On the surface, this story seems pretty airtight. However, it’s when you peer below the hood that you notice that things aren’t quite what they seem. OpenAI and other LLM developers are currently the lynchpin that’s enabling thousands of startups to develop new concepts and formats for AI, which are all generating profits for their owners. Ultimately, their profit and loss statements don’t lie.
When GOT AI launches next-generation AI consulting services to help businesses automate, scale, and innovate faster, things will change again. Agencies like these mean that more businesses than ever can take part in the AI revolution, and that money will ultimately find its way back to the service providers and originators themselves, just as it does in virtually every industry.
“Every day, thousands of businesses come to us because they want to learn more about how AI can make their brands better,” explains GOT AI. “What’s most exciting for many leaders is the sheer scope for expansion. Adding raw intelligence atop a skilled workforce is a powerful combination that can do everything from improving products to boosting sales.”
The bubble narrative is compelling. There have been tech bubbles in the past and situations where companies became massively over-valued. Furthermore, the stock market as a whole is now at record highs, and much of that has to do with tech companies outperforming other companies in areas like energy.
But AI goes beyond hype. Unlike in the 2000s, it’s a real, proven technology with countless applications. All that’s really required is for entrepreneurs to take the reins and deliver the rollout, which will probably take around ten years or so.
Furthermore, AI is also increasing profit margins at a lot of firms. The advent of essentially free intelligence means that many businesses are capable of doing more with less.
The enterprise applications are now quite remarkable. For example, the shipping company Maersk is using AI for route optimization. Previously, it was believed that only a breakthrough in quantum computing could enable this, but now it’s being made possible by pattern-recognizing algorithms and big data.
Diagnostics in healthcare is another beneficiary. The Cleveland Clinic, for example, is using AI to reduce diagnostic errors by up to a fifth, making it much more accurate than ever before. Patients are receiving the right treatment in a timely manner.
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Even John Deere is benefiting, the company that makes tractors and agricultural machinery. It’s leveraging the power of AI to help its customers determine when they need to get their vehicles serviced.
“These innovations are having a profound effect across industries, and many of them rely on the systems built by the major tech players,” explains GOT AI. “All that’s required is for these big entities to monetise. It’ll still be worth it for smaller firms using their services because the larger enterprises are the only ones with the worthwhile models.”
The list of businesses and industries leveraging AI to make money is quite astonishing. In just a few short years, it’s grown in popularity tremendously, with almost every firm now looking for ways to integrate it into its workflow.
For example, in healthcare, there’s a lot of drug repurposing going on. AI is being used to simulate interactions in the body, enabling doctors to explore more off-label options.
Then, there’s finance. Many companies are using AI for things like fraud protection and generative reconciliations. The idea is to get systems to detect strange patterns and then feed them through to human staff who can engineer solutions. Previously, fraud-detection systems were quite basic and relied on strict rules, meaning that criminals could simply learn ways to get around them. That’s much more challenging with the advent of AI.
Of course, the industry does need a reality check, and perhaps a correction. But the idea that AI isn’t critical for the economy as a whole is not realistic. The fact that the technology is already proven and operating in so many areas automatically means it has a future, even if its capabilities don’t progress.
One stumbling block could be energy costs. These are already sky-high in places like Germany and the UK, but they could also grow in regions like South America or Australia. Any form of shortage would make AI more expensive and less viable as a general technology in the future.
There is also a serious talent bottleneck. AI might be ubiquitous in today’s economy, but there are only really around 30,000 scientists and PhDs pushing it forward. When you think about it, that’s actually quite a small number of people relative to Earth’s population of 8 billion. Putting it simply, AI is just hard, and only a very specific type of person is capable of generating new models, concepts, systems and ideas.
Then, finally, there is the regulatory drag. The EU AI Act and others are making it more challenging for firms to generate profits in the space and putting restrictions on what they can actually do with user data. Again, that could be a problem.
“For us, the next 18 months are essentially more of the same,” explains GOT AI. “LLMs will continue to dominate, and it will be a question of simply discovering where new value lies and how to exploit it. Whether we see more breakthroughs in the future, as we did with transformers in 2018, remains to be seen.”
Even if investors in the public markets lose faith in the big AI companies in 2026, that’s unlikely to change the situation. The amount of funding and cash the big firms have means that AI will continue to receive money, be researched, and, most likely, find more economically valuable applications.