Key Takeaways
- The year 2025 was marked by the implementation of generative AI in various businesses and individual uses, with both productive and limitations-filled outcomes.
- The AI industry must address three key questions to justify the significant investment surge, including whether generative AI is hitting the limits of scaling, developing viable business models, and responding to the rise of Chinese open-weights AI models.
- The industry will shift towards hard-headed evaluation of AI’s practical reliability and commercial viability, with a focus on more efficient research pathways and neurosymbolic AI.
- US tech giants will need to respond to the increasing popularity of Chinese open-weights AI models, which have gained significant market share.
Introduction to the AI Landscape
The year 2025 was a significant one for the AI industry, with hundreds of thousands of businesses and hundreds of millions of individual users applying the technology in various ways. As stated by the article, "If 2024 was the year of experimentation with generative AI, then last year was one of implementation." This implementation has led to both highly productive uses of AI and embarrassing business blunders, highlighting the limitations of the technology. As a result, the industry will undergo intense scrutiny in the coming year, with a focus on evaluating the practical reliability and commercial viability of AI.
The Limits of Scaling
One of the key questions the industry must address is whether generative AI is hitting the limits of scaling. According to AI researcher Rich Sutton, "the most effective way to build stronger AI was simply to throw more data and computation power at deep learning models." However, Sutton and other researchers now believe that this approach may be running out of energy, both literally and figuratively. As the article notes, "Sutton is one of many researchers who now think that game is running out of energy, both literally and figuratively." This means that AI companies will need to convince investors that they can write smarter algorithms and exploit more efficient research pathways, such as neurosymbolic AI.
Developing Viable Business Models
Another crucial question the industry must address is the development of viable business models as AI becomes more commoditised. The valuations of businesses connected to the technology inflated in 2025, but there will be greater differentiation in the future. As the article states, "Some tech giants, including Alphabet, Amazon and Microsoft, will continue to deploy AI effectively to cut costs and improve existing services that already reach billions of people." However, insurgent AI start-ups, such as OpenAI and Anthropic, still need to convince investors that they can build competitive moats around their businesses. This will require developing innovative and sustainable business models that can withstand the increasing competition in the industry.
The Rise of Chinese Open-Weights AI Models
The third key question the industry must address is how to respond to the increasing popularity of Chinese open-weights AI models. As the article notes, "A year ago, China’s DeepSeek shocked the AI industry by releasing a highly performing reasoning model at a fraction of the training costs of most US counterparts." Since then, Chinese open-weights AI models have gained significant market share, with a study by the Massachusetts Institute of Technology and Hugging Face finding that they accounted for 17% of all downloads. Even Sam Altman, OpenAI’s chief executive, has admitted that his company might have been on "the wrong side of history" by mostly developing expensive, proprietary closed-weights AI models. US companies are now releasing more open models to compete with their Chinese counterparts, but it remains to be seen how they will fare.
Conclusion and Future Outlook
In conclusion, the AI industry is at a critical juncture, with significant investment and implementation in 2025 leading to both successes and limitations. The industry must address the three key questions outlined above to justify the extraordinary investment surge and ensure the long-term viability of AI. As the article notes, "Much of the excitement about AI’s potential is justified. When judiciously applied, the technology can streamline business processes, boost productivity and accelerate scientific discovery." However, both users and investors will need to discriminate between services and businesses that offer real value and those that have simply been surfing the AI hype wave. The coming year will be marked by intense scrutiny and evaluation, but also significant opportunities for growth and innovation in the AI industry.
https://www.ft.com/content/a221f976-6b06-4916-9b87-96e63213d8a2