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"Never waste a crisis. It is your single biggest opportunity to effectuate change in your life or in your business." — David A. Steinberg
Most companies find out whether their strategy was right during a period of disruption. David A. Steinberg tends to use disruption as the moment to accelerate. He has done it more than once, and the pattern shows up clearly across this conversation with Matt Britton on The Speed of Culture podcast.
Tune in to the latest episode or read the transcript below. Here are the top takeaways:
The Art of Triangulation
Before David gets into any of the specifics about Zeta Global, he describes the practice that has guided every major bet he has made as an entrepreneur. He reads five to six hours a day across publications, white papers, and scientific journals, specifically looking for signals in seemingly unrelated places that point toward the same conclusion.
He calls it triangulation. And the insight that led to Zeta's AI pivot in 2017 came from exactly that process. The company had built a significant data ecosystem, but there was no way to process what they were ingesting fast enough to make a decision that actually mattered. Milliseconds were the requirement. Hours were the reality. That gap was the opening, and it led David to start learning seriously about artificial intelligence at a time when almost no one in martech was having that conversation.
Being the Disruptor in a Category Full of Disrupted Companies
The broader marketing technology category grew about 10 percent last year. Zeta grew 30 percent. David is direct about what that gap means: the company is taking meaningful market share from competitors who are struggling to adapt to the same forces Zeta has been building for since 2017.
Three things explain it.
First, a proprietary data cloud covering 552 million opted-in individuals, with five to seven thousand data elements per person, that has never been fed into a large language model and never will. That matters enormously to enterprise clients who are increasingly nervous about where their first-party data goes.
Second, an architecture that makes AI and data native to the application layer rather than layered on top, which removes latency and drives higher return on ad spend.
Third, a business model where Zeta returns six to seven dollars for every dollar a client spends, making it a revenue center rather than a line item to be cut.
Those three things compound over time in a way that is difficult to replicate quickly.
What Athena Is Really About
The launch of Athena, Zeta's voice-enabled AI copilot built in partnership with OpenAI, is worth understanding at more than a product level. David's argument for why voice is the right interface starts with this observation: humans have communicated through voice for hundreds of thousands of years. The keyboard arrived in the 1950s. The mouse came later. Every interface innovation since has been adding steps between the person and what they actually want to do. Athena is designed to remove those steps.
The business case was already visible. When Zeta launched an earlier voice tool called Zoe, clients using it spent 250 to 275 percent more on the platform than those who did not. That data point gave the leadership team confidence to go into full build mode. From the first idea to general availability took approximately ten months.
What Athena enables in practice is significant. A client can ask it to drive two million incremental customers at a seven percent cost saving, receive a recommended approach based on real-time data from Zeta's cloud, narrow the scope mid-conversation, and ask for hourly ROI reports while they are out of office. All of it through conversation, fully integrated with ChatGPT.
What an Internal AI Transformation Actually Requires
David is candid about the change management work involved in becoming an AI-native organization. He did not hand down a mandate and expect compliance. Rather, he started by making AI tools available to everyone, then tracked usage, then publicly recognized the people who were using them well and asked those people to explain the benefits to their colleagues.
Engineers were organized into pods, with the most AI-capable people placed in leadership of each one. The goal was not to flip hundreds of engineers overnight but to move the pods one at a time. The result at the end of last quarter: engineering output at 125 percent of where it was twelve months ago on a net basis, after accounting for the quality control work required to remove noise from AI-generated code.
He is also honest that some employees who did not embrace the shift were moved on, and that the company is doubling down on those who did. He does not frame this as a hard line so much as a natural consequence of where the organization needed to go.
The Shift in Search and What It Means for Enterprise Marketing
One year ago, 97 percent of Google searches resulted in a link off the platform. Today, 60 percent of answers are resolved on the platform itself. David sees this as a structural shift with compounding implications. As more answers get resolved without a click, fewer clicks are available, which drives the price per click up. At some point, enterprises hit diminishing marginal return on what they can spend to acquire a customer through those channels.
Zeta has already built a generative engine optimization platform to help clients get ingested into AI-generated answers across OpenAI, Claude, and Gemini. And the partnership with OpenAI on advertising positions the company to be part of where budgets flow as that ecosystem matures.
The Mantra That Has Traveled the Furthest
The phrase David keeps coming back to is one he traces to Machiavelli: never let a crisis go to waste. The COVID example is the clearest illustration. Zeta had seen signals early, moved fast, rearchitected operations for remote work across global offices, secured housing for employees in India who lived in communal spaces, and put Chromebooks in the hands of hundreds of employees before lockdowns arrived. The company grew that year while the rest of the industry shrank.
His point is not that the preparation was easy, but that in the middle of a crisis, the opportunity cost of making a hard change drops to its lowest point. The things that would normally get deferred for another year suddenly have no queue in front of them. That window is the one most organizations miss because they are focused on getting through rather than getting ahead.
What He Tells Young People Who Are Worried
David spent a day at Penn State recently and found a room full of students more anxious about their futures than he had seen in a long time. His response was straightforward: stop chasing the same ten firms everyone else is chasing. Go somewhere you can learn how the business actually works. Build your soft skills. Develop creativity regardless of your function. Find a problem you think you can solve.
He looked at the stage that day and noted that nobody on it had followed a conventional path. He started his career on Capitol Hill. Others started at HBO or in government intelligence. The idea that there is one right door into a meaningful career in marketing and technology has always been wrong, and it is becoming less true by the year.
What This Means for Marketers and Leaders
What David describes across this conversation is a specific kind of discipline: the willingness to read widely, bet early, hold the standard through the friction of internal change, and treat uncertainty as an asset. That combination does not show up often, and it is worth paying attention to when it does.
