Common AI
Use Cases

Explore how UK organisations are saving time, reducing costs
and improving customer experience with AI. Work with
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PROCESS AUTOMATION

Workflow automation illustration

Workflow automation

Eliminate repetitive steps so teams focus on higher-value work.

  • Time saved: automatic triage, routing and updates.
  • Fewer errors: consistent rules and checks.
  • Happier teams: less “busywork”.
Practical examples
  • HR: auto-route new-starter forms, collect missing info, book inductions.
  • Operations: raise tickets from emails with fields filled and owners assigned.
  • Finance: request approvals and chase late responses automatically.
Agentic scheduling illustration

Agentic scheduling

Let AI coordinate calendars, rooms and reminders across teams.

  • Less admin: back-and-forth handled automatically.
  • Higher show rates: smart reminders and reschedules.
  • Clear ownership: hand-offs captured in the trail.
Practical examples
  • Sales: books demos across time zones, manages reschedules.
  • Field teams: coordinates site visits, sends directions and checklists.
  • Recruitment: lines up interviewers and candidates, confirms rooms/links.

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DOCUMENT PROCESSING

Document processing illustration

Turn PDFs & emails into usable data

Extract key fields with confidence thresholds and human-in-the-loop.

  • Days to minutes: slash backlogs.
  • Quality: validation rules and audit trails.
  • System-ready: push data to CRM/ERP/case tools.
Practical examples
  • Finance: AP invoice capture with line-item checks.
  • Legal: NDA intake + entity extraction + redaction.
  • Service: summarise long emails and generate next steps.

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PRODUCT DEVELOPMENT

Concept generation illustration

Concept generation

Explore more ideas, faster—then refine the best ones with data.

  • Speed: ideate in hours, not weeks.
  • Breadth: see options you might not consider.
  • Fit: tailor to user needs and constraints.
Practical examples
  • Services: new bundles, pricing, messaging tailored to segments.
  • Digital: AI suggests variants of flows to A/B test.
UX copy & microtext illustration

Build wireframes with ease

Speed up sprints with AI-suggested flows, copy and micro-interactions.

  • Faster cycles: more iterations per sprint.
  • Consistency: tone and components match your design system.
  • Evidence-led: synthesise research to guide designs.
Practical examples
  • UX: AI drafts screens/content blocks from user stories.
  • PMs: instant summaries of interviews to prioritise must-haves.
Synthetic test data illustration

Synthetic test data

Test safely at scale without exposing real customer data.

  • Safe: preserve privacy while testing edge cases.
  • Realistic: control distributions and constraints.
  • Faster QA: unblock teams waiting on data access.
Practical examples
  • QA: generate volumes of cases for performance tests.
  • Analytics: prototype dashboards without live PII.

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ASSISTANTS & CHATBOTS

Customer support illustration

Customer support

Always-on help for common queries, seamless handover for complex ones.

  • Lower wait times and faster resolutions.
  • Consistent answers with source links.
  • Happier agents handling higher-value work.
Practical examples
  • Accounts: billing queries answered from policy docs.
  • Returns: eligibility checks and label generation.
Sales enablement illustration

Sales enablement

Instant, on-brand responses and proposals that reflect the latest info.

  • Win more: faster, tailored answers.
  • Less admin: auto-fill collateral and pricing notes.
  • Joined-up: integrates with CRM/product docs.
Practical examples
  • RFPs: draft responses citing approved content.
  • Outbound: generate call notes and next steps.
Internal IT assistant illustration

Internal IT assistant

Fix common issues fast and guide staff to the right steps.

  • Self-serve: password resets, access requests, FAQs.
  • Reduced load: fewer basic tickets for the helpdesk.
  • Better docs: gaps flagged via unanswered questions.
Practical examples
  • How-to: device setup, VPN, MFA instructions.
  • Policies: explain what users can/can’t do in plain English.

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KNOWLEDGE SEARCH

Enterprise search (RAG) illustration

Enterprise search (RAG - Retrieval-Augmented Generation)

Trusted answers with citations from your own documents and systems.

  • Confidence: source links included.
  • Fresh: content refresh rules keep answers current.
  • Secure: respects permissions (who can see what).
What does “RAG” mean?

RAG — Retrieval Augmented Generation retrieves relevant documents first, then drafts an answer using only that trusted content—citing the sources so you can check them.

Policy & SOP assistants illustration

SOP (Standard Operating Procedure) assistants

Clear guidance that references your policies and procedures.

  • Consistency: fewer off-policy decisions.
  • Speed: instant step-by-step instructions.
  • Audit: who asked what and why.
Practical examples
  • Frontline: eligibility checks with links to the rule.
  • Managers: simplified HR/finance guidance for approvals.
Insights & summarisation illustration

Insights & summarisation

Turn information overload into the key points and actions.

  • Clarity: extract the relevant facts fast.
  • Alignment: share concise updates that teams act on.
  • Focus: next-best-actions instead of long reports.
Practical examples
  • Leaders: meeting packs condensed to a 1-pager.
  • Service: long case histories summarised with risks and options.

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RISK & COMPLIANCE

PII detection & redaction illustration

Confidential detection & redaction

Automatically find and mask personal or sensitive data.

  • Protect privacy and reduce manual effort.
  • Consistent: same rules everywhere.
  • Audit-ready: logs of what was removed.
Practical examples
  • Legal: scrub PII before sharing docs externally.
  • Support: mask personal data in email threads.
Prompt & output guardrails illustration

Prompt & output guardrails

Keep AI within your policies and prevent unsafe responses.

  • Safer: block risky prompts/outputs.
  • On-policy: align with GDPR & internal rules.
  • Visible: clear reasons when blocked.
Practical examples
  • Staff tools: prevent sending data to public models.
  • Chatbots: avoid off-brand or harmful replies.
Model monitoring illustration

Model monitoring

Track accuracy and usage so quality stays high as adoption grows.

  • Spot drift: catch changes in data or behaviour.
  • Improve: feedback loops to fix weak answers.
  • ROI: see what’s saving time and where to scale.
Practical examples
  • Service: alert when answer quality drops.
  • Docs: find content gaps from repeated fallback cases.

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