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AI content operations

A governed content engine that uses AI to research, draft and repurpose at scale, with brand voice, fact-checking and human sign-off built in.

Typical timing
6–8 weeks
Engagement
Fixed scope
Delivery framework
User researchDiscoveryAlphaBetaLive

Produce more high-quality content without diluting the brand or publishing errors. We design a content operation where AI handles research, first drafts and repurposing across formats, while editors own accuracy, voice and final approval — with clear disclosure where AI was used.

  • Content demand across channels outstrips the team
  • Staff use AI tools ad hoc with inconsistent results
  • Concern about accuracy, originality or brand voice in AI-assisted content
How it runs

Activities, step by step

The plan follows our delivery framework. Steps that do not apply to this kind of work are left out rather than padded.

  1. 02 · Discovery2 weeks

    Operating model

    • Content supply chain mapped from brief to publish
    • Where AI helps and where humans must decide
    • Tooling, voice guidelines and review standards
  2. 03 · Alpha2–3 weeks

    Build the engine

    • Brand voice and knowledge loaded into AI tools
    • Templates and workflows for priority formats
    • Fact-checking and approval steps
  3. 04 · Beta2 weeks

    Pilot

    • Pilot production against quality scorecards
    • Time and cost per asset measured
    • Workflow refined
  4. 05 · LiveOngoing

    Scale

    • Rollout across content types and teams
    • Quality and performance monitored
    • Guidelines kept current

Deliverables

What you keep at the end.

  • AI content operating model and policy
  • Configured tools, prompts and templates
  • Editorial review and fact-checking workflow
  • Pilot quality and productivity report

Outcomes

What it is built to change.

  • More content, faster, at consistent quality
  • AI use that is governed and disclosed
  • Editors focused on judgement, not first drafts