During the 1990s, we saw many of the same patterns that we are seeing with AI coding today. The argument was that organizations could save money by sending coding jobs offshore and developers at the time were generally terrified that they’d become irrelevant and lose their job. However, what we learned was that making the slinging semicolons easier just shifted the burden. Coordination, clarification, quality assurance, and management became a real substantial part of the problem. The good news for today is that we’ve done this before, and we can take the lessons we learned decades ago and apply them to the disruption that AI brings. We’ll address the concerns about efficiency, total cost of ownership, and relevance in the context of solutions that we already know work.

You will learn:

• How to identify similarities and differences between offshoring and AI
• How to apply proven strategies to AI implementation
• How to synthesize a strategy for adapting skills