There’s perhaps no more introspective soul at a conference right now than the AI holdout. At every panel, there are earnest people who approach me after, glancing down at their shoes when they confess that they’re not sure about AI, and haven’t adopted yet. What follows varies in wording but the fundamental core is this: Am I alone to not be fully on board with this? If I open myself up to the idea, am I too late?

When I was first introduced to the software world 28 years ago, ‘quality’ largely meant moving, storing and displaying data accurately. There was almost no weight placed on the look and feel of the application, the user experience, or the performance. If it got the bits and bytes where they were going, it was judged to be good. 

Amid all of the mudslinging between the Department of Defense and Anthropic this week, you may be asking yourself, “Where is this heading?” The high-pitched headlines make it sound like this is (yet another) AI inflection point, and yet for most consumers and businesses, there’s a lot more smoke than fire, at least in the near term.

The hype is starting to cool a bit on AI, and that allows the business world to see a bit more clearly, and recognize that yes, this was another hype cycle and yes, this too shall normalize. But we’ve seen this before.

Despite AI technology that largely works as promised, a striking 95% of generative AI pilots fail to deliver measurable business value according to MIT research. The culprit isn't the tech itself, but rather a classic set of pitfalls that plague enterprise technology initiatives of all kinds.

Over the last few days, the Q3 NVIDIA earnings reportspurred some dramatic gyrations in the stock market.

First, let’s put the earnings in perspective. Yes, chip sales are very strong. NVIDIA beat estimates of EPS by $0.04 per share, $1.30 vs. $1.26 forecast, about 3% better than expected. That’s a big achievement, but it’s not quite the drastic spike some news headlines at the time implied. 

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What captivates visionaries about the latest crop of AI tools is the promise of combining the best of technology (speed, accuracy and consistency) with the best of human ingenuity (compassion, creativity and nuance). That’s what users want and hope for from AI. It’s supposed to be like a computer, but softer. Like a human, but more knowledgeable. The very best we, collectively, have to offer.

Of course, as with any tech revolution, the path to achieve this is not trouble-free.