The Year AI Goes Mainstream

March 16, 2023 / Ben Bajarin

We are witnessing an inflection point for AI. Before the release of ChatGPT, much of the debate was centered on what would cause AI to move beyond the monotony of backend system processes, automation, and other things there were largely invisible to end customers and cause us to have fundamentally different interactions with computer systems and software. That answer turned out to be ChatGPT-3.

No, this is not a fad. But I won’t sit here and tell you the coming boom will be sustainable. There will be a ton of experimentation. There will be a ton of misuse of the term AI (something for later analysis). Still, we are in a traditional boom period where we will see an increase in experimentation, innovation, creativity, and more which will end up rooting many new behaviors and expectations. We are about to witness a Cambrian explosion of AI-infused apps and causing us to reconsider what we knew was possible with computers and develop a new mental model of the future.

Why Is This Not a Fad?

I was fortunate enough to have some early access to ChatGPT-3. Being able to experience it before anyone talked about it was a benefit for the behavioral researcher in me. When I had the chance, I let friends and family experience it for the first time but gave them no instructions on what it was or how to use it. I observed as each person tried to figure it out, looked at the prompt box, and inevitably tried to use it like a Google search. Some queries had a range of success, and some did not, but most quickly realized this was not a traditional search engine. I let them all experiment and see how ChatGPT is conversationally engaged. Still, almost no one noticed that it remembered the context of the conversation or had hidden powers of hyper-productivity.

With some guidance, I said, “ask it to write a 500-word essay on something you are learning or curious about.” It was at that moment everything changed. Not only did I observe universal facial expressions of shock and awe and many verbal “holy crap” moments, but once some of these hidden powers became clear, the floodgates of how they interacted with it and what they tried (even if it failed) changed dramatically. The usage went from using it like a traditional search query to figuring out what it can’t do and how far it can go in sorting through and presenting information of all types.

This is not a fad because, ultimately, what the masses experimenting with ChatGPT-3 showed us was that people gravitate to and get excited by tools they encounter that will save them time and make them more efficient. This is precisely what we see with many initial market successes around generative AI. This enabling technology holds the power to make us more efficient, productive, and creative, ultimately letting us get more done in less time. This is why some form of generative AI will likely come into nearly every person’s workflow around creativity and productivity in some form or function. This is evident as Google is infusing generative AI into Google Workspace. Microsoft is infusing generative AI into areas of Office 365 with Copilot. And many more leading apps and services will likely integrate a form of generative AI soon. 

Every current value proposition around generative AI that gets the most excitement is around workflow automation. We are observing AI-infused apps and services that eliminate monotonous steps in our workflows and get us to our end goals more quickly and efficiently. AI also will enable us to be more productive AND get more out of the apps or services we use today. In today’s announcement of Copilot into Office, Microsoft stated that “most users of powerpoint only use 10% of the features. Copilot will help unlock the other 90%.” This entire movement is about helping make humans more productive and efficient and even augment some human limitations. That’s why when the dust settles on this Cambrian explosion, apps, and services that hone in and emphasize speedier and more efficient workflows will have the most impact and staying power.

A New Software Developer Cycle

Interestingly, our current cycle feels like the early app stores for smartphones. Almost daily, we see a new app/service pushing the limits of what we thought was possible and getting us excited about something that enables us to do something new, faster, better, etc. 

One of the more interesting questions this raises is who will capture most of the value during this new developer cycle. Microsoft, via Azure, appears in the lead as many of these apps and services use Azure and OpenAI as a staple of their generative AI strategies. Google recently released its own set of APIs looking to bring developers into the Google Cloud backend. Amazon is working with Hugging Face as an enabler of AWS for developers wanting to infuse their apps or services with generative AI. But will this be primarily a cloud software revolution, or will there also be a client-side component for developers? Meaning that Andriod, iOS, macOS, and Windows will evolve their APIs to support continued client-side development for apps and services that utilize this new generation of AI technologies. Qualcomm’s demonstration of Stable Fusion running on Android is an example of how models can benefit by running locally on the device. 

Other questions arise amidst this next developer boom. Will marketplaces remain the same, or will new players emerge that help us aggregate and discover new apps or services? Are we back into a platform race dominated by only a few players who can afford to control and maintain massive foundational models? How do the major players foster and develop this new technology responsibly? Is it possible that the pace of innovation will be so fast around generative AI and future breakthroughs that customers will have trouble keeping up? Another question arises around economics. Will these tools only be available to those who can afford them thus creating a productivity gap between haves and have-nots? We are in an exciting period where are significantly more questions than answers.

Ultra Quick Diffusion Into the Mainstream

Lastly, generative AI and future iterations and innovations around generative AI will diffuse extremely quickly. One primary reason is that this technology is reachable with devices the masses already own. Whether functional applications of AI/generative AI comes as a feature to existing software suits or as the cornerstone of entirely new apps and services, the masses can readily adopt them on computers of all shapes and sizes, which they already have on their desks or pockets. Meaning from day one, the addressable market is billions of people. This is a crucial reason why ChatGPT raced to 100m people experiencing the technology in the shortest amount of time of any technology in history, as no new hardware was required.

This ultra-quick diffusion into the mainstream creates both opportunities and challenges. This technology can play a role in solving real pain points for people today. Saving time, being more efficient, getting more done, and more are things that will drive the adoption of these new AI-enhanced solutions. But, in such early days, we also run the risk that the excitement level, or specifically the expectations or hope of the end market, falls short. These technologies have a great deal of promise but also a wide range of limitations, making it a challenge for companies to integrate and put the proper guardrails around to protect themselves and their customers.

Just the Beginning

With all we are seeing, Microsoft deeply embraced generative AI into all of Microsoft Office, Google embedded it into Workspace, and 100s of new apps and services are coming out weekly/monthly. It is wild to think we are only in the first inning of this AI Cambrian explosion. I’m glad companies emphasize the importance of responsible AI, and that trend must continue.  There is much work to be done but a lot of excitement justifiably so.  As I see all that is being announced as generative AI is integrated into all forms of computing, it hits me that all we see around generative AI feels like magic. We see a broad sweep of said Arthur C. Clarke quote almost daily. “Any sufficiently advanced technology is indistinguishable from magic.”

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