Signals That Separate Great Companies from Risky Bets with Neal Patel, CRO of Crunchbase
Making sense of the market and your next move
The world of revenue leadership sits at a fascinating crossroads. On one side, we see traditional GTM strategies that have served us well for decades now failing and tremendous economic and geopolitical uncertainty. On the other, a technological revolution that promises to fundamentally transform how businesses connect with customers in AI.
Neal Patel brings a wealth of experience to this conversation. Before joining Crunchbase, Neal spent close to a decade at Google in various strategic roles, where he helped build Google Maps in its early days, led global partnerships for search, and was instrumental in the go-to-market strategy for Google Fiber. His background also includes time as a corporate attorney specializing in M&A and international finance, and he joked that his keeps his mechanical engineering skills as a weekend pursuit. This multidisciplinary background gives Neal a unique lens through which to view today's rapidly evolving tech landscape. He also works for Crunchbase who have arguably the most valuable startup and venture data in the market.
As Crunchbase's CRO, Neal oversees all go-to-market functions including sales, partnerships, business development, marketing, customer success, and revenue operations. Under his leadership, Crunchbase has achieved remarkable 75x growth and secured strategic partnerships with industry titans like LinkedIn, Nvidia, Amazon, and SAP. He also serves as the de facto GM for Crunchbase's data licensing business, giving him deep insights into how companies are leveraging data in the age of AI.
Our conversation revealed five key insights that every revenue leader should consider as they navigate this rapidly evolving landscape.
1. The Agent Revolution: Prepare for Disintermediation
The most profound shift Neal identified isn't just about AI making things more efficient; it's about fundamentally changing how users interact with enterprise software.
"You could loosen the grip of having to engage with any enterprise app's UI if it's connected to an agent," Neal explained. "I could have an agent pull customer data from Salesforce via an API and merge it with financial data from NetSuite to generate a business intelligence report. As a user, I wouldn't need to engage with either platform directly."
This represents a seismic shift in how we think about enterprise software. The interfaces we've meticulously designed and the user experiences we've obsessed over may soon become invisible infrastructure, with AI agents serving as the primary point of interaction.
The implications are profound. As Neal puts it: "The apps could become like early web browsers—invisible infrastructure sitting behind the UI of an agent. You no longer log into any of these apps. They're just infrastructure in the background."
This isn't just theoretical. According to Gartner, by 2025, 50% of knowledge workers will use a virtual assistant on a daily basis, up from just 2% in 2019. Major enterprise software providers are already racing to position themselves in this new paradigm.
2. The Future Belongs to Those Who Adapt Now
One of the most dangerous mindsets I encounter among revenue leaders is the "wait and see" approach to AI adoption. Many are waiting for clear winners to emerge before investing in these technologies, worried about backing the wrong horse.
Neal's perspective on this was refreshingly clear: "I'd rather pick the wrong horse than not be in the race at all."
This resonates deeply with me. At Owner.com, we've implemented six major AI initiatives. While one didn't work out as planned, the advantages gained from the other five have created a significant competitive edge. The cost of not experimenting far outweighs the cost of occasional failure.
Neal frames this perfectly: "If you're not in the race, pretty soon you'll stop getting invited to races, and then you'll stop getting invited to anything anybody's doing. And then whether you wanted to retire or not, you are retired."
The research bears this out. McKinsey's research shows early AI adopters are already reporting 20% higher EBIT margins compared to peers. This advantage compounds over time as organizations build institutional knowledge and technical capabilities that can't be quickly replicated.
3. Proprietary Data Is the New Competitive Moat
While discussing what makes businesses AI-resistant, Neal highlighted a crucial insight: proprietary, dynamic data is becoming one of the most valuable assets a company can possess.
Crunchbase recently pivoted from being purely historical (documenting what has happened) to predictive (forecasting what will happen). Using their rich dataset of company histories and user engagement patterns, they now predict future funding rounds and acquisitions with remarkable accuracy. You can see their new Heat Map and Growth Score for Owner here. It’s pretty fascinating insight.
"Every piece of data that anybody has about a company is historical," Neal noted. "But if you're trying to do business with these companies, what you really care about is what's going to happen in the future."
This represents a profound shift in how we think about data as a strategic asset. Neal explained that Crunchbase's engagement data (80 million users viewing and interacting with company profiles) is impossible for competitors to replicate. "No one has that, and it changes all the time," he said.
For revenue leaders, this suggests a critical strategic consideration: businesses built on proprietary, dynamic data that's difficult to scrape or replicate will be more resistant to AI disruption than those relying on public, static information or simple workflow automation.
4. Human-to-Human Skills Become More Valuable, Not Less
Contrary to fears that AI will replace revenue professionals, our conversation highlighted how certain human skills will become even more critical.
"GTM folks are going to be more about the things that AI can't do," Neal predicted. "Relationship development, strategy, and creativity... when you have to have creative strategy linked to human relationships, that's where the GTM portions really going to come in."
This aligns with research showing that the most effective approach combines AI-powered efficiency with enhanced human relationship skills. Multiple studies suggest that this hybrid approach significantly outperforms either AI-only or human-only strategies in complex B2B sales environments.
What's particularly interesting is how this shift will impact company valuation and career trajectories. Organizations that excel at the uniquely human elements of building relationships and solving complex problems will maintain their value, while those providing simple workflow automation or data services may be vulnerable to disintermediation.
As Neal put it, the GTM stack could shrink from "10-15 tools to 2-3 AI-driven platforms," with the emphasis shifting to relationship-building and strategic thinking rather than process execution.
5. Company Selection: Look Beyond Market Size to Leadership Vision
For revenue leaders considering their next role, Neal shared invaluable wisdom about how to evaluate opportunities, especially in an AI-transformed landscape.
Beyond the usual advice about product-market fit and market size, Neal emphasized the importance of understanding how leadership thinks about the future:
"Are they skating to where the puck is going or where it is today?" he asked. "You have to balance both—you have to build things today to capitalize on what's available, but you also have to be in parallel building for the future."
Neal suggested looking for these specific signals when evaluating an opportunity:
Leadership vision beyond the immediate: How do they think about potential disruption? Are they focused on next quarter's targets or years ahead?
Proprietary data assets: Does the company have unique, dynamic data that's difficult to replicate?
Value-add beyond simple workflows: Is the company creating value that can't be easily automated or disintermediated?
Cultural alignment: Can you have genuine, vulnerable conversations with your potential peers? "My job is to make you look like a hero, your job is to make me look like a hero," Neal said, describing his relationship with Crunchbase's CPO.
Growth mindset: Look for companies that want you to adapt and grow, not just implement playbooks from your past successes. "Go someplace that wants you to adapt, go someplace that's going to need you to change," Neal advised.
The most compelling red flag Neal identified was companies that want you to simply replicate past successes without adaptation. "They're looking at you like, 'Take what you did there and do it here,'" he explained. "But hidden in there is a presumption that things haven't changed since you did it, and you haven't changed, and you're not going to change once you're here."
The Path Forward
As I reflect on my conversation with Neal, I'm struck by how AI is forcing revenue leaders to confront fundamental questions about value creation. Even the most basic assumptions about our markets are obsolete in many cases. The tools and tactics we've relied on are being reimagined, while the essence of what makes sales work (human connection and strategic problem-solving) is becoming more important than ever.
The organizations that will thrive in this new landscape will be those that embrace AI as a tool for augmentation rather than replacement, investing in both technological capabilities and uniquely human skills. And the leaders who will guide these organizations will be those who can navigate today's challenges while preparing for tomorrow's transformations.
As Neal so eloquently put it: "Create the context for your success." In an AI-transformed world, that context will look very different than it did before—but the opportunities for those who adapt have never been greater.