data shows AI-specialist roles still command a wage premium , but it also stresses that most workers using AI don’t have those specialist skills. If generative models can automate coding, analysis and writing, does hiring five experts still make sense?

Implications for HR and Leaders

So what should HR and business leaders do with these trends? First, recognise that learning agility now trumps static expertise. As Alida Miranda-Wolff argues, “The one skill that will matter most in the AI age is the ability to learn.” New hires should be curious, tech-savvy generalists as much as they are qualified specialists. Deloitte’s survey found young workers embracing AI as a basic tool – “I don’t think this genie can be put back in the bottle,” said one analyst of GenAI. “Either you get used to working with AI or you get left behind.” In practice, that means valuing resumes that show breadth: cross-functional projects, evidence of rapid upskilling, or collaborative problem-solving across domains.

Second, invest in AI partnerships training. The future workforce will include digital agents and copilot tools everywhere. Encourage teams to co-train with AI (prompt-engineering skills, AI literacy) so specialists can focus on innovation and oversight while generalists coordinate the bigger picture. For example, an HR leader might rely on an AI assistant to triage resumes and surface candidate insights, but still needs a human to make judgment calls on culture-fit. In the same vein, IT specialists should shift towards architecting AI workflows, while hybrid teams lead execution. As Survis notes, Generative AI will “democratise specialised skills,” letting any adaptive worker tap into them . Leaders should hire for that adaptability and ensure their talent management reflects AI fluency (see also WEF’s call for AI and data literacy).

Finally, don’t lose sight of the specialists – but reframe their roles. Specialists (in AI, cybersecurity, legal, etc.) will still be essential, but increasingly in strategic and advisory capacities. With GenAI automating routine analysis, experts will pivot to oversight, ethical judgment, and complex problem- solving . Pay structures may also shift: one forecast even predicts that “salaries will be based on the breadth of the generalist’s skill set,” with generalists eventually earning as much or more than specialists at the same level . While such transitions take time, the direction is clear.

In sum, the balance between specialists and generalists is tilting. As AI agents take on more discrete tasks, companies will prize those who see systems, connect functions and keep learning – the very essence of a generalist mindset. The evidence is mounting: disruption rewards curiosity and adaptability.

HR and business leaders should ask not just “Can this candidate do the job?” but “Can this candidate adapt to AI-powered work?” Looking ahead, the most future-proof teams will likely be composed of interdisciplinary thinkers empowered by AI, rather than specialists standing alone.

 

---

 

Sources: Recent industry research and expert analyses have shaped these insights . Each citation above points to a study or article supporting the claims made.

1. How AI is changing the definition of work- Fast Companyhttps://www.fastcompany.com/91210851/bots-agents-and-digital-workers-ai-is-changing-the-very-definition-of-work
2. Investor Relations – AI and the Workforce: Industry Report Calls for Reskilling and Upskilling as 92 Percent of Technology Roles Evolve – Ciscohttps://investor.cisco.com/news/news-details/2024/AI-and-the-Workforce-Industry-Report-Calls-for-Reskilling-and-Upskilling- as-92-Percent-of-Technology-Roles-Evolve/default.aspx
3. Everybody Now Has Range: How Generative AI Democratizes Specialized Skillshttps://www.linkedin.com/pulse/everybody-now-has-range-how-generative-ai-specialized-gary-survis-epbze
4. AI agents and the future: The rise of ultra-generalists – SmartBriefhttps://www.smartbrief.com/original/ai-agents-and-the-future-the-rise-of-ultra-generalists
5. PwC’s 2024 AI Jobs Barometerhttps://www.pwc.com/hu/hu/sajtoszoba/assets/ai_jobs_barometer_2024.pdf
6. Generalists or specialists: who do employers value more? | World Economic Forumhttps://www.weforum.org/stories/2016/06/generalists-or-specialists-who-gets-hired/
7. What will the impact of gen AI on the workforce be? | Cognizanthttps://www.cognizant.com/us/en/aem-i/impact-of-gen-ai-on-the-workforce
8. Forget Specialists Vs. Generalists — Hire Learners | by Alida Miranda-Wolff | Mediumhttps://alidamw.medium.com/forget-specialists-vs-generalists-hire-learners-e871b3389f3e
9. Entry level jobs reskilling for AI | Deloitte Insightshttps://www2.deloitte.com/us/en/insights/topics/talent/ai-in-the-workplace.html
10. The bright future of generalists in the workplacehttps://www.zendesk.com/blog/bright-future-generalists-workplace/