Tamara Kinney, our CRO, was named one of the Top Women Chief Revenue Officers of 2026 by Women We Admire. In this interview, she talks about selling expertise, reading pipeline, and what AI changed in the first client conversation.
In a consulting firm, you sell expertise and people. How does that shape the way you run revenue?
In consulting, your product walks out the door every evening. That fundamentally changes how you think about revenue. You’re not just selling a solution; you’re selling trust, expertise, and the confidence that your team can deliver on a promise. I believe the best revenue organizations are built around what I call service-market fit: aligning exceptional talent and differentiated capabilities with real market demand. Sustainable growth happens when sales, delivery, and client outcomes operate as one engine.
How has AI changed the first conversation with a client over the past year?
A year ago, conversations often started with “What can AI do for us?” Today, they’re increasingly starting with “How do we turn AI into measurable business value?” That’s an important evolution. Executives are moving beyond experimentation and demanding outcomes, speed, and scale. Our job is no longer just to educate clients on what’s possible. It’s to help them prioritize where AI can create the greatest competitive advantage and build a practical path to realizing that value.
How do sales and delivery work together here, so what we sell is what our teams can build?
I’ve always believed that sales and delivery shouldn’t operate as separate functions. They’re two halves of the same promise to the client. At Lovelytics, we bring technical and industry experts into conversations early, ensuring we’re designing solutions around real business challenges, not just selling capabilities. That collaboration also creates a powerful feedback loop: what we learn delivering for clients directly informs the next generation of solutions we bring to market.
What does a strong co-selling motion with partners like Databricks and Anthropic look like in practice?
Great partnerships aren’t built on logos and joint announcements. They’re built in the field, one opportunity at a time. The strongest co-selling motions create mutual value: aligned account strategies, shared customer intelligence, differentiated solutions, and clear incentives for both teams to win. We’ve built our Databricks and Anthropic partnership around making it easier for their sellers to bring Lovelytics into opportunities and accelerate customer outcomes. When your partner views you as an extension of their team, you’ve built something scalable.
Tell us about a client win this year you’re proud of. What made it work?
One of the wins I’m most proud of is our work with Xcel Energy, where we helped bring agentic AI into the utilities industry to solve meaningful operational challenges. The solution demonstrated the potential to unlock $3 million in annual business value. What made it successful wasn’t simply the technology; it was the combination of deep industry expertise, strong client collaboration, and a relentless focus on measurable outcomes. That’s what makes AI transformation exciting to me: turning innovation into tangible business impact.
What’s the first number you look at on Monday morning, and why?
Pipeline coverage and velocity. Revenue is a lagging indicator; pipeline health tells you what’s coming. I want to understand not just how much pipeline we have, but whether we’re creating the right opportunities, progressing them effectively, and maintaining the momentum required to deliver predictable growth. In a high-growth business, you can’t manage by looking in the rearview mirror. The best revenue leaders are constantly looking around the corner.
What advice would you give a seller moving into Data & AI consulting?
Stop selling technology and start selling business transformation. The most successful sellers in this space are intellectually curious, commercially minded, and comfortable connecting technical capabilities to executive priorities. You don’t need to be the smartest engineer in the room, but you do need to understand how data and AI can change the economics of a business. Build credibility with technical teams, learn your client’s industry, and always lead with the outcome rather than the architecture. For example, I have a seller who trained Claude to give him a daily podcast on Oil & Gas use cases to build his expertise in the industry – this type of hunger and AI accelerated knowledge that makes our team unstoppable.
You’ve led revenue at AWS, Gartner, and Booz Allen. What carried over to a Data & AI consultancy, and what did you have to learn fresh?
Every chapter of my career taught me something different. Gartner taught me to lead with executive insight and strategic value. AWS taught me how to build and scale partner ecosystems. Booz Allen taught me the importance of mission-driven, complex problem-solving. What I had to learn in consulting was how to bring all three together while scaling a people-driven business at extraordinary speed. Growing Lovelytics from roughly 30 employees to more than 650 reinforced that culture, talent, and execution are just as important as strategy.
Congratulations, Tamara. (We’ll be borrowing the Monday-morning habit.)
