Forrester released its Wave evaluation of customer service solutions for Q1 2026, and it puts AI agents at the center of enterprise service strategy.
The report argues that AI is shifting customer service away from a reactive, manual cost center. It positions AI as the mechanism for proactive, personalized service at scale.
For CX leaders, the signal is sharper than a vendor ranking. AI will handle the majority of interactions. Human agents will guide, correct, and recover.
That means service modernization is no longer just a platform upgrade. It is a workforce redesign.
AI Is Becoming The Frontline In Customer Service
Many enterprises still treat AI as a sidecar. It helps with deflection, summarizes a chat or drafts an agent response.
Forrester’s Wave signals something bigger. AI is becoming the primary service layer.
In an assessment, Kate Leggett, Principal Analyst at Forrester warned:
"AI is fundamentally transforming customer service operations from a reactive, cost-heavy, and manual function into a proactive, efficient, and personalized experience."
That shift changes how you think about quality. It also changes how you think about accountability.
If AI becomes the first touch, you cannot treat failures as edge cases. You need controls that prevent wrong answers from becoming a scaled problem.
The Work Flips: Humans Support AI, Not The Other Way Around
This is the most disruptive message in the report. The role hierarchy changes.
AI handles the majority of work. Human agents become the exception layer. Asked what changes now, Leggett emphasized:
"The role of AI and the CSR flips: AI addresses the majority of the work, while CSRs assist AI."
For enterprise leaders, this creates immediate questions around who owns, AI outcomes, customer harm when automation fails, and who updates policy and knowledge when the business changes?
It also forces an org conversation about skills. The agents who thrive will not just answer questions. They will diagnose complex scenarios, correct automation and become coaches for a digital workforce.
What CX Leaders Should Demand From AI-First Platforms
The Wave reframes selection criteria.
It is no longer enough to ask whether a platform has gen AI. Most do. The real question is whether it can run an AI-first service operation responsibly.
From an execution standpoint, Leggett outlined the goal:
"Look for vendors that offer tightly blended AI and CSR experiences and measurement and optimization frameworks for AI."
That points to three priorities.
First is a blended AI and agent experience. Agents need visibility into what AI did and why. They also need fast handoffs that keep context intact.
Second is measurement and optimization. AI performance will drift. Enterprises need a repeatable system for evaluating outcomes, reducing risk, and improving accuracy.
Third is agentic execution. AI needs to complete multi-step work, not just provide answers. That increases the importance of orchestration, guardrails, and policy control.
Leaders: Built For Scale, But Not Always For Speed
Forrester names four Leaders: Salesforce, Microsoft, Pegasystems, and ServiceNow.
A fit-for-purpose read starts with your operating reality. If you already run a large ecosystem, you may value integration over speed. If you need rapid time to value, you may value simplicity and lower implementation gravity.