Today’s most successful IT leaders must be master translators, interpreting technical complexities with clarity and precision for the business units that rely on their services for into decisions and action. Deluxe Chief Technology and Digital Officer Yogaraj “Yogs” Jayaprakasam is among the best at putting this into practice, a strategic imperative he describes as “humanizing” technology.
Rather than beginning with cloud, architecture, or AI, Jayaprakasam frames Deluxe’s IT strategy as one focused on technology “that powers profitable growth.” This translation mastery can also be seen in the five-part series he and CEO Barry McCarthy co-developed to establish a common language around Deluxe’s IT transformation, a sea change that improved not only the way Deluxe does business but the way its customers do as well. And you can see it in how he translates strategy to measurable business, customer, and talent outcomes. Jayaprakasam’s widely read newsletter, “AI Signals: Navigating Change,” is perhaps the clearest expression of his knack for finding the signal and translating it into pragmatic, immediately useful leadership insight.
After a recent episode of the Tech Whisperers podcast, Jayaprakasam and I spent some time discussing why being a master translator is critical for today’s technology leaders and how he separates signal from noise to serve Deluxe’s next reinvention. What follows is that conversation, edited for length and clarity.
Dan Roberts: You’re an engineer by training. When did you realize knowing technology wasn’t enough and that one of your most important jobs was helping others understand what technology makes possible?
Yogs Jayaprakasam: It comes from a pattern I’ve seen throughout my career. As a technologist, you can provide an elegant technology architecture, but the customer wants to know, “If I invest half a million dollars in that, what will I get in return?” I’ve had some of my most high-performing senior technology leaders tell me, “Here are all the great things our team has done,” but they still struggle to figure out, “What does this mean to the company?”
For example, as AI adoption increases, so does exposure to third-party operational risk beyond traditional cybersecurity threats. Recognizing this shift early, my team deployed capabilities such as synthetic monitoring, blast-radius analysis, and proactive service desk operations. The outcome was an 80%+ reduction in system incidents over the last nine months, demonstrating the value of anticipating emerging risks before they impact the business. But when I asked the team what that meant to the business, they couldn’t articulate it.
Technology earns credibility when its impact is expressed in the language of the business — financial performance, risk reduction, customer satisfaction, and employee experience. In this case, I helped the team recast the message as what it truly was: a direct contribution to EBITDA protection and enterprise risk reduction.
I rewrote it as, “It directly protects the EBITDA of the company and reduces our risk posture meaningfully.” Because every time there is an impact, it takes additional time — and costs — for us to fix the problem. That chips away at EBITDA while impacting our customer and employee experience. That’s what the business wants to know.
Deluxe has one of the most inspiring business success stories. Can you talk about where the company started out and where you are today?
Our founder, W.R. Hotchkiss, used the most cutting-edge printing technology of 1915 to introduce uniformity to American bank checks, and he invented what we recognize today as the modern checkbook. Deluxe was a dominant force in paper payments and used that trusted history and massive business network to move with the times. Today, we are a digital payments and data company offering merchant services solutions that provide credit card processing, payment settlement enablement, the payment gateway, and data-driven marketing solutions for B2B businesses, financial institutions, and various industries.
When this business transformation journey started, we were around 30% payments and data. As of this past quarter, we were at 52% payments and data, and we are potentially trending towards 60% payments and data with the recent acquisition of Celero Commerce. So we are a payments and data company with the legacy checks division still being profitable, supporting our cash flow and business growth.
You’ve described Deluxe’s journey as one of reinvention, not simply transformation. Why is that distinction important?
Typically, people use modern technology to do the same thing they were doing before. It could be a manufacturing company that still does the same manufacturing, but now you are applying a digital order management system to accelerate fulfillment. At legacy Deluxe, the product we were building was checks, so we identified ourselves as a manufacturing company. Adopting digital technology for that process simply enabled it to be more efficient. That’s transformation.
But the job customers trusted us to do for more than 100 years has largely moved to credit cards, digital payments, embedded payments — all things that no longer require manufacturing. Now, technology is how we build those services and deliver. The mission is the same — to make sure the payments transactions are safely and quickly completed — but we had to reinvent what we do, how we do it, and the whole mindset of delivering a software-driven product.
Every function inside the company had to change. Finance had to change the way we do revenue recognition. In manufacturing, you have to think about inventory management to optimize your balance sheet. It’s totally different on the payments side. The talent is different. The sales talent is different — somebody who used to sell a tangible product versus somebody who is selling a service level and functionalities. The tech stack is different. For the technology function, this means you have to build applications and platforms that are always on to facilitate those digital payments and data solutions. Every part is evolving in every sense to make the whole bigger than its parts. That’s why it is a reinvention story, not just a transformation story.
How do you translate your technology strategy into something everyone, from the boardroom to an engineer at the keyboard, can understand and act on?
I have a one-page strategy slide that begins with “Technology’s mission inside Deluxe is to power profitable growth.” This was co-created with my CEO and the rest of the executive leadership team. We connected that to five strategic pillars:
First is Deliver Measurable Business Value. That means aligning technology investment to growth. This an executive leadership team and board pillar — it is of special interest to the leaders responsible for investment decisions — but my team will experience it through the projects we invest in.
The second pillar is Build Modern Products and Platforms. That is where the investment turns into initiatives. Can the core platforms we are building be reused in many business units? We identified data, AI, and APIs as a core part of our platform strategy to drive reuse and leverage. For example, if I built an API that can extract invoice solutions, every business that needs an invoice solution can consume it.
Third is Scale AI Responsibly. This is about using AI with our data to drive more automation efficiency for the internal functions. We used AI to eliminate a 50-year-old mainframe and move to the cloud. We are using AI to continue to drive resiliency on that platform but also to improve our legacy unit, because, according to the Federal Reserve, 60% to 80% of businesses still use the check product, and many of those businesses are banks, even our largest banks.
Number four is Strengthen Cyber Resilience and Trust, where we continue to innovate in not only cybersecurity but also systems availability, proactive resiliency, all those things to protect our revenue, EBITDA, and our existing business.
The fifth pillar is Grow Next-Generation Talent and Culture, which is investing in our people across the company, giving them the right tools and AI skills in an accountable, collaborative culture.
Stepping back, the first pillar talks about strategic investment through the lens of the ELT and board. But the next three pillars talk about technology’s job: driving profitable growth and improving the margin. Products and the platform contribute to driving the growth. AI usage contributes to expanding the margin. The trust and governance comes from next-gen cyber resiliency. Then we’re investing in and training our people.
You’ve told me the CEO and executive leadership team are your “first team.” How has being on that team and serving on boards, changed the way you think and lead?
Becoming part of the executive leadership team is your best opportunity to truly become a business leader, not just a technology leader. Your first duty is to the team that you are a part of, which is the ELT. But serving on boards gives another dimension for a technology leader. How you think and act in the executive leadership team is different from being on the governance team of a board. How you observe and guide operating teams is different.
It makes you realize that you are not going to play the same role on every team. For my function, I am the head of technology. For my ELT, I’m one of the teammates who makes a decision come to life. As part of a board, my job is to help assess as a group if the operating team is representing the right outcomes for the shareholders that you represent as well.
These are, in my opinion, the best opportunities to evolve to be a fully rounded leader. Business is the ultimate team sport. Individual excellence is valuable, but collective excellence is what creates lasting impact. I believe the hallmark of a successful technology leader is the ability to seamlessly shift between leading and serving, always doing what best advances the success of the team and the enterprise.
There’s no shortage of AI content. What did you believe was missing when you created your newsletter, “AI Signals: Navigating Change,” and how are you using it to help audiences separate signal from noise?
It began when ChatGPT was released in November 2022. I observed many of my peers trying to figure out how to bring ChatGPT into their organizations and how to drive value with it. Then, many AI companies started coming out. Many models started coming out. It was extremely hard for any company to decide what to do with the technology.
That triggered me to research and review the last 70 years of technology evolution. I wanted to understand, when a moment like this happens, whether it is through the internet, web development, mobile, or big data and machine learning, what occurs afterward that becomes durable, and what lessons can we learn from those moments?
What quickly became clear is, all of those changed how you solve a problem inside your business, not what you need to change. Eighty percent of what you do inside every business is the same. We are a 112-year-old company; 80% of what we do is the same. Go through every department — we all have to do the same things, but we have to do it faster, better, and cheaper.
So instead of chasing what is changing, I tried to go back to what is not changing in this chaotic moment. Then I thought, how can I draw attention to those things that are not changing? That’s how “AI Signals” was born. I realized that I need to write about it so that it is clear in my head. The newsletter provides a forum for input and collaboration with industry peers so we know how to make the right decisions for our organizations.
What signals are you paying closest attention to right now, and how are they shaping what you’re preparing Deluxe for next? How do you know when it’s time to change your mind?
I track what’s happening because of AI through three lenses: One, because Deluxe is all about payments and data, I keenly watch what’s happening in the payments industry, paying close attention to agentic commerce and how much it will pick up steam, and how much trust humans are placing in agents to make decisions on their behalf to make purchases, and things like that.
The second is a continuous focus on cybersecurity. As AI continues to mature, that space will continue to expose what we took for granted in the past, where we’ve said some vulnerabilities are medium and low, you can get exceptions that linger, and also how you handle the end of life for a technology. All those things are dramatically changing, because several low vulnerabilities chained together by an AI tool could become a path for malevolent AI to penetrate. And that doesn’t even include the threat posed by well-intended frontier models like those made by OpenAI, which accidentally penetrated a government database last week. The focus is on vigilance about patterns of AI behavior and how to effectively defend our companies.
The third lens is much more personal to me but also relevant to my job, which is how we view AI’s impact on talent. It is already redefining our jobs, and the biggest work in front of us is legal, compliance, HR, and technology partnering together to really figure out how to retrain our talent to use AI to stay relevant for the jobs we need to deliver. Whether you apply your lens as a leader or you have broader community concerns, we all have to contribute to the talent adjustments.
I don’t just rely on my opinions and my own research. I talk to real people at every level, and if my research does not fit well, is not practical, or is a couple of steps ahead of where the reality is, I rein it in and go from there. I have about a dozen volunteers for “AI Signals” who meet with me every Sunday, and we go through the ideas before I post. And there are articles that they’ve brought their own real examples to. Those people come from different industries and different backgrounds, so I’m pressure testing in those areas as well.
Perhaps the biggest lesson in Jayaprakasam’s approach to being a master translator is that it starts with being a master learner. He is equally intentional about staying current to develop an informed point of view as he is in challenging his own thinking, engaging peers with different perspectives, and changing course when the signals suggest he should. With virtually every company confronting reinvention in the AI era, the best leaders will need to strike that same balance, while still having the courage to move.
For more insights from Yogaraj Jayaprakasam’s leadership playbook, tune in to the Tech Whisperers.
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