“Where’s the beef?!” Has the Technical Beef of AI Arrived Yet?
Where are the real results of AI?
“Where’s the beef?!” This is a throwback to a series of commercials from the 1980s for the U.S. restaurant chain Wendy’s, when many hamburger chains were offering smaller portions of beef for the same price—much to the frustration of customers. Today, we find ourselves asking a similar question about the advancements in artificial intelligence (AI). It often feels like we’re still waiting for that promise of something truly new and better to actually show up in our lives—at home or at work. Whether you’re part of a company building AI, a firm trying to use it, or simply someone trying to make sense of it all, it’s easy to wonder: “Where’s the technical beef?!”
Lessons from past technological revolutions
To put it in context, the revolution we’re living through with AI is quite similar to previous tech revolutions—while at the same time being unique in its own way. The famous Gartner Hype Cycle, often brought up in meetings or online to emphasize how overhyped AI is, fails to capture some of the critical differences and nuances AI introduces for businesses, economies, and individuals.
Earlier revolutions—records, phones, computers, and the internet—all came with big misconceptions about the role they would play in our lives. Take audio records, for instance. Now mostly relics you’ll spot in hipster enclaves like Roma Norte in Mexico City, Mission District in San Francisco, or Le Marais in Paris, they were once thought to be useful only for professionals sending voice notes across cities. Few imagined they would be used to record music, reshape the live music industry, or lay the groundwork for what we now know as Spotify—over a century later.
The internet followed a similar path. Initially dismissed as niche, a fad, and more hype than reality, it turned out to be one of the most significant revolutions in history—spurring the development, use, and widespread deployment of increasingly advanced phones, computers, and IoT devices. In fact, whether you're reading this on your phone or computer, you're only able to do so thanks to the internet. That may seem obvious now, but it wasn’t so clear in 1993—the year the internet opened for commercial use.
Today, with AI, we are still in the early stages of discovering what it can and will do for us. And just like it was hard to see the opportunities in the early ’90s, it’s incredibly difficult to predict how the AI landscape will evolve in the years and decades ahead. That’s why everyone keeps asking: “Where’s the beef?”, “Where are the results?”, “When will tomorrow finally arrive?”
The key difference with AI: productivity and replication
What sets AI apart from past revolutions is that these systems don’t just enhance our productivity—they also have the capacity to replicate many of the things we already do: writing, designing, drawing, composing music, analyzing data, and more. And they do it far more efficiently—in terms of time, cost, and quality. We are in the middle of an entirely new kind of revolution, unfolding around us every day. That’s why it’s critical—for you, your business, and your industry—to start thinking about how to prepare and adapt.
In future articles, I’ll dive into Artificial General Intelligence (AGI), quantum computing, quantum AI, and other advanced emerging technologies that will shape the near future faster than most expect. We’ll cover the business side of these technologies, the opportunities and challenges they bring, and the cycles of expectation that surround them. So stay tuned.
The time to master AI is now
As we close out 2024, the adoption rate of AI across most industries remains under 10%. Many companies in tech hubs like San Francisco, New York, London, Berlin, and Singapore are already paying $20 a month for top-tier AI models from OpenAI, Anthropic, or other leading firms. But once you move beyond these capitals, many companies aren’t even spending the equivalent of three Starbucks coffees a month to access the best tools available to most users—and still wonder: “Where’s the beef?!”
To get the most out of AI, you have to engage with it and start working hands-on to uncover your competitive edge. Build a solid AI strategy, define clear objectives, and think through how you want to position your business as AI continues to evolve. A lot of people online make working with AI look easy—but what you don’t see is the time and effort they invest in learning how these systems work, how to write good prompts, and how to navigate the subtleties of each platform. Don’t be discouraged. It gets easier with practice. Trust me.
So, what can you do to get more value from AI in most practical scenarios? Sure, if your needs are highly specific, you’ll probably want to bring in an AI firm or build an internal team. But these suggestions will help you get started—and maybe even cut back on your coffee budget:
Identify a few use cases where AI could benefit your business.
Set aside a small budget and a tiny team (maybe just you, at first) to run short sprints building something using OpenAI, Anthropic, or whatever tool you prefer.
Give yourself a timeline—say, one month or six weeks—to deliver, test, and iterate.
As things progress, involve key people to identify the solutions worth scaling.
Brag to your friends, get promoted, and send me a thank-you email.
We’re only beginning to understand what AI can do. We’re not halfway through the journey—nowhere close to the end. This is the moment to start experimenting and seizing the opportunities that AI offers—in Latin America and beyond.
So where’s the beef? It’s in the fridge, waiting for you to cook it. Because, in the end, your future is in your hands. Just saying.
Originally published in Spanish for Fast Company Mexico:
https://fastcompany.mx/2024/09/17/donde-resultados-inteligencia-artificial-opinion/
