Generative AI is reshaping the way businesses assess professional skills, experience and knowledge. As AI tools become more capable of producing reports, analysing information and assisting with complex tasks, companies are reconsidering which human abilities create the greatest value.
The shift is moving beyond automation. Businesses are increasingly exploring how AI can help employees perform unfamiliar tasks, improve productivity and make better decisions. However, the technology also raises questions about whether traditional qualifications and years of experience will remain reliable indicators of professional ability.
A March 2025 analysis published by Harvard Business Review examined how generative AI could change hiring practices, career development and the value employers place on technical skills. More recently, research published in October 2026 has added evidence that AI can temporarily improve workers’ ability to perform tasks outside their existing expertise.
Workplace Adoption Accelerates as AI Capabilities Expand
The growing use of generative AI is increasing pressure on businesses to reconsider how work gets done.
According to Stanford University’s 2026 AI Index Report, 88 percent of surveyed organizations reported using AI in at least one business function during 2025. Additionally, 79 percent reported regular generative AI use in at least one business function.
These figures highlight how quickly AI has entered mainstream business operations. Technology insights now increasingly focus on integrating AI into existing workflows rather than treating it as an experimental tool.
Consequently, employees may spend less time producing routine documents, summarising information and completing repetitive analytical tasks. Instead, businesses can direct more attention toward reviewing results, solving problems and making strategic decisions.
However, adoption alone does not guarantee better outcomes. Companies still need appropriate training, reliable information and human oversight to ensure AI generated work meets professional standards.
Research Shows AI Can Help Workers Perform Beyond Their Experience
Research published in Nature Human Behaviour on October 26, 2026, examined whether generative AI could help professionals develop capabilities beyond their existing skill sets.
The randomized controlled trial involved 487 management consultants who received access to ChatGPT and training to solve data science tasks outside their areas of expertise. Researchers found that AI assisted participants performed better than the control group on three tasks.
However, the study also found that participants did not demonstrate improved technical knowledge when answering questions without AI after the experiment. Their improved performance therefore did not necessarily translate into lasting independent expertise.
This finding highlights an important distinction between using AI to complete a task and developing the knowledge required to perform it independently.
Furthermore, a study published in The Quarterly Journal of Economics in 2025 examined 5,172 customer support agents. Researchers found that access to an AI assistant increased productivity by 15 percent on average, measured by issues resolved per hour.
Less experienced workers experienced improvements in both speed and quality, while the most experienced workers recorded smaller speed gains and small declines in quality.
Together, these findings suggest that AI can help close certain skill gaps. Nevertheless, the benefits depend on the task, the worker’s existing knowledge and the ability to evaluate AI generated results.
Why Human Judgment Could Become More Valuable
As AI tools become more effective at generating content and analysing information, businesses may place greater value on abilities that extend beyond producing an initial answer.
These include critical thinking, contextual understanding, communication, ethical judgment and accountability. Experienced professionals can use these skills to identify errors, challenge assumptions and determine whether an AI generated recommendation makes sense in a particular situation.
For example, an AI system might prepare a financial analysis or suggest a marketing campaign. However, a finance professional must assess financial risks, while a marketing specialist must understand customer behaviour and brand positioning.
Similarly, software developers must evaluate generated code for security, performance and compatibility with existing systems.
Therefore, expertise may increasingly depend on how effectively professionals combine subject knowledge with AI capabilities, rather than simply how quickly they produce an output.
Implications for Hiring, HR and Business Strategy
The changing relationship between AI and expertise could influence recruitment, employee training and career progression.
In human resources, employers may place greater emphasis on practical assessments, problem solving and the ability to use AI responsibly. Some roles may require fewer routine technical tasks, while others could demand stronger analytical and supervisory skills.
Meanwhile, sales strategies and research could benefit from AI assisted customer analysis, personalised communication and faster preparation. Marketing trends analysis may also change as teams use AI to generate campaign concepts, examine performance data and accelerate content production.
Finance industry updates and technology insights will increasingly need to address the balance between efficiency, professional accountability and risk management.
However, organizations should avoid assuming that AI can replace all forms of experience. High stakes decisions, complex customer relationships and work requiring specialist judgment still demand appropriate human involvement.
What Businesses Should Know
Businesses should prepare for a workplace where AI literacy and professional expertise increasingly work together. Investing in employee training, establishing clear review processes and measuring productivity gains can help organizations adopt the technology responsibly.
Moreover, employers should distinguish between short term performance improvements and genuine skill development. Employees who understand their fields can use AI more effectively, verify its outputs and recognize when its recommendations are unreliable.
The future value of expertise will therefore depend not only on what professionals know, but also on how they apply that knowledge, evaluate AI generated information and make sound decisions.
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Source : hbr.org
