Every technological revolution follows a pattern: an installation phase typified by eruption and frenzy, followed by a more stabilized period of deployment seeing steady growth to maturity. It’s a concept studied and introduced by researcher and consultant Carlota Perez as early as 2002.
At the start of these technological revolutions, the focus is on building the infrastructure. It’s the phase where early adopters reap huge rewards by developing the tools and platforms for future innovation. In the AI era, dominant players like OpenAI, Anthropic and Google laid the groundwork by creating powerful large language models (LLMs) and multimodal systems.
But AI’s initial Big Bang is almost over. It’s now entering a new phase. As the cost of AI infrastructure falls and access to these tools becomes more widespread, the competitive advantage will shift from owning infrastructure to applying new tech in novel ways.
This is not just theoretical. It’s a real-life pattern I lived as co-founder of Vungle, a mobile advertising platform that emerged within the mobile app economy. In 2011, when we started Vungle, mobile app development was still in its nascent stage. It was anyone’s game. We saw that current advertising models hadn’t yet adapted to mobile-native experiences. So, we addressed the pain point through high-quality video ads designed specifically for mobile games and apps. By the time mobile advertising became ubiquitous, Vungle was already well-positioned, which ultimately led to our $780 million acquisition.
If — as philosophy and Perez’ model suggest — history repeats itself, the next events in AI will play out as in the pattern of the 2010 mobile app revolution. When Apple launched the App Store, early adopters like Instagram, Uber and WhatsApp saw an opportunity to rethink entire business models around mobile-first user behavior. They were among the first to recognize how smartphones could change user interaction, distribution and monetization. They were also the biggest winners of the mobile app boom.
What’s to Expected Given AI’s growth
Just as having a mobile app is now table stakes for most businesses, AI-powered features will soon be expected rather than optional. Integrating AI for efficiency will be commonplace, not a differentiator. The real winners will be those applying AI in ways that make entirely new experiences possible. This is why the application layer of AI will create the most long-term value.
And just as most mobile companies that saw massive success weren’t infrastructure providers but companies that leveraged mobile effectively, the most successful AI companies won’t be building new AI models. They’ll be using AI to solve critical problems in industries like healthcare, finance and enterprise SaaS.
What IT Leaders Need to Do (and Fast!)
So, how can organizations stay ahead in this next phase of the AI revolution?
Start approaching AI as an enabler. AI’s time as a mere feature or tool to automate existing processes is done. You should go from “How can AI automate our tasks?” to “How can AI drive new business models?” A report from McKinsey said that corporate AI use-cases could yield long-term added productivity gains as high as $4.4 trillion. The same report shares three questions for leaders navigating this AI-centered future:
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Is your AI strategy ambitious enough?
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What does a successful AI adoption look like for your organization?
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What skills define an AI-native workforce?
Prioritize AI-native products. Businesses should adopt — or better yet, pioneer AI-native solutions that fundamentally redefine user experiences and decision-making. Take Boardy for example. As early as we are into AI’s deployment era, it’s already found a niche (professional networking) to disrupt (by using AI to facilitate smarter, more personalized introductions), automating what was once an entirely manual process.
Invest in talent with AI-first thinking. Now’s the time to launch AI upskilling initiatives, such as AI certification programs or company-led AI boot camps. Hiring efforts should seek out AI-native product leaders, engineers and executives who will design products that incorporate AI from inception, rather than retrofitting it into legacy systems.
We are at a defining moment in the AI revolution. Access to foundational models is becoming democratized, and the real opportunity is shifting to how AI is applied in the real world. During the mobile app boom, our company succeeded because we saw how mobile-first thinking separated winners from also-rans in the early days of the App Store. The same will be true for AI. Companies that iterate and operate with AI’s unique capabilities will emerge as the dominant players of the next decade.
There’s no longer any doubt whether AI will change industries — it already is. The real question now: Who will be the AI-native companies that define this new era?