Getting Real About AI Readiness with New Breed’s Jonathan Burg

In the rush to embrace AI, many companies are sprinting toward adoption without a clear strategy or plan for implementation. The result? A bunch of professionals wondering if they’re actually equipped for all of this.

To get a real look at what AI readiness actually means, we chatted with Jonathan Burg, the Senior Vice President of revenue sales, marketing, and partnerships at New Breed, a top HubSpot Solutions partner. In our conversation, he shares how leaders can move beyond the hype and start using AI with purpose.

As a speaker at G2’s upcoming AI in Action roadshow, Jonathan will also discuss the real challenges behind AI adoption, what leaders often get wrong, and how to build alignment across teams before bringing in new tech. No spoilers here!

To watch the full interview, check out the video below:

This interview is part of G2’s Industry Insights series. For more content like this, subscribe to G2 Tea, a weekly newsletter with SaaS-y news and entertainment.

Inside the industry with Jonathan Burg

You lead revenue across sales, marketing, and partnerships. How has that shaped your perspective on adopting new technologies like AI?

First and foremost, it's really helped me take a holistic viewpoint across the entire customer lifecycle and understand how important context is in leveraging AI the right way. I think one of the roles of a revenue leader is to understand how to think through revenue from the very beginning. An organization may not even know that they have a problem, so how can you, as a leader, look across that entire cycle and identify areas of friction and optimization? 

Over the years of being a revenue leader connecting the dots across different teams and processes, I’ve been able to identify how we can leverage AI in a world where it needs context across the entire customer lifecycle. You can get good benefits from using AI tools focused on finite use cases, but you're only going to get so far. So you have to leverage integrated data and knowledge across the customer lifecycle. That's really when you start unlocking the power of AI. 

Another critical role of a revenue leader is to create true interlocks across an organization. That's at the leadership, VP, director, management, and individual contributor levels. How can you create an interlock across the entire organization and help teams work together in order to accomplish their goals? 

Two of the primary use cases that we've leaned into this year involve the marketing organization supporting our sales and customer success teams in identifying the exact right piece of content and references to help support decision-making processes. The other really big part is that our sales and technology group is collaborating to help with really amazing customer launch experiences. These are cross-functional and require a ton of context across groups and true interlapses.

What’s one common misconception you see when companies say they're “ready” for AI?

It's rare that I come across an organization right now saying that it is truly AI-ready. I was just at the HubSpot Spotlight release event, and they actually asked the audience of early adopters and cutting-edge organizations if they were AI-ready. I’m going to guess that 10% of organizations raised their hand. At the event, I saw that 75% of organizations don't feel they are moving fast enough in the age of AI. 

One of the biggest hurdles is data. Even if an organization has the cleanest structured data, it must standardize and make its unstructured data available. AI readiness across that data spectrum is when you can define your structured and unstructured data so that AI models can interact with it autonomously. 

During the roadshow event, I'll explain how organizations can become AI-ready, not just by analyzing their data but also by considering team enablement and how they can optimize and facilitate the customer buying process in the age of AI.

AI adoption is a big goal for many organizations, but it can be overwhelming. How do you recommend leaders prioritize AI initiatives? What metrics or ROI indicators should they be tracking to know they're on the right path?

I completely agree. It's like, “Where do I start?” Particularly when we're talking about the first question that you asked, there are so many things that we can do. But this is the answer I give to a lot of similar questions: start with your customer journey. I think every revenue leader has a really unique opportunity to remap their customers' buying journey in the age of AI. That doesn't mean that it's changed drastically. It may not have; there might just be some tweaks. 

You need to look at your customers’ buying journey and start thinking about how to apply AI to support it. So it’s about asking the right questions. Where are buyers going to do their research? How are they progressing through the decision-making stages? How are we helping to support the progression through those stages? Who's involved in the buying process today? Are we reaching all of those people in the most appropriate way? I think once you do that, it's going to help you prioritize the top use cases where AI can help remove friction. 

You also need to help your team enhance customer connections. The important element of that is to think through the tools and technology that you already have in your environment and how your team can help leverage them. If those align with some of the most prioritized use cases, you can identify gaps. That's one way to be very structured and very customer-centric. 

Once you identify those use cases that you're going to lean into, you’ll want to focus on the metrics that are most aligned. Generally speaking, efficiency metrics, velocity metrics, and conversion metrics are particularly relevant in the areas of the buying cycle.

What role do you see sales and marketing teams playing in AI adoption beyond just using the tools?

It's enablement. It's making sure that your teams are utilizing the tools in a consistent way and that you're offering training to help people actually do that. 

Revenue teams need to deliver really important things in order to consider themselves high-functioning. One is to help the organization define a strategic direction and go-to-market (GTM) strategy. They need to enable the organization with the tools and resources to be successful. And when I say tools and resources, in today's day and age, I mean AI. You have to think through. Not just how AI is an add-on, but how it is integrated into those things. It's not just using the tools but also transforming your GTM strategy so that you drive incrementally more out of the team.

I would also challenge sales and marketing teams to champion the voice of the customer in this age of AI, and listen to how customers are utilizing AI in relation to their solution and their product. Drive that back into the organization to help your entire organization create innovation across all functional areas.

What does “AI readiness” not mean to you? Any red flags you think leaders should watch out for?

I think for revenue leaders, it doesn't mean utilizing AI in bubbles. I've spoken to a couple of revenue leaders, and they say things like, “Yeah, yeah, I'm AI-ready,” and they talk about all the things that they're doing with AI. For teams, that could be intimidating. Their boss is crushing it with AI, and they don't even know where to start. Or companies that share all these AI use cases, but whose people don't know how to grab them and operationalize them. There can be feelings of intimidation or isolation. That's not AI readiness.

The role of a revenue leader in this age of AI is to create a culture of learning and experimentation with strategic guardrails. And culture is the key word there. If you don't have a culture that integrates AI into all planning processes and is part of your DNA, and where people can learn together, but one that's characterized more by hiding AI use cases because you’re unsure of how it's going to be perceived, that's major red flags right there. 

AI readiness is not about everybody just using AI in isolation. It's about creating a culture of how to use tools in a way that makes an impact for customers.

What’s one thing you hope attendees walk away with after your session at AI in Action?

I'm so excited! Because yes, I'm presenting, but I'm also learning. We have some heavy-hitter speakers talking about big trends. It's just over half a day, but my goodness gracious, I think we're going to learn about a month's worth of value.

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My hope is that people have a roadmap to getting AI-ready. I want them to have at least one practical use case that they can apply within their environment when they go back to their office. I know there's going to be a whole bunch of things people take away, so we're creating a little workbook that you can take and map out how you are going to use this approach to get AI-ready within your organization. 

Everybody at the event has tools and technology with really powerful AI capabilities within their environment through GTM tools. It's all about using those capabilities in an impactful way that helps customers make buying decisions. I'm pretty confident that people are gonna walk away with at least one or two things that they can bring back to their teams to apply. I can't wait. See you in New York, San Francisco, Atlanta, and London!

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Follow Jonathan Burg on LinkedIn to learn more about his extensive knowledge in the industry and catch him as a featured presenter in G2's AI in Action Roadshow.

Edited by Supanna Das