How AI Agents and Human Agents Work Better Together
1/7/26, 10:00 am
The conversation about AI in customer service often begins with automation. Which enquiries can be handled faster? Which tasks can be completed without human intervention? Where can contact volumes be reduced?
Those are useful questions, but they do not tell the whole story.
As AI agents become more capable, the role of the human agent is also changing. Routine enquiries may increasingly be handled by AI, while human employees spend more time on complex issues, sensitive conversations, exceptions and moments where judgement matters.
The most effective service models will be built around a clear understanding of what AI does well, where human expertise adds the most value, and how the two can work together without creating more friction for customers or employees.
At a glance
- AI agents can help reduce repetitive work and support faster customer resolution
- Human agents remain critical for empathy, judgement, exceptions and complex problem-solving
- The role of the human agent is likely to become more specialised as AI handles simpler interactions
- AI can support employees by summarising conversations, surfacing knowledge and recommending next steps
- Customers are increasingly open to AI when it improves the service experience
- Strong service design is needed to ensure AI and human agents work from the same context
AI is changing the shape of service work
Automation is reducing some tasks and elevating others.
Customer service has always involved a mix of predictable and unpredictable work. Some interactions are simple and transactional. Others require interpretation, empathy, negotiation or judgement.
AI agents are well suited to many repeatable interactions. They can help customers find information, complete standard processes, check account details, update records or progress simple service requests. When designed well, this can reduce wait times and free human employees from repetitive administrative work.
Proof point: McKinsey’s analysis of contact centres found that 50% to 60% of customer interactions remain transactional, despite years of effort to shift these enquiries into digital channels.
When AI handles routine demand, human agents are more likely to manage interactions that are complex, emotionally charged or commercially sensitive. These situations often involve incomplete information, frustrated customers, policy interpretation, vulnerable people or decisions that carry reputational and regulatory risk.
Customers still value human judgement
Trust depends on the nature of the interaction.
Customers are becoming more comfortable with AI in service environments, particularly when it helps them resolve issues quickly. NiCE’s 2025 Global Happiness Index found that 72% of consumers report experiencing benefits from AI and automation in customer service.
Proof point: Gartner found that 54% of customers trust human agents more than AI for product or service recommendations, compared with 32% who trust AI more.
The distinction is important. Customers may be happy for AI to help with routine requests, but they often prefer human support when the situation involves advice, judgement or personal impact. A billing correction, urgent claim, hardship request or complex complaint carries a different emotional weight from checking an order status.
AI can support that experience by providing context, knowledge and recommendations. The human agent still plays a central role in interpreting the situation and deciding how best to respond.
AI can make human agents more effective
The greatest value may come from assistance.
AI agents are often discussed as a customer-facing capability. Inside the contact centre, they can also become a powerful support layer for employees.
- summarising the customer’s issue
- surfacing relevant knowledge articles
- recommending next best actions
- identifying customer sentiment
- checking policy or eligibility rules
- preparing case notes
- reducing after-call work
For agents, these capabilities can reduce cognitive load. Instead of searching through multiple systems while trying to keep a customer engaged, the agent can focus more attention on the conversation itself.
Proof point: Salesforce reported that 81% of service representatives say their role has become more specialised as a result of working with AI tools.
Salesforce also found that 71% of representatives say AI is creating growth opportunities and 86% have developed new skills.
Human roles are becoming more specialised
The frontline role is expanding.
AI adoption is already influencing workforce planning. Gartner found that 85% of customer service and support leaders are expanding human agent responsibilities as AI reduces contact volume and shifts work towards higher-value tasks. It also reported that 75% are shifting agents into entirely new roles.
The stronger long-term opportunity lies in redesigning the role of the human agent around the work customers value most.
- handling complex escalations
- supporting vulnerable or high-value customers
- resolving complaints and exceptions
- coaching AI performance through feedback
- improving knowledge content
- identifying process issues
- supporting proactive outreach or retention activity
For many organisations, this will require new skills, coaching models and performance measures. Traditional metrics such as average handle time may need to be balanced with resolution quality, customer effort, employee confidence and the successful management of complex interactions.
Where AI and human agents each add value
| Service need | AI agent strength | Human agent strength |
|---|---|---|
| Routine enquiries | Fast, consistent responses at scale | Reviewing exceptions or unusual cases |
| Knowledge retrieval | Finds approved information quickly | Interprets policy in context |
| Case preparation | Summarises history and recommends next steps | Validates, adapts and applies judgement |
| High-volume tasks | Handles repetitive work efficiently | Focuses on complex or sensitive issues |
| Customer sentiment | Detects signals and flags risk | Responds with empathy and nuance |
| Escalations | Transfers context and suggested actions | Owns resolution and relationship repair |
Collaboration depends on shared context, trusted knowledge and clear accountability. If AI handles the simple parts but fails to transfer context, the customer experience suffers. If human agents do not trust AI-generated recommendations, they may ignore them or duplicate work.
The handover matters as much as the automation
Customers should not feel the join between AI and human support.
One of the biggest risks in AI-enabled service is a poor escalation experience. A customer may start with an AI agent, explain the issue, provide information and follow several steps. If they then reach a human agent who has no context, the experience becomes frustrating.
Good handover design should include conversation history, customer details and intent, actions already completed, relevant knowledge articles, sentiment or urgency signals, recommended next steps and the reason for escalation.
This helps the human agent begin from a position of understanding. It also reduces repetition for the customer and shortens the time required to resolve the issue.
Questions organisations should ask now
- Which customer interactions are suitable for AI-led resolution?
- Which interactions should remain human-led from the beginning?
- What signals should trigger escalation to a human agent?
- What context should transfer during handover?
- How will agents know when AI recommendations are reliable?
- What new skills will human agents need as their work becomes more complex?
- How should performance measures change in an AI-supported service model?
Better together, by design
AI agents can improve customer service by reducing repetitive work, increasing availability and helping customers complete routine tasks faster. Human agents bring empathy, judgement, creativity and accountability to the moments that need them most.
Success will depend on the design choices organisations make now: how knowledge is governed, how workflows are orchestrated, how escalations are handled and how employees are supported as their roles evolve.
When AI agents and human agents work from the same context, the experience becomes smoother for customers and more manageable for employees. Customer service has always depended on people who can solve problems. AI now gives them a better toolkit.
Design service experiences that support your people
Better customer outcomes depend on how well AI, knowledge, workflows and human teams work together. Explore NEC’s approach to Contact Centre and CX, and how we help organisations support employees, reduce friction and create more responsive service experiences.
