Onboard your AI, not just your people

Your best answers aren’t on the public internet. They’re hiding in SharePoint folders, Confluence pages, Git repos, and the heads of people who are in back‑to‑back meetings. Meanwhile, your AI assistant keeps giving confident half‑truths. The fix isn’t to buy a bigger model—it’s to give your assistant your organisational memory.

Big idea: Treat AI like a new colleague who needs onboarding—sources, standards, and guardrails—not like another search box.

The context gap: why generic AI falls short at work

Let’s be honest: the biggest blocker to workplace AI success is missing context. People waste hours re‑asking the same questions because the assistant can’t see what they can see. The result? Change fatigue. Skepticism. A sense that AI is clever but not trustworthy.

Here’s what’s changed in 2025:

• Company knowledge grounding means your assistant can answer with citations to your files (e.g., policy PDFs, client decks, Jira tickets), respecting existing permissions.

• Persistent context (projects, glossaries, coding standards) lets teams keep shared ground rules in every conversation—no more repeating yourself.

• Data controls (residency, retention, audit logs) make legal and security teams comfortable from day one.

Imagine a new starter asking, “What’s our policy on client data in test environments?” and your assistant replies with a two‑sentence answer, a confidence note, and links to the exact paragraphs in your infosec policy and SOP. That’s the shift—from guessing to grounded.

When context clicks: three high‑leverage moments

Picture three high‑leverage moments across your organisation:

1) Engineering velocity

The assistant knows your coding standards, architectural decisions, and PR templates. It drafts migration steps aligned to your repo’s CLAUDE.md and links to previous PRs that solved a similar issue. Engineers spend time shipping, not scavenging.

2) Client delivery without rework

A consultant asks for a client‑approved definition of “production‑ready.” The assistant pulls the signed SoW line item and the acceptance checklist, then drafts a status update you can paste into Slack/Teams. No ping‑ponging across five tools.

3) Ops that actually scales

HR needs an onboarding plan for a new role. The assistant stitches the role handbook, security training, and facilities checklist into a single, dated plan—complete with links and a short Loom script outline. Day one becomes day done.

Why this works

• RAG done right: Answers are composed from your sources with citations.

• Memory with boundaries: Team‑level context persists; personal details don’t.

• Governance by design: SSO/SCIM, least‑privilege access, and audit trails are standard.

Outcome: Faster decisions, fewer errors, and growing trust—because every answer shows its working.

From idea to impact: your 90‑day plan

Stop treating AI as a search engine. Treat it as an expert colleague you can brief.

Here's a 90‑day plan to get there

Weeks 1–3: Foundations

• Curate 20 must‑answer questions per team (policy, delivery, engineering).

• Connect priority sources (SharePoint/Drive/Confluence/GitHub/CRM). Mirror permissions.

• Create project‑level context packs (glossary, style, coding rules).

Weeks 4–8: Pilot

• Enable citations. Require a source link for every fact.

• Run side‑by‑side tests (assistant vs. human search). Track time‑to‑answer & accuracy.

• Close gaps: add missing repositories; refine chunking; update context packs.

Weeks 9–12: Scale

• Automate governance (SCIM groups, DLP, retention). Turn on audit dashboards.

• Roll out enablement: “how to ask”, “how to check”, “when to escalate”.

• Publish a living playbook; review monthly.

Generation Digital helps UK organisations design this securely—connectors, context, and controls configured to your estate. Book a working session and we’ll map your top use‑cases and ship a pilot plan.

The Bottom Line

Custom AI is onboarding: connect your systems, give it persistent team context, and insist on citations. With that, assistants move from clever guessers to dependable colleagues who speed decisions and reduce cognitive load—without exposing data beyond existing permissions.

FAQs

How do we avoid hallucinations? Ground answers in your content and require citations. Most “hallucinations” are missing context, not model failure.

Is memory safe? Yes—when scoped. Use team/project memory and set sensible retention. Avoid storing personal data.

Do we need a data lake? No. Start with connectors and retrieval. Federate search before you consolidate.

Will this work with Microsoft 365? Yes. SharePoint/OneDrive/Teams are common first connectors.

Custom AI for organisations means connecting internal systems (SharePoint, Drive, GitHub, CRM) to an assistant and adding persistent team context (policies, standards, client info). The assistant answers with citations to your files, reducing hallucinations and speeding decisions—while respecting existing permissions, retention rules, and data residency requirements.

Next steps?

Ready to turn AI into an expert colleague? Contact Generation Digital to plan a secure, UK‑ready rollout.