Why support backlogs are growing — and why AI search fixes the basics

Ticket volumes keep climbing while customers expect near-instant help. The bottleneck isn’t effort; it’s finding the right, up-to-date answer fast. AI-powered enterprise search addresses this by unifying your knowledge (KBs, runbooks, prior tickets, docs) and surfacing permission-aware answers directly inside your existing tools, reducing handle time and escalations.

Glean’s Work AI platform plugs into tools support teams already live in — Zendesk, ServiceNow, Salesforce, Slack/Teams — so agents and employees get answers without tab-hopping. This “shift-left” approach deflects common requests before they become tickets and speeds resolution when a ticket is required.

How Glean’s AI-powered search works for support

1. Connect & index securely. Glean’s connectors bring in content and permissions from systems like Zendesk, ServiceNow, and Salesforce so results respect record-level access.

2. Understand questions, not just keywords. AI search interprets intent and context (e.g., product, plan, error code) to retrieve the most relevant, current guidance.

3. Answer with citations. Agents see the answer and where it came from — knowledge article, solved case, or internal doc — building trust and speeding compliance reviews.

4. Embed in workflows. Surface answers in Slack/Teams, within the ticket sidebar, or the help centre, minimising context switching and encouraging self-service.

What’s new in 2025

• Work AI + agents: Glean now supports building assistants/agents on the platform and via popular frameworks, enabling deeper workflow automation (e.g., propose replies, update cases) while keeping systems of record authoritative.

• Customer service integrations: Strengthened native integrations for Zendesk, ServiceNow and Salesforce streamline triage, routing, and knowledge use in-flow.

• Shift-left deflection: Improved help-centre and chat experiences present verified answers before users file tickets.

Reality check: even top AI leaders note that effective automation demands careful engineering and guardrails — start with search + assist, prove value, then automate gradually. Business Insider

Practical ways to reduce your backlog with Glean

1) Deflect repetitive tickets with knowledge-first answers.
Publish your best KB content and solved-case learnings; Glean exposes them in help centres and collaboration tools. Expect fewer “how do I reset…” or “where do I find…” tickets, cutting volume before it hits the queue.

2) Accelerate triage and routing.
Use AI search to identify problem type, product, and urgency from ticket text, then route to the right queue or suggest next actions. This reduces ping-ponging and speeds SLA compliance.

3) Boost first-contact resolution (FCR).
Surface runbooks, policy pages, and similar solved cases directly in the agent view so L1 can resolve more without escalation — shaving minutes off every interaction and lowering MTTR.

4) Equip cross-functional responders.
Because results respect source permissions, engineers and product managers can safely search prior incidents and fixes to assist support without exposing sensitive records.

5) Mine patterns to fix issues upstream.
Aggregate insights from tickets and chats to spot recurring problems and content gaps — then update KBs and macros. Backlog drops when root causes are addressed.

Step-by-step rollout (low risk, measurable)

Phase 1 — Connect & pilot (2–4 weeks).

• Connect Zendesk/ServiceNow/Salesforce + main KB.

• Pick one product area and a small agent cohort.

• Baseline KPIs: deflection rate, MTTR, FCR, escalations.

Phase 2 — In-flow assistance (4–6 weeks).

• Enable sidebar/Slack/Teams answer surfacing and citations.

• Add macros/snippets informed by top answers.

• Track: time-to-first-response, touches per ticket.

Phase 3 — Automate where proven (ongoing).

• Introduce safe automations (draft replies, case field suggestions, knowledge suggestions).

• Govern with human-in-the-loop reviews; expand scope as quality holds.

What good looks like (KPIs to watch)

• Deflection rate (help-centre or virtual assistant): % of sessions resolved without filing a ticket.

• MTTR (mean time to resolution): should drop as answers surface faster.

• FCR (first-contact resolution): rises with better knowledge access.

• Agent handle time/touches: should decline as context is unified.

• Escalation rate: falls as L1 resolves more.

Example: Embedded AI search inside your stack

• Zendesk: Search across cases + KBs with record-level permissions; show verified content to agents as they type.

• ServiceNow: Join IT/HR knowledge and tickets with the rest of company knowledge to resolve issues faster.

• Salesforce: Bring case and account context into the workspace; prep responses and keep Salesforce as the system of record.

Summary & next steps

Backlogs shrink when the right answer appears in the right place, instantly. Glean’s AI search unifies knowledge, speeds triage, and enables shift-left self-service — reducing MTTR and raising satisfaction without heavy process change. Start small, measure, then automate where quality is proven.

Talk to us: Generation Digital can help you connect Glean, design a safe rollout, and measure impact.

FAQs

How does AI improve ticket resolution times?
By unifying knowledge and surfacing verified, permission-aware answers inside agent tools, AI removes search time and reduces escalations — speeding MTTR and boosting FCR. glean.com

Can AI strengthen self-service?
Yes. With “shift-left” deflection, AI presents relevant answers in the help centre or chat before a ticket is filed, reducing inbound volume. glean.com

Is implementation complex?
Glean ships with native connectors (Zendesk, ServiceNow, Salesforce) and embeds into existing workflows, so pilots are fast and low risk. Start with search + assist, then automate in steps. Business Insider | glean.com