A leaked internal memo from Google reveals that even the pioneering companies developing Generative AI (GenAI) to create new solutions are questioning their role in the future. In this case, the unrest comes not from any fear of AI’s ability to replace human workers, but instead, whether the combination of GenAI’s open source design and ease of use may eliminate any sort of competitive moat for solutions providers.

The technology and algorithms that underlie GenAI models are complicated, so inventing the basic concept was difficult and time-consuming. But with the heavy lifting complete, creating models and applying them to various use cases is now limited only to one’s imagination. This reality presents a significant challenge to Google and every other GenAI solutions vendor. As the memo states, “We have no moat, and neither does OpenAI.”

Welcome to the newest technology commoditization revolution. Rarely does a day go by without a startup announcing the launch of a new, market-specific GenAI product. The potential for new applications that use GenAI is endless, and the friction and barriers to creating new applications have already disappeared. For GenAI companies everywhere, this rapid uptick in activity begs the question: when the best of everything can be easily duplicated or created, will there be such thing as a ‘competitive moat’ in the future? As daunting as this threat may seem for GenAI providers and traditional business services organizations alike, however, previous technological revolutions can shine some light on what we can expect moving forward.

History may not repeat itself, but it will surely rhyme. In the 1980s, the personal computing revolution opened the floodgates of software development, creating some of the technology corporate leaders of today and making Bill Gates and Steve Jobs household names. Seemingly overnight, software development shifted from being the exclusive domain of a few elites working for major corporations to being open to anyone with enough programming skills to create a software application. Soon after, access to powerful systems, virtualization, and the Internet created further commoditization across the industry, making it possible to create a startup company in the Cloud with little to no physical infrastructure. It was a whole new world.

During each of these eras of change, industry leaders may indeed have felt that their ‘competitive moats’ had evaporated. We know, of course, that the opposite was true. Early movers and adopters were able to capitalize on the environment and excel. They built technology ecosystems and scalable business models. They created massive network effects to rapidly improve the value of their solutions, and they focused on providing superior user experiences. And the momentum companies like Apple, Microsoft, and Amazon created afforded them valuable head starts that enables them to reduce the friction of scaling and focus on the next revenue generator: data management. These early winners remain among today’s tech leaders.

Will GenAI present a different scenario? In this case, the level of commoditization seems even more extreme. Threatened by AI’s ability to deliver outcomes that had always been considered as reserved for the human brain, content creators and creatives are doing whatever they can to protect their livelihoods. When the GenAI-created song, “Heart on My Sleeve” that expertly faked top artists Drake and the Weeknd swept the internet earlier this year, it proved to the world that AI could not only write a song in the style of an artist but even perform in the style of the artist. The music world went into immediate crisis mode. Hollywood is also feeling the pain, with AI restrictions a key negotiating point in the current Writers Guild of America (WGA) strike. Other unions are bound to follow suit. They are right to be worried. Multi-modal Generative AI—which includes text, image, video, voice, and 3D—is still in its infancy, but with the rapid advances and pace of change, it seems imminent that AI will soon be able to tackle every element of project development and delivery—from choosing a lucrative audience and forming a story, to writing a screenplay, planning a shot list, and ‘cast’ synthesized actors to fill each role. It will then be used to render the scenes, edit the movie, and write an original score—all without the need for layers of executives or the teams of creative professionals that traditionally bring a story to life.

Already, brands representing celebrity actors and large franchises like Star Trek, Star Wars, and everything Disney are working to negotiate commissions to help protect their intellectual property. We’ve shifted from a world where human influencers were in control to one where distribution channels like Apple, Netflix, and Spotify rule the day. Next, we may see savvy entrepreneurs create completely fictitious, virtual characters that appeal to the next generation who are seeking brands that reflect their own experiences and identities.

The challenge is accelerating daily. The capabilities of GenAI are leapfrogging past results at lightning speed, quickly democratizing open-source tools like GPT, LoRA, QLoRA, and other Large Language Models (LLMs). Thanks to the massive improvements in training performance enabled by GenAI, the next wave will not be larger models, but greater optimization and specialization to deliver new information in near-real time and to produce customized models for individual users and devices. And as inexpensive, customized models prevail, they will enable a simplified path to much greater data privacy that could lead to de-platformitization and, ultimately, a reduced reliance on big tech names.

If we see the dominance of big tech names drop, tomorrow’s winners will be the companies that build their strategies around embracing GenAI. Their leaders will think much like the prior generation of tech visionaries—Nadella, Gates, Bezos, Musk, and Jobs—who recognized technology’s potential and delivered on that promise. In an environment where technology is open and democratized, those that are able to pinpoint areas to dominate will rise to the top.

The ROBO Global Artificial Intelligence Index (ticker: THNQ) invests in companies across the ecosystem of AI and that are poised to emerge as leaders in this new, dynamic environment. It seems likely that the early explosion of GenAI startups will eventually consolidate as the first-movers use their initial war chests to acquire worthy players to create their own GenAI platform or, at least, to operate like a conglomerate. Some of the companies in the THNQ ETF may take part in these M&As, giving investors access to the results of this growth. Others are key components of the infrastructure that, behind the scenes, is powering the training and deployment of these AI technologies and are more immune to which models ultimately become most successful.

Google’s successful mantra has been “Dominate then Monetize.”  Thanks to GenAI’s open source design and ease of use, Google and many of the other big tech players may no longer have the luxury of time to execute on this approach. If Google’s leaked memo is correct, their competitive moat by already be gone. The result: the door is wide open to lesser-known companies that can quickly build a great ‘poker hand’ of related GenAI capabilities and deliver that platform ahead of the pack. May the best player win!