AI speeds responses, adds 24/7 coverage and cuts support costs, survey finds

AI is buying back time for support teams-faster replies, 24/7 coverage, and scale without adding headcount. Mature setups turn those time savings into lower costs and new revenue.

Categorized in: AI News Customer Support
Published on: Feb 05, 2026
AI speeds responses, adds 24/7 coverage and cuts support costs, survey finds

AI is helping support teams move faster - and do more with the same headcount

A new survey of 2,400+ customer support professionals from Intercom points to a clear theme: AI is buying back time. 53% said faster response and resolution times are a top benefit.

Teams also report 24/7 coverage, the ability to scale without growing headcount, and a lower cost to serve. The most common AI agent use cases: automating manual work, assisting with proactive engagement, and performing customer tasks.

What AI actually does well in support

  • Automates the admin: call summaries, ticket tagging, post-interaction notes.
  • Speeds up knowledge retrieval: surfaces policies and technical specs instantly.
  • Handles repeatable customer tasks: updates, lookups, simple changes.
  • Supports proactive outreach: nudges, follow-ups, renewal reminders.

"The most impactful thing AI does is strip away the administrative drag; the manual call summarization, ticket tagging, and post-interaction data entry that create distractions for agents," said Julie Geller, principal research director at Info-Tech Research Group. "It can also handle the heavy lifting of knowledge retrieval, where instead of an agent digging through PDFs or internal wikis while a customer waits, the AI surfaces the exact policy or technical spec instantly."

Maturity matters for ROI

Teams with mature AI deployments see the strongest efficiency gains and measure ROI by time freed up. Nearly three-quarters of those mature teams track time savings as a primary ROI signal, compared to 64% for teams in the scaling phase and 59% in initial deployment.

That maturity shows up in how teams use the time they win back. 56% of mature teams are redirecting it to revenue-generating work, versus about one-third of teams just getting started.

Turn time savings into revenue

  • Route seasoned agents to retention plays: save attempts, win-backs, renewal outreach.
  • Enable contextual upsell/cross-sell during resolved conversations (with clear guardrails).
  • Stand up proactive check-ins for high-risk accounts to reduce churn.
  • Offer VIP follow-through: callbacks, white-glove troubleshooting, and account expansion discovery.

A practical playbook to implement

  • Pick high-volume, low-judgment tasks first: summaries, tagging, FAQs, order status.
  • Deploy an AI knowledge layer before you chase edge cases. Centralize source of truth.
  • Instrument everything: time saved per ticket, agent handle time, first-response time, resolution time.
  • Redesign queues: AI handles, triages, or drafts; humans review, personalize, and resolve exceptions.
  • Embed quality checks: sample reviews, policy tests, red-team prompts, and continuous tuning.
  • Keep human-offramp visible: "Talk to a person" should be one tap away.
  • Train agents on AI-as-copilot workflows, not just prompts. Update SOPs accordingly.

Mind the customer signal

The Intercom report didn't probe downsides, but prior research shows customers worry about losing access to humans. Make it obvious how to reach a person and set clear expectations for response times.

Use AI to cut the wait and remove busywork, while humans handle nuance, empathy, and high-value conversations. Communicate that balance up front to build trust.

What to measure (and report up)

  • Response and resolution times (median and 90th percentile).
  • Cost to serve (per contact, per channel).
  • Containment rate with satisfaction (AI-resolved and CSAT on those interactions).
  • Transfer rate and time-to-human for escalations.
  • Agent productivity: cases per hour and time saved per case.
  • Revenue impact: saves, renewals influenced, qualified expansion opportunities.

Level up your team's AI skills

If you're building AI workflows for support, align training with roles and responsibilities. Explore curated learning paths by job to accelerate rollout and reduce rework: Complete AI Training - Courses by Job.

Bottom line: use AI to remove the admin load, elevate knowledge access, and reroute saved time into revenue and retention. The earlier you instrument and iterate, the faster the payoff compounds.


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