Customer support is shifting toward digital self-service, live chat, and AI-assisted workflows, while human agents remain essential for complex and sensitive cases. The clearest trend is not that people are disappearing from service: teams are redesigning how technology and human judgment work together, with customer satisfaction, knowledge quality, security, and efficiency all in view.
What is changing in customer support?
Service teams are balancing four connected shifts: more digital-first support, broader use of AI in service workflows, greater reliance on knowledge and self-service, and changes to agents’ responsibilities and skills. Survey findings point to these directions, but they do not establish a universal channel mix or prove that any one technology will improve results for every organization.
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Gartner’s survey of 265 customer-service and support leaders, conducted in April and May 2025, found that respondents expected digital-first technologies to gain value relative to phone and email. Live chat, self-service portals, and knowledge-management systems featured among the important technologies. Gartner’s research director J.J. Moncus described them as “solidifying their place as essential tools for fast, scalable support.” The finding is about leaders’ expectations, not a recommendation to remove phone or email from a particular service operation. Gartner, September 2025.
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AI is moving from experimentation into more service workflows, but adoption and case-handling figures measure different things and should not be combined into one universal adoption rate.
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AI handling cases: a projection, not an audited count
In Salesforce’s seventh State of Service survey, fielded April 25 through June 6, 2025, service professionals estimated that AI handled 30% of service cases at the time of the survey and projected that it would handle 50% by 2027. The survey covered 6,500 service professionals and decision makers. These are respondents’ estimates and projections, not independently audited case counts or a guarantee that the forecast will be reached. Salesforce, 2025.
Agentic AI: reported organizational use
A separate Salesforce survey of 3,075 service professionals, fielded March 9 through April 4, 2026, found that 66% of customer-service organizations reported using agentic AI, compared with 39% in 2025. Salesforce also reported that 70% of organizations using AI service agents said they observed measurable value within 60 days. Customer satisfaction ranked highest among the KPIs respondents said improved after deployment. These are survey-reported adoption and experience findings; they are not a controlled comparison or a promise of results for another team. Salesforce, 2026.
The 2025 estimate of cases handled by AI and the 2026 report of organizations using agentic AI are not interchangeable: one concerns a share of cases estimated by respondents, while the other concerns organizations reporting use of a category of AI.
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Automation is most useful when it makes routine service easier without leaving customers stranded when an issue requires context, empathy, or judgment. Salesforce reported that representatives using AI spent 20% less time on routine cases in its 2025 survey. That is a survey finding, not proof that AI alone caused the reduction or that every team will see the same effect.
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Gartner’s October 2025 survey of 321 customer-service and support leaders found that nearly 80% planned to transition at least some agents into new roles, 84% planned to add skills to the agent role, and 58% aimed to upskill agents into knowledge-management specialists. These are reported intentions, not completed workforce changes. Gartner research director Kim Hedlin summarized the direction: “Service organizations are entering a period where AI and human expertise must work in tandem.” Gartner, January 2026.
For service teams, the implication is a shift in the work rather than a settled forecast of headcount: agents may handle more exceptions and complicated cases, while also maintaining the knowledge that powers self-service and AI. The surveys report plans and experiences; they do not establish how any one organization should redesign its roles.
Knowledge quality is becoming operational infrastructure
Self-service and AI depend on reliable, current answers. A portal cannot resolve an issue with an outdated article, and an AI workflow built on inconsistent guidance can reproduce that inconsistency at scale. Gartner’s reported interest in knowledge-management systems and planned upskilling for knowledge-management roles point to the importance of maintaining the information behind automated and human support.
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Knowledge work is therefore not just documentation. Teams need clear ownership for updates, a way to identify gaps from unresolved contacts, and consistent guidance across channels. The available survey results do not quantify the return from any particular knowledge program, but they show knowledge management appearing alongside digital support and workforce skill priorities.
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Customer experience, security, and efficiency must be weighed together
Speed and lower effort matter, but reported customer expectations make successful resolution central. Zendesk’s 2026 CX Trends release said 85% of surveyed CX leaders believed customers would drop brands unable to resolve issues on first contact. In the same report, 86% of surveyed consumers said responsiveness and accurate resolution strongly influenced purchase decisions. These figures describe the respondent groups in Zendesk’s report; they are not universal behavior rates. Zendesk, 2026 CX Trends.
Security is another constraint on AI programs. Salesforce reported that 51% of service leaders said security concerns had delayed or limited their AI initiatives in its 2025 State of Service survey. Meanwhile, Gartner’s 2026 priorities survey reported that 91% of customer-service and support leaders faced executive pressure to implement AI. Pressure to adopt does not remove the need to protect customer information, set appropriate permissions, and decide when a human should review or take over a case.
What the survey numbers do—and do not—show
| Finding | What it measures | How to read it |
|---|---|---|
| 73% — Gartner, 2025 | Forecast for customer-service organizations implementing agent-assist technology by the end of 2025 | A forecast made in Gartner’s April–May 2025 survey, not a measured end-of-year outcome. Source |
| 30% then; 50% by 2027 — Salesforce, 2025 | Respondents’ estimates of the share of service cases handled by AI at the time and their projection for 2027 | Survey estimates and expectations from 6,500 service professionals and decision makers, not audited case data. Source |
| 66% in 2026, up from 39% in 2025 — Salesforce, 2026 | Customer-service organizations reporting agentic AI use | Survey finding from 3,075 service professionals; it is not the same metric as AI’s estimated share of cases. Source |
| 91% — Gartner, 2026 | Customer-service and support leaders reporting executive pressure to implement AI | Reported in a survey of 321 leaders conducted in October 2025; it measures pressure, not successful implementation. Source |
These studies use different samples, dates, and definitions. Taken together, they indicate changing priorities and reported activity, not a controlled comparison of service strategies or a guaranteed return on investment.
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How service teams can evaluate the trends
A useful evaluation starts with the customer’s issue and the outcome the team needs, rather than with a target to automate a particular share of contacts.
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- Resolution and customer effort: Track whether customers complete self-service successfully and whether contacts are resolved accurately, including at first contact.
- Case complexity: Separate straightforward, repeatable questions from cases requiring human judgment, sensitivity, or investigation.
- Channel access: Assess whether chat, portals, phone, and email fit the needs and accessibility expectations of the customers you serve. Gartner’s findings do not establish that one channel should replace another.
- Knowledge accuracy: Identify who owns customer-facing answers, how often they are reviewed, and how unresolved contacts reveal missing or outdated information.
- Data and security readiness: Set boundaries for customer data, access, and human review before expanding AI workflows; Salesforce found security concerns had delayed or limited initiatives for some leaders.
- Agent workload and skills: Measure how technology changes routine work and what training agents need for exceptions, judgment-heavy cases, and knowledge responsibilities.
- Balanced outcomes: Consider customer satisfaction, self-service success, accurate resolution, and operating efficiency together. The cited surveys do not establish a universally best mix or guaranteed ROI.
Frequently Asked Questions
Are customer-service teams replacing human agents with AI?
The cited surveys describe AI use and plans to change agent roles and skills, not a universal replacement of human agents. Gartner’s 2026 survey reported intentions to transition some agents into new roles and add skills to the agent role.
Does the 2027 AI case-handling figure mean AI will resolve half of every company’s support cases?
No. Salesforce reported that survey respondents estimated AI handled 30% of cases at the time of its 2025 survey and expected 50% by 2027. Those figures are not audited results for each company.
Which customer-support technology trends should teams watch?
The surveys point to live chat, self-service portals, knowledge-management systems, agent-assist, and AI agents. Their relevance depends on the team’s customers, issues, knowledge quality, and security requirements; the findings do not establish a single best technology stack.
Frequently Asked Questions
Are customer-service teams replacing human agents with AI?
The cited surveys describe AI use and plans to change agent roles and skills, not a universal replacement of human agents. Gartner’s 2026 survey reported intentions to transition some agents into new roles and add skills to the agent role.
Does the 2027 AI case-handling figure mean AI will resolve half of every company’s support cases?
No. Salesforce reported that survey respondents estimated AI handled 30% of cases at the time of its 2025 survey and expected 50% by 2027. Those figures are not audited results for each company.
Which customer-support technology trends should teams watch?
The surveys point to live chat, self-service portals, knowledge-management systems, agent-assist, and AI agents. Their relevance depends on the team’s customers, issues, knowledge quality, and security requirements; the findings do not establish a single best technology stack.
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