Perficient’s Bryan Berumen talks revenue teamwork and being an AI-native company

Perficient, an AI services company, landed its chief services officer because of FOMO.

Bryan Berumen had only recently left Accenture, where he worked for over 20 years, for Boston Consulting Group when he heard about a chief services officer role being created at Perficient.

“I was afraid I would have FOMO if I didn’t take the chance to go back and really do something very unique in an industry that I had spent my entire professional career in,” Berumen told Morning Brew.

He now leads Perficient’s go-to-market strategy alongside the company’s chief delivery officer, Abhishek Sinha, who lives abroad. Berumen talked with us about how he makes that partnership work, the changes he’s made to the company’s growth plan, and balancing AI opportunities and costs.

What are some ways you and Perficient’s chief delivery officer approach your partnership that make it work?

First off, it’s getting to know each other, good old-fashioned relationship and in-person collaboration. No technology will ever change that. I think we learned that during Covid—we can be more flexible, but at the end of the day, being together in person and conquering problems together really does have a multiplier effect. So I’ve spent some time in India, and he’s spent some time here in the US.

I think we’re both very big believers in “follow your strengths” versus “trying to make up for your weaknesses,” and take advantage of that. And so the things that he’s exceptional at, I’m not very good at, and the things that I do very well, he knows that may not be a core strength of his. We don’t need a very prescriptive, racy matrix on who does what. There’s a lot of trust and belief in each other on the things that we know I’m going to get a better outcome for, or he’s going to get a better outcome for. We let each other operate, and we really show up together as a unified leadership team.

And traditionally these co-lead things are hard and often they don’t really work, so I think we were both a bit skeptical on how this would play out. But now that we’re nine months in—I’m nine months into the role; he’s been here a little bit longer than me—I think we both look back and say, “I think we nailed it.” I think we’ve really got this co-leadership concept going, and it’s been a driving force into how our teams operate, but also the impact that we make to our clients, which is ultimately the goal.

Based on how the revenue streams were working when you initially started at Perficient, compared to now, are there any big changes you’ve made? Are there any strategies that you’ve implemented that you think have worked?

Absolutely. Perficient has been around a really long time. I think most people are surprised to understand they’ve got over a 20-year history as a consulting company. But they’ve historically grown by acquisition, and that’s where we get some of our amazing talent. They’re deeply focused in a particular area, specialists in that space, and technically exceptional…Over time, that led to a lot of different business units that each had a level of autonomy that allowed them to do what they were great at. What you found over 20+ years of that is you had a series of P&Ls that were too big for a company of our size—it was over 30 P&Ls that were running simultaneously.

So we’ve broken out our strategy into what I would call three waves, and wave one, which we completed back in January, was just a simplification of the operating model. How do we take all of these different P&Ls that existed and organize them in a way that was a little bit easier for our clients to consume, for our partners in the ecosystem to navigate, and then for our talent to know where they belong and where they fit? We oriented around five industry verticals, and that’s really where the P&L sits. And then we took the rest of the practitioners, the folks that are deep in different technologies or specialty areas, and we created seven service lines that are all at the top line, led by leaders in the industry that are specific to a particular function, like marketing or sales and customer service. And then there’s a collection of practices that sit underneath them, so it was a bit more of a “let’s make things easier for our clients to consume.”

We put in an account ownership model that lives inside the industry teams, and then the horizontals are all these practices that bring unique depth and specialty in areas like data and AI and Salesforce or Adobe—things that you would kind of expect on top of a pretty significant custom development team. So that was the first phase of the strategy.

The second phase, which is what we’re living right now, has been being a disruptive but beneficial partner to the industry. We like to use the word “disruptive” because we think our clients can relate to that, and it’s all being driven by what’s going on with AI. While AI has been around for a really long time, when you think about machine learning, the capabilities around generative that showed up three [or] four years ago, to now the agentic capability is moving at a pace that—even watching the SaaS world operate very quickly 10, 15 years ago—this is a whole new game. There are a lot of business models, particularly for some of the larger companies that are very reliant on labor to produce revenue, and as we look at what is arguably a shrinking total addressable market in professional services, because a lot of this work is being done by AI, the only way for us to grow is to be disruptive in what we offer and take share from competitors. In order to do that, we have to operate very differently, and bring a different value proposition to our clients.

So we do that by being AI-first…We don’t use PowerPoint anymore. We use Claude to develop our web decks and points of view. It’s become widely adopted inside the company without a lot of process and rigor. It’s available and people are jumping into it. We’re also partnering with unique companies like Swantide, which is a Salesforce-based AI configuration and administration capability that cuts your delivery time up to 60%. When we can show up to our clients and say, “Hey, we can do that work that traditionally might have taken you eight to 10 months, and we can do it in four to five for half the cost, and we can put some fees at risk to get you the outcome,” that’s a way for us to be disruptive to the traditional market and still give our clients comfort and confidence that we can deliver it. And so that, applied across all 15 of our practices and seven of our service lines, becomes that force multiplier that we need to drive growth in a very difficult market, and you can see that really working.

And then the third phase of the strategy, which is also happening in parallel—because you just don’t have time to wait, as I’m sure you’re finding from the people you talk to—is how do we keep that pivot moving into being an AI-native consultancy, where what we do is focused on industry-specific use cases and problems that those industries face, so that we build AI capability and solutions around those challenges? One example…is we’ve built a wealth advisory AI platform for wealth advisors to understand their customers better and think about how [they] prepare for an annual review with a particular family or individual, what’s going on in current events. It’s got a really smart database that sits underneath it that makes sure that the data is secure, because that’s critical, but then is also pulling information from the wealth advisor’s portfolio of offerings, understanding what’s happened in the macro market, what’s going on geographically, geopolitically. All that helps an advisor become better at their job, and solutions like that six months ago were a dream. They literally couldn’t exist. So the more we invest in these types of industry-specific solutions, the more we’re seeing our clients look at us very differently, and say, “These guys just aren’t the ones that are going to plug in some application—they’re bringing me thought leadership.” It’s a different revenue stream for us. It’s a new way for our clients to buy our services, but more importantly, it’s a new way for our clients to get the outcomes that they need from the investments they make with us and any other partner that they spend money with.

Speaking about using AI to shorten timelines for products, have there been any big trade-offs? I would imagine you’ve got to pay for enterprise licenses for everyone in the company, and then there’s also the fact that AI can change the hiring structure but also the training structure of low-level employees. How have you dealt with that?

“Trade-off” is an interesting word because—maybe I’m a glass-half-full guy—to me there are more opportunities to think differently. But I hear you, the cost is absolutely real and it’s very unpredictable, even when you’re using it for your own productivity, like I do with my chief of staff agent and our pipeline analyzing tools. Using these enterprise licenses, it costs, and it’s consumption-based, and so you can’t really tell where that bill is going to go. But you also don’t want to throttle it to the point that it’s ineffectual and doesn’t help anybody. We’ve been very lenient. This is…“trying to be different for real,” which is kind of our new slogan. We’ve got to let our people embrace and adopt these tools, and we believe firmly that those investments will pay off in bigger deals, different deals, new revenue streams, new ways of thinking and operating with our clients. That [cost] is very real, that we’re keeping a close eye on, but making sure that we have some autonomy to go do what we need to do.

Talent is, I think, going to be a huge change, not only in how we operate…For us, the traditional consulting paradigm was a pyramid, and it starts to beg the question, “Do you need the lower end of the pyramid anymore, and does it become more of a diamond?” A lot of thought leadership and papers out there will say it is different. Well, where do you get the middle layer if no one’s learned their way from the bottom?

I don’t know that it’s actually going to be a diamond ever, because I think the way to skill people up can happen a lot faster, so I still feel strongly that there will be junior staff that will evolve and learn, just much more quickly than we had in the past. But we’re also taking it as an opportunity. In fact, we’re starting a cohort here at the end of the month, where we’ve gone to essentially the top 10 schools around the country and hand-picked about 15 individuals to come and do more of that in-person-style onboarding training, multiple weeks where they’re going to be learning all of these capabilities. But they have a different mindset because they’ve grown up in more of this digital-native, AI-native world, and that’s going to be really exciting. And so we have to rethink what that, you know, new-joiner orientation looks like, or the university hiring process, and what that looks like. But in a volatile market where kids are having a hard time finding jobs coming out of college, we actually get to probably go grab talent that five years ago would have been very difficult for a company of Perficient’s size to compete for. So we’re finding these areas where it’s a challenge, but it’s offering us a unique opportunity to go do things very differently than we may have historically. But that requires just a bit of a different mindset.