AI literacy for non-technical teams

AI arrived before the training

Non-technical teams already use AI to summarize, write, research, compare, and prepare decisions. Many companies still treat it as an IT topic, but real usage happens in marketing, sales, support, finance, HR, and operations.

AI literacy is not turning everyone into a specialist. It is giving people enough judgment to use the tool without exposing data, accepting false answers, or automating sensitive decisions without review.

The gap between leaders and teams is risky

McKinsey showed in 2025 that employees are three times more likely to already be using gen AI for more than 30% of daily tasks than leaders estimate. Usage exists even when governance does not.

That is the point: if the company does not train people, the team learns alone. Solo learning often ignores privacy, sourcing, intellectual property, and hallucination risk.

The minimum program content

A good program covers five themes. First, where AI helps and where it hurts. Second, which data should never be entered. Third, how to verify answers and sources. Fourth, how to record usage in relevant processes. Fifth, when to call technical or legal support.

Prompting is a small part. Judgment matters more.

Training needs to live in the work

Generic courses have limited effect. Use real company cases: customer replies, contract review, financial summaries, market research, internal documentation, and demand triage. Each area learns better when it sees risk in its own flow.

Create a clear list of approved tools too. Without it, the company gets shadow AI by default.

Where Diglion comes in

Diglion helps structure AI literacy tracks connected to processes, data, and governance. The goal is making usage more useful and less invisible.

Sources consulted

• McKinsey, Superagency in the workplace: Empowering people to unlock AI's full potential at work, retrieved 2026-07-22.
• OWASP, GenAI Security Project, retrieved 2026-07-22.