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Who benefits most from AI agent support?

Artificial intelligence is often discussed as a way to automate customer service, but some of the strongest evidence points to a different benefit: helping inexperienced support staff perform more like seasoned agents.

On this page

  • Why newer agents gain the most
  • How AI changes specialist work
  • Where assistance can become overreliance
Preview for Who benefits most from AI agent support?

Why newer agents gain the most

Customer service work is difficult to learn because much of the expertise is informal. Experienced agents develop instincts about which questions to ask, how to explain policies, how to calm frustrated customers and which solutions tend to succeed. Historically, that knowledge was acquired slowly through mentoring, observation and repeated exposure to cases.

Agent assist illustration 1 AI agent-assist systems change this process by making accumulated organisational knowledge available during live interactions. Instead of searching multiple knowledge bases or waiting for a supervisor, a new agent can receive suggested answers, relevant policy extracts or recommended next steps while handling the conversation. [NiCE]nice.comBoosting Customer Experience with Agent Assist AI for… - NiCEAI Agent Assist is designed to provide real-time assistance, guidance…

The best-known evidence comes from a large study of more than 5,000 customer-support agents conducted by researchers from Stanford and MIT. After the introduction of a generative AI assistant, overall productivity rose by about 14–15%, measured by issues resolved per hour. However, the effects were not evenly distributed. Novice and lower-skilled workers improved by roughly 34–35%, while highly experienced workers saw little benefit. [NBER+2OUP Academic]nber.orgGenerative AI at Workby E Brynjolfsson · 2023 · Cited by 2855 — Access to the tool increases productivity, as measured by issues reso…

This pattern is important because it suggests AI is not merely accelerating work. It appears to be transferring expertise. Researchers concluded that the system captured successful practices from high-performing agents and helped less experienced colleagues apply them more consistently. [NBER]nber.orgGenerative AI at Workby E Brynjolfsson · 2023 · Cited by 2855 — Access to the tool increases productivity, as measured by issues reso…

In practical terms, newer agents often benefit from AI in three ways:

  • Faster policy retrieval: finding the correct procedure without extensive searching.
  • Response drafting: generating a first version of a reply that the agent can edit.
  • Decision support: recommending likely resolutions based on similar historical cases.

These capabilities reduce uncertainty and allow newer staff to spend more attention on the customer rather than on navigating internal systems.

Workers with less experience Gain the most from Generative AI | MIT Sloan | Shanmugaraj.

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How AI changes specialist work

The same evidence that shows large gains for inexperienced workers also suggests that expert agents experience a different relationship with AI. When someone already knows the policies, common exceptions and effective communication techniques, there is less room for improvement from basic guidance. [NBER]nber.orgGenerative AI at Workby E Brynjolfsson · 2023 · Cited by 2855 — Access to the tool increases productivity, as measured by issues reso…

As a result, AI often shifts specialists away from routine information retrieval and towards tasks that require judgement. Instead of spending time answering standard questions from colleagues, senior staff may focus on:

  • Handling unusual or high-risk cases.
  • Resolving policy conflicts and exceptions.
  • Coaching less experienced agents. [mitsloan.mit.edu]mitsloan.mit.eduMIT SloanWorkers with less experience gain the most from…Jun 26, 2023 — Contact center agents with access to an AI assistant were 14%…
  • Reviewing AI-generated recommendations.
  • Improving knowledge resources and workflows.

This can create a multiplier effect. Rather than helping customers one interaction at a time, specialists help shape the guidance that AI distributes across an entire service team.

Evidence from customer-service deployments also suggests that AI can make communication more consistent. In one large-scale field experiment involving customer-support operations, AI assistance improved service speed and helped lower-performing workers narrow performance gaps with stronger colleagues. The result was a more uniform level of service across the workforce. [arXiv]arxiv.orgGenerative AI in Action: Field Experimental Evidence from Alibaba's Customer Service OperationsFebruary 8, 2026…Published: February 8, 2026

That consistency is often valuable to customers. A customer receiving help from a new employee may receive an answer closer in quality to what they would have obtained from a veteran agent.

Agent assist illustration 2

What effective agent assistance looks like

The most useful agent-assist systems are not simply chatbots embedded inside a support dashboard. They are integrated into the workflow and appear at moments when assistance is needed.

Typical functions include:

  • Automatic summaries of customer history before a conversation begins.
  • Suggested replies that reflect company policies.
  • Real-time identification of relevant knowledge articles.
  • Step-by-step guidance through standard procedures.
  • Alerts when a proposed action may violate policy.
  • Automatic generation of case notes after the interaction.

The key design principle is augmentation rather than replacement. The agent remains responsible for the customer interaction, while the AI reduces the cognitive effort required to locate information and complete routine tasks. [NiCE]nice.comBoosting Customer Experience with Agent Assist AI for… - NiCEAI Agent Assist is designed to provide real-time assistance, guidance…

This distinction matters because customer service frequently involves exceptions, emotional conversations and ambiguous requests. Even when AI can suggest a response, human judgement often remains necessary to decide whether that response is appropriate.

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Where assistance can become overreliance

The same features that make AI valuable for inexperienced staff can also create risks.

One concern is skill development. If agents rely heavily on AI-generated answers, they may learn procedures more slowly than previous generations of support staff. An employee who follows recommendations without understanding the reasoning behind them can struggle when unusual situations arise.

Research also indicates that top-performing workers may not benefit in the same way as novices. In some settings, extensive reliance on AI recommendations has been associated with little improvement and, under certain conditions, declines in aspects of service quality among already strong performers. [arXiv]arxiv.orgGenerative AI in Action: Field Experimental Evidence from Alibaba's Customer Service OperationsFebruary 8, 2026…Published: February 8, 2026

Another challenge involves error propagation. If an AI system retrieves outdated guidance or misunderstands a customer issue, inexperienced agents may be less likely to recognise the mistake. This creates a risk that incorrect information spreads more widely than it would through purely human decision-making.

Customer-service organisations therefore increasingly emphasise verification and oversight. Effective programmes teach agents to treat AI suggestions as recommendations rather than instructions. The goal is to build confidence without eliminating critical thinking.

Agent assist illustration 3

The balance between confidence and competence

One of the most valuable effects of AI agent assistance is psychological rather than technical. New support staff often struggle with uncertainty. They may know where information exists but not how to find it quickly during a live interaction. AI can reduce that hesitation by surfacing relevant knowledge at the moment it is needed.

However, long-term success depends on balancing confidence with competence. Organisations that use AI solely as a shortcut may create workers who depend on automated guidance. Organisations that use AI as a teaching tool can potentially accelerate the development of expertise.

The strongest evidence so far suggests that AI agent assistance works best when it acts as an experienced colleague sitting beside a newer employee: providing guidance, surfacing knowledge and suggesting next steps, while leaving responsibility and judgement in human hands. In customer-service redesign, that ability to elevate less experienced workers may be one of AI’s most significant contributions. [NBER+2Stanford Graduate School of Business]nber.orgGenerative AI at Workby E Brynjolfsson · 2023 · Cited by 2855 — Access to the tool increases productivity, as measured by issues reso…

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Endnotes

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    Generative AI Make You More Productive at Work? Yes...24 Apr 2023 — They found that access to AI assistance increased agent productivity...

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Additional References

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