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.
Salesforce is positioned as a Leader with enterprise scale and Agentforce Service momentum. Complex pricing and slower value realization for AI agents are cautions to factor into planning.
Microsoft is positioned as a Leader with strong integration across Azure, Office, and Teams. Complexity and support concerns are worth pressure-testing in global environments.
Pegasystems is positioned as a Leader with strengths in case management and workflow design. Stronger integration to support an optimization flywheel is a stated gap.
ServiceNow is positioned as a Leader with enterprise orchestration and SLA frameworks. Complexity and cost are the main cautions to weigh against strategic fit.
Strong Performers And Contenders: Faster Paths, Clearer Tradeoffs
Strong Performers in the Wave include Zendesk, Oracle, Creatio, and Freshworks. Contenders include Intercom, SAP, Zoho, and HubSpot.
These vendors can be strong options when speed, usability, and deployment simplicity are priorities. The tradeoff is usually less depth in global rollout controls, complex governance, and mature optimization frameworks.
Zendesk stands out for pretrained intents and real-time quality measurement. Packaging changes and scale pricing are the main cautions called out.
Oracle leans into back-office automation and AI agent tooling. Gaps remain around digital experience strength and analytics depth.
Creatio brings no-code flexibility and value-aligned pricing. Reporting depth and complex scenario handling are the areas to pressure-test.
Freshworks often wins on usability and time to value. Process management and automation depth can be limiting in more complex enterprise environments.
Intercom is positioned around Fin AI Agent and conversational strengths. Global deployment settings are flagged as a constraint.
SAP’s advantage is its proximity to ERP workflows and Joule Studio. Native knowledge management and CCaaS are not central strengths, and specialist expertise can be required.
Zoho is framed as frictionless to deploy with low-code tooling. Quality management and conversation intelligence are less robust.
HubSpot is presented as simple to adopt and aligned to lifecycle use cases. Customization depth and reporting are the key limitations to factor into fit.
What This Signals For CX Leaders In 2026
The most important takeaway is not who lands where on the chart. It is what AI forces you to operationalize.
AI-first service requires a governance model that fits your risk profile. It requires measurement you can trust, escalation that preserves context and customer emotion.
It also requires a workforce strategy. Some roles will shrink. New roles will appear. Your best agents may become the people who train, tune, and audit AI, and the people who handle the moments that actually define loyalty.
That is achievable. It is not automatic.
The leaders who get this right will treat AI as a new workforce. They will manage it with discipline. They will measure it with honesty. And they will build service experiences that feel more human because the humans are focused where they matter most.
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