Editorial
Research Report
The State of Enterprise Site Search: 2026 Benchmark Report
The Gist
- AI shifts the agent role, not eliminates it. Agentic AI is increasingly handling repetitive CX tasks, but human agents remain central for complex, emotional and high-value interactions.
- Human agents gain operational support. Real-time intelligence, automated follow-ups and AI-driven coaching can reduce administrative burden and improve agent confidence.
- The future of CX is collaborative. Organizations are moving toward a blended model where AI agents and human workers operate together to improve both customer and employee experiences.
While AI is making its presence felt across virtually all industries, customer experience (CX) has emerged amongst a handful of major early adopters when it comes to scaled implementation. The combination of good data and optimized business processes; the volume of repetitive admin carried out by human service workers in contact centers, and the promise of more consumer self-service has presented compelling AI use cases that organizations are buying into.
One of the inevitable questions that arises is this: with fully-automated agentic interactions hoovering up all the easy tasks, will AI trigger a "human agent experience crisis" where those who still have jobs in contact centers find themselves lumbered with only the undesirable work?
Table of Contents
- Core Questions About AI’s Impact on Human Agents in Customer Experience
- Is It AI or Other Financial Strain?
- Emergence of Agentic AI in CX
- How Human Agents and AI Agents Can Succeed
Core Questions About AI’s Impact on Human Agents in Customer Experience
Editor’s note: As agentic AI expands across customer experience operations, organizations are rethinking how human agents, automation and customer service workflows coexist.
Is It AI or Other Financial Strain?
There can be little doubt that AI is already re-shaping the job market, even if some of the job losses announced by major employers are being given an AI spin, when the causes may be more cyclical or the result of strained financial models. Although job displacement can sound alarming, with 92 million jobs predicted to be taken by AI by 2030, there are also opportunities for job growth, with 170 million new jobs set to be created globally by AI according to the same report from the World Economic Forum.
CX sits on the frontline of this shift, with some hawkish reports predicting that all contact center agent roles will be fully automated. The reality of the situation is more nuanced, and will more likely be a balance between human and AI in CX as organizations find the best blend to best serve customers while supporting their staff.
Generative AI has unlocked a number of benefits in CX, mainly for human agents who are tasked with supporting customers. For example, features such as real-time transcription and summarization are able to create live notes, which are used to auto-generate summaries, vastly reducing wrap-up time during interactions and limiting the amount of admin tasks required.
Emergence of Agentic AI in CX
With generative AI now widespread within CX, and AI development continuing apace, we are now seeing the adoption of agentic AI capabilities. By implementing agentic AI, organizations can use tools that autonomously reason, plan and execute tasks with the aim of achieving goals, with minimal human intervention. With agentic AI now able to handle a growing number of enquiries, what will this mean for the role of the human agent as the balance tilts further away from the old model?
One key theme that came out of Enterprise Connect 2026 was that the rise of agentic AI would leave human agents to handle the most challenging and undesirable interactions, in turn harming agent experiences. However, the impact of AI agents will likely be much more beneficial to their human counterparts, since it works in partnership alongside them.
Ways that AI agents will positively improve the human agent experience include:
1. Real‑Time Case Intelligence & Preparation
AI agents can create knowledge articles to support human agents during interactions. They have the ability to determine customer details and intent, and draw information from different systems of record, via the CX environment's customer data platform (CDP), so that human workers have all the information and context they need. Furthermore, AI can provide real-time suggestions based on pre-approved organizational sources, outlining how to resolve the customer's issues.
AI agents will be able to create knowledge articles that include context such as customer history, prior tickets, sentiment trends, product usage, known issues and Service Level Agreement (SLA) status. It can also pull information from product guides, customer policies and FAQs to provide suggested actions which can be relayed to the customer.
As a result, interactions will run more smoothly and benefit the human worker by giving them all of the information they need to achieve a positive outcome – even when that worker is new to the role.
Related Article: What NiCE's Q1 2026 Results Reveal About Agentic AI in the CX Enterprise
2. Post-Interaction Administrative Activities
The implementation of generative AI tools has started to alleviate the administrative burden on agents. The addition of agentic solutions means that AI agents can now take what generative AI started and go one step further to create outcomes. For example, systems of records can be automatically updated, and AI agents can work on next steps, including the creation and scheduling of follow-up emails to customers and colleagues.
AI agents also have the ability to create support tickets and escalate issues, as well as initiate refunds for approval. Humans will still be "in the loop" and overseeing the progress AI agents are making, and they can intervene if necessary, but crucially, human agents are freed up and able to focus on problem-solving and human interaction, which is why many chose the role.
3. Continuous Coaching, Support and Development
As well as having the ability to offer "live" guidance through knowledge articles and prompts, AI agents can also act as coaches or mentors. These AI agents can monitor all interactions and offer feedback and guidance that feels supportive to the human worker, rather than punitive. Before AI, providing feedback was tricky as supervisors would typically only review a small percentage of interactions, with the review process often taking weeks, if not months.
AI has allowed for auto-analysis, and the implementation of AI agents can drive value through assistance. The relationship between humans and AI will be supportive and ensure human agents feel like they are getting the coaching they require. Managers and supervisors don't have the capacity to provide such intensive support and the introduction of AI Agents to provide feedback and guidance will leave human agents feeling more confident and valued in their roles.
Related Article: The CX Reckoning of 2025: Why Agent Experience Decided What Worked
How Human Agents and AI Agents Can Succeed
Despite narratives around autonomous versions of AI coming for their jobs, or diminishing the role of the agent, the growing relationship between human agent and AI has to be seen as a positive partnership.
Since the first contact centers opened their doors in the 1980s, workload has always been the number one source of job dissatisfaction among workers. The addition of more channels of engagement, more systems of record and increasingly complex workflows sometimes threatened to increase that workload to unsustainable levels, driving churn and leading to more organizational cost in sourcing and onboarding the next set of workers, as well as diminishing the customer experience and knowhow that seasoned human agents bring.
Now, finally, AI may be delivering the solution to this eternal conundrum.
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Despite increasing automation, humans will still be crucial within CX, and the focus should be on how AI can remove lower-range tasks from human agents and allow them to focus on high-value interactions, which provide great customer service and agent experiences.
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