”To study music, we must learn the rules. To create music, we must break them.” Nadia Boulanger
There are probably several people in your team that are already using generative AI tools to help them get stuff done. It’s not difficult to find online tutorials that help you get started.
The difficulty for organisations is in somehow coordinating the use of new tools across and between teams. This is where basic training can help, particularly when it’s focused on the specific needs and behaviours of your team, rather than something generic.
Basic AI training
Things change fast with genAI. Accept that you can’t possibly keep up to date on all the latest developments and tools. It’s fine. Everybody’s in the same boat.
Apart from “Nigel”, who does nothing but study the latest updates all day every day. We don’t see much of Nigel these days. I should probably check in on him.
Once you’ve accepted that you can’t know everything, you can move on with some basic training for the team.
Basic AI training should cover some or all of the following:
- Understanding AI: Teach your team the basics of how AI works and what it can do. As the capabilities continue to develop, you’ll want a way of doing a “refresher” every so often.
- Hands-On Practice: Nothing beats practical experience, so provide practical training with specific AI tools. Again, refreshers will be necessary as the tools develop. This is typically the most fun part of the training.
- Prompting: The need for clever prompts is likely to diminish as the language processing and reasoning capabilities of the tools mature. But covering prompting does make it much easier for people to appreciate various genAI use cases for their role or team.
- Evaluating Results: Train staff to critically look at AI outputs and check for accuracy. I’d say “critical thinking” here, but I’m bored with reading it everywhere.
- Ethics in AI: Discuss the ethical use of AI, including issues like privacy, IP, and bias. You’ll want to make sure everyone is clear about the specifics of what is and isn’t acceptable when using AI tools.
- Integrating AI: Demonstrate how AI can fit into existing workflows. This is where it’ll come to life for many people in the team. When they see some previously laborious or onerous task become much easier, they’ll probably start thinking about other applications too.
There’s no one-size-fits-all when it comes to team training for genAI. It’s also something you’ll need to revisit and update intermittently, purely because of the speed of change.
If you’re already preparing your team for a future with AI, I’d love to hear how you’ve approached it.
