Venture capital powerhouse Sequoia Capital just dropped a deep analysis telling us where generative AI is headed next. They say we’re moving from “Act 1” of proving the core tech to “Act 2” of actually delivering concrete value to users.
“Generative AI’s first year out the gate—’Act 1’—came from the technology-out. We discovered a new ‘hammer’—foundation models—and unleashed a wave of novelty apps that were lightweight demonstrations of cool new technology.
“We now believe the market is entering ‘Act 2’—which will be from the customer-back. Act 2 will solve human problems end-to-end. These applications are different in nature than the first apps out of the gate. They tend to use foundation models as a piece of a more comprehensive solution rather than the entire solution. They introduce new editing interfaces, making the workflows stickier and the outputs better. They are often multi-modal.”
Why it matters
Generative AI is moving even faster than Sequoia has previously predicted.
The technology now has the ability to generate text, code, audio, and visuals at levels of competency that Sequoia expected were years away. These capabilities will be even more stunning as the core technology becomes more user friendly and solves real business problems.
Connecting the dots
On Episode 65 of the Marketing AI Show, Marketing AI Institute founder/CEO Paul Roetzer broke down for me what we need to pay attention to in Sequoia’s analysis:
1. This current moment in generative AI has been building for decades.
It may feel like ChatGPT and generative AI exploded out of nowhere. But, in reality, a few key factors have come together to produce the perfect storm of innovation.
According to Sequoia:
“Six decades of Moore’s Law have given us the compute horsepower to process exaflops of data. Four decades of the internet (accelerated by COVID) have given us trillions of tokens’ worth of training data. Two decades of mobile and cloud computing have given every human a supercomputer in the palm of our hands.
\In other words, decades of technological progress have accumulated to create the necessary conditions for generative AI to take flight.”
2. Despite the speed of innovation, it’s earlier than you think.
Things are moving fast, says Roetzer, but many underestimate how many people still don’t even know how to use generative AI.
“There are so many professionals who aren’t experimenting with this stuff,” he says.
As Sequoia notes, generative AI applications so far, while impressive, must evolve to solve real problems and create tangible business value.
3. AI literacy is the deciding factor moving forward.
Roetzer largely agrees with Sequoia’s assessment, but notes that at every stage of generative AI, AI literacy is needed to see true mass adoption and value creation.
Despite how powerful these tools are today, the majority of businesses and users out there still don’t fundamentally understand how to leverage the tools in their work.
“None of these things even have user guides,” he says. “We’re just putting out these powerful things into the world and no one teaches you how to use it.”
What to do about it
You have to take charge.
It’s on you to figure out what these tools and this speed of innovation mean to your business and career. Even the smartest people at Sequoia get major things wrong about where we’re headed and how fast we’re getting there.
Start with use cases.
You don’t have to get to generative AI’s “act two” to get massive value out of the technology.
Hundreds of use cases for these tools exist today to improve your workflows, drive efficiencies, solve problems, and increase productivity.
In our own business, even basic generative AI workflows for creating content are saving us easily 100+ hours per month.
“We talk to companies all the time that are doing nothing with this stuff,” says Roetzer.
“They’re just sitting there almost paralyzed by too many things, too many opportunities. Just pick something.”
As Chief Content Officer, Mike Kaput uses content marketing, marketing strategy, and marketing technology to grow and scale traffic, leads, and revenue for Marketing AI Institute. Mike is the co-author of Marketing Artificial Intelligence: AI, Marketing and the Future of Business (Matt Holt Books, 2022). See Mike's full bio.