Understanding what’s the same and what’s different about this moment for AI and work, and how we can build on what we already know, is crucial. If you’re new to AI, I will offer you a map of essential concepts so you can navigate confidently. If you’ve been here for a while, I will reframe the challenge, moving the conversation toward leadership and collaboration rather than technical mastery alone.
After all, how we choose to work with AI, and who we’ll become in the process, is something we still get to decide.
What’s different about today’s AI?
A number of factors have propelled today’s AI from data science laboratories into the center of everyday business conversations. The technology has not only gotten more powerful, but harder to ignore.
Generalists, not specialists:
For decades, AI was used behind the scenes, embedded in models that (for example) predicted customer churn or flagged fraud. Those systems were specialists, usually trained for one narrow task and confined to it. Today’s AI models are generalists. These “foundation models” are vast neural networks trained on oceans of data and capable of being adapted across contexts. The same model that helps a developer write code can also be harnessed to help a marketer write copy or an HR leader write a job description.