Thought Piece: The real AI story of 2024

The $3T reality check nobody saw coming...

Author

Matt Leta
December 18, 2024

Hi there,

Let's be honest, 2024 wasn't the year AI conquered the world. It was the year AI hit the gym, got a reality check, and finally started doing the hard work of growing up.

Early 2024 kicked off with a bang. Claude 3 launched, Tesla was promising self-driving taxis, Google was showing off Project Astra, and industry leaders couldn't stop talking about how AGI was just around the corner. But then something interesting happened.

By mid-year, tech companies were sweating over their power bills as AI's appetite for energy started straining the grid. The industry discovered that building artificial general intelligence wasn't just about clever algorithms - it was about figuring out where to put all those hot, power-hungry servers. NVIDIA rode this wave to a staggering $3 trillion valuation, as the enterprise value of AI companies hit $9 trillion overall, proving that sometimes the boring stuff (like making really good chips) matters more than the fancy AI promises.

Here's what made 2024 different

The industry finally started listening to its critics. When people raised concerns about energy use, security risks, or infrastructure limitations, they weren't brushed off as doom-mongers. Their insights helped shape a more practical approach to AI development. Just look at the numbers from the McKinsey survey. 72% of companies were using AI, only 18% had proper governance in place. The industry took notice.

This maturation of AI wasn't just happening in big tech labs. As someone who witnessed this transformation firsthand, I saw it reflected in how businesses and leaders were approaching AI adoption. My book "The LEAP Guide," which hit #1 Amazon Bestseller in September, captured this exact moment. It was when companies were learning that innovation doesn't need to be revolutionary to be effective. The book's success showed how hungry organizations were for practical, grounded approaches to AI implementation.

The story got even more interesting in the fall. Meta launched Llama 3, challenging the status quo of closed AI systems. Anthropic shifted from their ultra-cautious stance to a more balanced approach. Not because they stopped caring about safety, but because they realized that real-world testing and careful scaling might actually be safer than endless theoretical safeguards.

Chinese AI companies showed us something fascinating too. Despite export restrictions meant to slow them down, they kept making progress. By year's end, models like DeepSeek, Qwen, and Kling were challenging the top players, proving that innovation finds a way, even when the path looks blocked.

November brought more surprises. Anthropic announced breakthroughs in self-correction and reasoning capabilities, challenging the notion that AI was hitting a wall. Meanwhile, the political landscape shifted with potential implications for Big Tech and AI development that we'll be feeling well into 2025.

Looking ahead, the industry faces some tough questions. Can we build the infrastructure AI needs without wrecking the environment? How do we make AI truly practical rather than just impressive in demos? Can regulations keep up without killing innovation?

The lesson from 2024 is clear

AI's future isn't about magical breakthroughs or scary robot overlords. It's about rolling up our sleeves and solving practical problems. Both through Future Works' transformation projects and the overwhelming response to "The LEAP Guide", I've seen how organizations are craving this balanced, practical approach to innovation.

Maybe this isn't the AI revolution people dreamed about. But it might be something better. It’s the beginning of AI growing up and getting a taste of the real world. And honestly, that's probably exactly what we needed.

See you next year,
Matt

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