IT & Data
IT service desk triage and deflection
Classify and route inbound IT tickets, resolve common requests through self-service, and draft first-line responses for the remainder using the internal knowledge base and past resolutions.
25–45%
reduction in first-line ticket volume
Opportunity assessment
Minor improvement. Small efficiency gain with limited effect on overall turnover or bottom line.
Relatively straightforward. Off-the-shelf tools handle the core task. Implementation is well-understood with good examples to follow.
Light data requirements. Uses straightforward inputs — documents, product descriptions, customer records — that are usually accessible with minimal prep.
Low risk. Limited external exposure. A human reviews output before it reaches anyone outside the team.
Moderate people impact. Part of someone's working day changes. Requires training and some adjustment time, but roles remain broadly the same.
Tooling required
Things to consider
Password resets, access requests, and software installs typically make up a large share of first-line volume and are the obvious starting point — they are high frequency, low ambiguity, and easy to verify.
Access requests must retain an approval step. An assistant that grants permissions without approval creates an audit finding and a security exposure at the same time.
Deflection rate is a vanity metric if the deflected user just opens a second ticket. Measure resolution without re-contact within seven days instead.
Experiment starter: Take twelve months of ticket history, identify the ten highest-volume request types, and automate the three with the clearest resolution path. Track re-contact rate as the quality gate.
Go deeper in the playbook
Section — Opportunity Identification, including the AI Opportunity Assessment ScorecardSection — The Tooling LandscapeThis is an automation opportunity — see the relevant playbook section for how to approach it.More in IT & Data
AI coding assistance for internal development
Equip internal developers with an AI coding assistant for code generation, refactoring, test writing, and code review, integrated into the existing development environment and review process.
Legacy system documentation generation
Generate readable documentation for undocumented legacy systems — data models, integration points, business logic, and dependencies — from source code, database schemas, and configuration.
Master data quality anomaly detection
Monitor product, supplier, and customer master data for anomalies — implausible values, duplicates, broken hierarchies, missing mandatory attributes — and route corrections to the owning team.
AI Transformation Playbook
Ready to assess your own opportunities?
The playbook gives you the full 150-opportunity directory, scoring tools, and 100+ templates for every stage of an AI transformation programme.