Jason Ambrose talks CEO role at People.ai

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There’s change at the top of AI-powered revenue intelligence company People.ai, with the appointment of Jason Ambrose as its new CEO.

Founded in 2016, People.ai was one of a batch of notable AI startups that emerged around that period (including OpenAI and Scale AI) that have gone on to become influential players in the space. People.ai had the goal of automating go-to-market data and streamlining CRMs, something that’s top of mind today for businesses of all stripes. It was accepted to Y Combinator within 30 days of launching and was last valued at around $1.1 billion after raising a 2021 Series D.

Ambrose previously served as senior vice president of marketing and strategy, and his appointment comes at a time of traction for the company. Its clients include enterprise open-source solutions company Red Hat, which People.ai says saw a 50% increase in sales win rates after onboarding its tools. At the beginning of this month, People.ai launched its latest product: an AI-native forecasting solution for general availability.

Revenue Brew sat down with Ambrose to discuss his transition from SVP to CEO and his strategy for People.ai’s growth.

This interview has been edited and condensed for clarity.

What are some of the learnings and experience you’re taking from your previous role and applying it to your current role as CEO?

I’ve been in this space a long time. When it comes to sales tech and particularly CRM, that space has always had a core challenge of working from self-reported data from reps, so understanding how that information permeates everything that we do in CRM systems and the related technologies that rely on that information is an important historical view of the space. That’s very relevant to what People.ai does, when it comes to taking that direct activity information and turning that into answers about what's happening in your go-to-market organization.

Then coming into the organization and thinking about their own history of how they’ve talked about their products and how it’s evolved lent itself very well to comparing the history of the space and how People.ai, who’s been at this for a decade and trying to apply AI to solve that challenge, but then also looking with that history: What has been changing and what are the customer expectations that are changing?

What is your strategy for People.ai and how are you planning on evolving it for your new role?

What’s fascinating about People.ai is there’s been different chapters to its evolution. There are a few businesses like ours that really find themselves in a whole new opportunity. Historically, we spent a lot of time on this notion of activity capture and mapping that into CRM, so how do we understand how those activities connect to accounts, contacts, and opportunities? It was very down in the boiler room of working with data analysts and RevOps of how do we get better CRM data?

The second act of the company was how do we think about bringing that forward into ways you would apply it in application experiences and then thinking about how we pair AI with that to turn our platform really into expert agents, where you’re not just creating this data, but you’re creating answers…That led to our forecasting application, which we’re out in market with now. Then we have this idea of there’s a third horizon where what we’re doing is really preparing those answers that could be used by humans or agents. We thought it would be longer for the market to see the need for that and a platform like ours that’s agnostic to whether it’s humans or agents that are trying to get these answers that are actionable and what we’ve seen is that horizon has come forward really fast for us. There’s a tremendous opportunity that we need to lean into and we want to focus on our core of the hard problem of taking all of this data and turning that into meaningful answers that you can act on and then providing that wherever our customers want.

What growth opportunities are you looking at for the new year?

The biggest is opening up this platform for a lot of different ways to use the answers. We’ve been thinking about providing them in well defined and structured what we call rituals, so opportunity management, forecasting, and account execution. What we found with customers with our new MCP capabilities, there’s a ton of different use cases and ways that they can use the information that don’t require us to invest in [a] road map. They can do that today by just pointing at Claude and asking a set of questions to our agent to create answers…There’s just a lot of ways to use our information, so we need to broaden our approach to make that accessible to our customers, so that they can use it in all the ways that they want to use it.

What do you think is People.ai’s point of difference in the AI landscape?

A lot of people have access to this data. For us to prepare that to become answers that are actionable, there’s a few things. We talk about matching and filtering: Think about, for example, a Microsoft selling to a Verizon. If you think about a typical, simple sales process, it’s one rep selling to one person at one customer in one account, so matching the activity to the context of that sales process is a simple question. But if you’re Microsoft or Verizon, you’ve got many different sellers, many different specialist overlay roles selling to many different stakeholders and many different business units at Verizon across many different opportunities. When that CRO or head of sales has a conversation with a CFO, they might have 10 to 15 topics that they cover. How do you capture that information properly so that AI can use that to generate the right kind of answers? That’s a difficult problem to solve and we’ve been solving that for 10 years over billions of transactions, and there’s just no making up for that time. You can’t just throw LLMs at this information and get the same quality of answers.

What are your short-term and long-term goals as CEO?

The short term is, we want to change the way that we’re coming to the market, both in how we talk about ourselves, so that it’s clearer what this value proposition is and the importance of this. We want to establish ourselves as having a voice of what AI means and the best ways to get value out of it. We want to share examples from our customers, like Red Hat, that have had really transformational results at a time when people are questioning whether or not AI can do anything. They’re living and breathing that, so short term it’s resetting the understanding of the things that we’ve done for a long period of time and why that’s important in this new landscape and as people try different things and hear different stories from vendors.

Longer term, I see this as we become this platform and this source of information that gets used in a lot of different ways, with humans and agents, and we want to be that core set of information that’s delivering those answers.