Five Learnings from the Past to Guide the AI Future at Digital Turbine

I’ve been part of four distinct tech revolutions during my career. I started in the 90s during the fixed-to-mobile transition and the freedom that it enabled all of us. Then came the digital explosion of the 2000s, followed by the birth of the app economy in the 2010s.

We are now embarking on the fourth, the AI revolution. What makes this moment unique is that it isn’t just a new chapter; it’s the synthesis of the previous three.

Lately, I’ve been asked one question more than any other: "Bill, how is AI going to impact your business?"

My answer is always: ‘a lot.’ But I don’t subscribe to some of the more extreme scenarios, like the idea that apps are simply going to vanish. We’ve seen this pattern before with every major technology shift - and in our view, AI is far more likely to expand our opportunities than eliminate them. That’s why I see it as a tailwind, not a threat.

To explain why I’m so upbeat, I want to share five learnings from the past tech revolutions that are guiding how we build for an AI-first world.

Learning #1: Technology may be King, but Distribution is the Emperor

Inventing great tech and driving widespread adoption are two very different challenges. We see this playing out in real-time as AI companies scramble for on-device real estate. For instance, Gemini has inherent distribution advantages over its competitors, who must now find new ways to reach consumers where eyeballs are, which is on device. 

For centuries, there has been a balance between customer "pull" and advertising "push." AI doesn’t eliminate that dynamic; it accelerates it. As AI lowers barriers to entry through efficiencies like agents and vibe coding, it will create more choices in the marketplace, not less. While the market is currently focused on the tech disruption itself, these expanded choices will likely grow the half-trillion dollar advertising market as companies compete for users. 

The inherent advantage in this new world goes to the companies that provide the "picks and shovels" with the reach to connect those new choices to the right consumers. For us, that’s our 1P data, on-device Single-Tap delivery, and intelligent app management that are the essential tools for this new era of discovery. Our scale is the proof of that reach: Ignite has been installed on more than 1B devices since its launch, and our DTX footprint touches nearly 100,000 apps across almost 3B devices.

Learning #2: Automation is the Secret Engine of Growth

Efficiency isn't always the sexiest part of a tech revolution, but it is often the most impactful. Every major shift simplifies and accelerates outcomes, which in turn unlocks profit for reinvestment.

At Digital Turbine, we’re already seeing this. Last quarter, our gross profit increased by nearly 25%, without increasing operating expenses. This wasn't just belt-tightening; it was the result of a more efficient operating model. By leveraging AI across our back office, from coding and QA to creative and campaign setup, we are unlocking the capital and time needed to invest in our next chapter of growth.

Learning #3: Data is the Differentiator for Customer Outcomes

Every revolution makes life more productive. Landlines, faxes, calculators, and typed memos are largely extinct. But while the speed of the network or the power of the processor used to be the differentiator, in the AI era, the differentiator is Data.

Not all data is created equal. In an AI-driven world, real-time, high-signal data tied to actual user behavior will outperform modeled or inferred 3P signals. Our unique 1P data and the advancement of machine learning allows us to turn that data into better outcomes for our customers, through our optimization ML engine that we call DT IQ. AI is simply the underlying technology that allows us to use our data to be more relevant for our users, more often.

Learning #4: Respect the Gartner Hype Cycle: Timing is Everything

Nobody wants to be what Friendster was to Social Networks (too early) or what Tidal was to Music Streaming (too late). In tech, you want to be where the adoption curve meets reality.

Mobile phones were invented in 1973, the internet as we know it in 1983, and mobile apps in the mid-90s. In every case, it took more than a decade to move from "what is possible" to "what is real." While AI is moving at a breakneck pace, it still faces many hurdles including intellectual property, privacy, regulations, business models, and process integration - just to name a few. We are moving fast, but also being thoughtful. Success requires clear-eyes of where we are on the curve.

Learning #5: Disruption and Adaptation are Not the Same

There are some narratives suggesting AI will make software obsolete. At DT, we believe the opposite: AI will make software like ours faster, leaner, and more responsive.

History is full of companies that failed to adapt, like Blockbuster and Kodak, and those that used disruption to become stronger, such as Microsoft and Nvidia. The difference is not just the technology, it is the culture. At Digital Turbine, adaptation is in our DNA. Years ago, our revenue came from things like ringtones and downloadable music. Those businesses are gone, and our revenues have grown in other areas. But our vision of connecting users and devices to the app economy remains. While others focus on the "magic" of AI, we believe the "secret sauce" is fusing the technology with a culture that knows how to adapt to change.

AI is the future but the lessons of the past should be guides on how to harness its power into the future. Focusing on distribution, automation, data, timing and adaptation, we move past the hype into real results. Spending decades in tech has taught me that tools change, but the key to winning still means how you integrate and execute the new tools against your strategy and vision. And I’m excited to lead Digital Turbine through this next chapter.

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