How to avoid the AI complexity trap

Artur Debat/Getty Images Developing, deploying, and supporting artificial intelligence can be a daunting venture that calls for an often-confusing array of new skills and technologies. Yet, ostensibly, it's supposed to reduce complexity. Can we have it both ways? Magical or a lot of work? AI can't just be dropped into an organization to start churning out insights -- among many other things, it requires budgeting, rollout, and performance measurement, Chris Howard, global chief of research, explained in a recent video. "AI seems like this magical, really easy thing, and it can do all kinds of amazing things," he said. "But once you start to work with it, you realize that it's actually hard, and there are aspects of it that are really complicated." Also: The best free AI courses and certificates in 2025 Adding to the complexity is the fact that "the technologies themselves are constantly evolving," Howard added. "So they haven't reached a point of stability, at least in the generat ... Read full article.