Gen AI: The Technology That Broke the Adoption Curve

When Neil Armstrong and Buzz Aldrin landed on the Moon in 1969, their giant leap for mankind was also a giant mass of dependencies navigated over eight long years. Saturn V had to work flawlessly. Navigation systems had to process more than they ever did, and more than some thought they could handle. Tracking stations had to stay in perfect sync. Astronauts had to rehearse every possible failure scenario. Washington had to keep writing more and more checks to meet President Kennedy’s promise of putting a man on the moon. Break one link in that chain at any moment, and the entire mission would collapse.

The success of Apollo 11 was not just about landing on the Moon. Success was the flawless alignment of thousands of bespoke parts, hardware, software, politics and people for a single moment in history. It was the orchestration of dependencies coming together at exactly the right time.

Half a century later, SpaceX and Blue Origin proved that spaceflight doesn’t have to be that precarious.  Neither eliminated the complexity of space travel, but they collapsed many of the dependencies that once made space missions so fragile. Reusable rockets meant no new Saturn V for every launch. Modern computing automated what once required astronaut overrides. Vertical integration reduced points of failure. Even the business model shifted to scalable commercial platforms with business models instead of government checks. (Although they get some of those, too).

Apollo 11 was the miracle of dependencies aligning. SpaceX and Blue Origin turned miracles into repeatable outcomes by collapsing them.

Now, Gen AI is doing the same thing for innovation itself.

Shattering Adoption Curves

Three years ago, ChatGPT didn’t exist outside the labs of OpenAI. Today, it has 700 million users worldwide. That’s 16.5% of the world’s smartphone users.

No technology in history has moved this fast. The personal computer took nearly two decades to reach half of American households. Broadband slogged through a decade of cable trenching before hitting majority adoption. Smartphones needed six years after the iPhone launch to reach 50% penetration. Mobile wallets took a full decade to break the same threshold.

Gen AI didn’t just break these records. It shattered them.

ChatGPT reached 100 million monthly users in just two months, the fastest and steepest adoption curve of any consumer application ever recorded. By mid-2025, three years after its commercial launch, 34% of U.S. adults had used ChatGPT directly, roughly doubling in a single year. But the real kicker? A Gallup survey conducted in November 2024 found that 99% of U.S. adults used at least one AI-enabled product in the past week, yet 64% didn’t even realize they were using AI.

That makes Gen AI anything but another technology wave.

It will collapse the dependencies that slow innovation.

It will fast-track change regardless of whether businesses are ready because their customers and their workforce are already there.

It will shatter and steepen the adoption curves of innovation across every sector of the economy because it will slash the time required to create and bring breakthrough ideas to market.

The Technology Dependency Trap

Every transformative technology before Gen AI had to solve multiple problems simultaneously before consumers and businesses could embrace it.

The personal computer needed affordable hardware, user-friendly software and household readiness to get traction. IBM launched the PC in 1981 five years after the first Apple computer. It still took until 2000 for just half of U.S. households to own one. That was nearly two decades of incremental progress, one household at a time.

Broadband’s story was even more brutal. DSL emerged in 1999, but adoption crawled through single digits for years. By 2007, fewer than half of U.S. households had high-speed connections. Cyber Monday was dubbed a retail shopping sale day in 2005 because so many people hopped on their computers at work the Monday after Thanksgiving to snag holiday deals.

Its 50% milestone didn’t arrive until 2008. It would take a total of two full decades for adoption to plateau above 90%. Every mile of fiber optic cable had to be trenched. Every neighborhood had to be wired. Every installation required a technician visit. Broadband adoption could only move as fast as construction crew schedules and manpower allowed.

Smartphones seemed different when Apple launched the iPhone in 2007. Here was a breakthrough in form factor and usability that felt magical from day one. But even the iPhone was trapped by dependencies which delayed adoption. Consumers had to sign expensive carrier contracts, buy new expensive hardware, initially live without many apps and with a fairly unusable phone until 4G technology made it more reliable. Smartphone adoption didn’t cross 50% until 2013, six years after launch and five after the launch of the App Store and Google Play. By 2019, adoption climbed past 80%, only recently plateauing above 90% of U.S. adults.

Mobile wallets faced the most painful dependency trap of all, and they still do.

Google Wallet launched in 2011, Apple Pay in 2014. Both promised to revolutionize how consumers pay for things in the physical store. But wallets required a perfect storm of coordination. Merchants had to install NFC terminals, banks had to enable tokenized credentials in those wallets so that consumers could use them with their preferred cards, and consumers had to see value in changing their checkout habits.

For years, adoption grew slowly from the 20% to 40% range. It didn’t break 50% until 2021, a full decade after Google Wallet’s launch. Even today, only roughly 70% of U.S. consumers have used a mobile device to pay in the past year.  Far fewer do that monthly or daily, with wallets accounting for less than 10% of all transactions.

The Great Collapse

Gen AI changed everything by changing nothing.

All Gen AI needed was a web browser or mobile app download. No new hardware purchases. No infrastructure buildouts. No merchant upgrades. No carrier contracts. Just billions of people with phones or computers and a decade-plus of experience in using apps and digital products at the ready to give it a test run.

The models took a page out of the catalyst framework to build a critical mass of users and get better from day one. It made basic access free so that consumers would play around with it, and their models could learn and improve.

The dependencies that once created friction didn’t exist because access was made available to anyone who wanted to try it. Gen AI models asked consumers to bring nothing more than their own curiosity to their virtual front doors.

The Gen AI adoption curve isn’t a slow climb. It is a vertical line, powered by what people can do with it, not by the systems holding it back.

Flipping the Technology Script

The pattern that defined every other technology wave, with business adoption first and consumers later, has been turned on its head with Gen AI.

Personal computers started in corporate offices before landing in homes. The internet was a research and business tool before becoming a consumer platform.

Gen AI breaks that cycle. It didn’t wait for businesses to make the first move. Consumers jumped in headfirst, experimenting, adopting and building it into their daily routines long before companies began  integrating it into theirs.

It was the consumer that set the expectations businesses must now race to meet.

Workers who use ChatGPT at home ask why their employers don’t offer the same tools or bypass IT entirely by using LLMs anyway. PYMNTS Intelligence data confirms this consumer-first shift. While both consumers and businesses worry about privacy, security and AI accuracy, businesses face a maze of additional hurdles that include integration, compliance, data governance and vendor risk. Consumers average only 2.2 concerns, and nearly a third see none at all. Businesses, on the other hand, see more than twice that number.

For consumers, adoption is frictionless and personal. For businesses, it is an organizational transformation moving at warp speed at the same time other priorities vie for dollars and resources. Yet the workforce already sees value. The PYMNTS Intelligence survey finds that 92% of consumers say that while they could technically do their jobs without Gen AI, it would be slower (46%) and harder (20%).

The Value Proposition That Changes Everything

That expectation is what makes Gen AI fundamentally different from every technology that came before.

Gen AI isn’t perceived as a marginal upgrade. It reimagines productivity. Workers report saving hours on writing, analysis and coding. Analysts complete projects in days that once took weeks. Developers spend more time problem-solving. Customer service teams handle complex cases with less back and forth. The technology doesn’t just make doing things faster, it expands what is possible within the same amount of time.

Once people experience that value, there’s no going back. And they don’t just want those gains for themselves. They expect the businesses they buy from, bank with or seek service from to be just as smart as the assistants they use every day. Interactions that feel slow, generic or “not as smart” no longer meet that standard.

That shift creates intense business pressure. Companies that fail to keep pace risk looking out of step with both their workforce and their market. The race is now about matching consumer expectations for businesses that think and respond as intelligently as the AI assistants shaping their daily lives.

More important, unlike past waves, the adoption pressure doesn’t come primarily from competitors. It comes from employees, customers and stakeholders who have already experienced AI and expect organizations to deliver the same intelligence and responsiveness.

That’s why Gen AI as an enabling technology represents more than just faster adoption. It reduces the dependencies that once slowed innovation’s grip. It promises productivity gains across white-collar work, efficiency in supply chains, breakthroughs in research and new ways for brands to connect with consumers. Healthcare firms can run more experiments in parallel. Retailers can test personalization strategies at scale. Financial institutions can iterate on customer experiences in real time.

Gen AI has steepened its own adoption curve because it bypasses the layers of coordination, physical buildouts, and years of incremental effort that governed how quickly innovation could scale. It opens direct pathways to value. Consumers feel the benefits and raise their expectations almost instantly. Businesses integrate the tools and discover that innovation spreads more quickly when the friction points are gone.

Their own innovation curves will steepen as well.

The Return on Innovation

The companies that thrive will be those that move fast enough to meet expectations while avoiding the missteps that erode trust.

PYMNTS Intelligence finds nearly six in ten middle market firms already using Gen AI strategically to improve products, reimagine customer experiences, and test entirely new business models.

Roughly half report embedding Gen AI into core operations, from marketing and customer service to compliance and risk management. Importantly, the focus is shifting away from measuring ROI in cost savings alone. Executives are looking at the return on innovation: the ability to experiment faster, explore more ideas and create new sources of value.

That mindset is why its adoption and innovation will accelerate. Businesses are aligning data strategies, building governance frameworks and training their workforces so they can scale Gen AI responsibly. They are adapting not only to meet consumer expectations, but also to unlock opportunities consumers have only begun to imagine.

Even Walmart’s CEO Doug McMillon, who oversees more than two million employees, has said that Gen AI will change every job. Not some jobs. Every job.

And that will happen at every company. The change won’t just affect jobs.

What’s Next

Apollo 11 showed us what happens when thousands of dependencies align for one extraordinary moment. SpaceX and Blue Origin demonstrated what happens when collapsing dependencies makes extraordinary outcomes faster and repeatable.

Gen AI shows what happens when dependencies can disappear. Or be significantly marginalized.

Consumers leapt first. Businesses are now building to make that leap lasting. The return is not just efficiency. It is the acceleration of innovation itself. The force that will keep the adoption curve steepening across every sector of the economy. And faster than anything that came before.

What do you think?

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