Steve Lucas, CEO and Chairman of Boomi, is the author of Digital Impact and a multi-time CEO with nearly 30 years of leadership experience in enterprise software. He has held CEO and senior executive roles at some of the world’s leading cloud organizations, including Marketo, iCIMS, Adobe, SAP, Salesforce, and BusinessObjects.
Boomi is a leading provider of cloud-based integration platform as a service (iPaaS), helping organizations connect applications, data, and systems across hybrid IT environments. Its low-code platform enables rapid integration, automation, API management, and data synchronization to support digital transformation and streamline operations for businesses of all sizes.
As a multi-time CEO, how has your leadership approach evolved in the face of AI-driven disruption? What’s different about leading now vs. a decade ago?
Leading today is fundamentally different from even three years ago, let alone a decade. Back then, digital transformation was a strategic advantage. Today, it’s a survival imperative. AI-driven disruption has completely reset expectations around speed, adaptability, and data-driven decision-making. As a CEO, that means I no longer have the luxury of linear planning or incremental improvement. The pace of change, particularly in my industry, demands bold, system-level thinking and execution.
If you’re thinking that AI is just another tool in your stack, you’re wrong. It’s a force multiplier. Or at least it can be if you architect your organization with AI at the center of everything you do. In every discussion with my team, I always ask: “Have we thought about how we can use AI in this initiative?” It’s literally part of every discussion. That’s changed how I lead. I’ve always been hyper-focused on integration, data transparency, and breaking down silos. But now, all of that is in service of making AI better. Leadership is still about aligning teams around goals. But now AI is at the heart of achieving those goals.
Above all, today’s CEOs must be deeply human in how they lead. AI is accelerating everything, and that can worry people. It’s why the human element (our values, our judgment, our empathy) must guide how we deploy it. It’s no longer just about digital transformation. It’s about human transformation.
Your book argues that AI will fail without fixing digital infrastructure. Can you explain what you mean by “digital fragmentation” and why it’s such a critical issue right now?
Digital fragmentation is the silent killer of enterprise AI efforts. Over the last two decades, organizations have raced to digitize their workplaces, adding more systems, apps, clouds, and platforms. But in that rush, few paused to build meaningful integration between them. The result is a tangled web of disconnected technologies and data silos that can’t talk to each other. The sum was less than all of those parts.
Now, AI is forcing companies to finally confront that fragmentation. AI systems require clean, connected, real-time data to function well. But most businesses are trying to scale AI across an unstable data foundation. That’s why, according to industry data, more than 70% of enterprise AI projects fail. It’s not because AI doesn’t work, but because the digital environment around it is too fragmented for it to succeed.
In Digital Impact, I argue that before any leader invests another dollar in AI, they must first fix the foundation. That means creating an integrated, AI-ready architecture that connects systems, harmonizes data, and enables intelligent automation. Otherwise, AI will only amplify the chaos.
In “Digital Impact,” you highlight real-world examples where integrated tech is making a difference — from disaster relief to sustainable farming. What case study surprised or inspired you the most while writing the book?
The example that stuck with me most was the work done during a series of natural disasters to provide rapid emergency relief through integrated systems. In one case, multiple disconnected government and aid organizations had to collaborate in real-time, sharing data on everything from infrastructure damage to the location of vulnerable populations.
Historically, that kind of coordination would’ve taken days if not weeks. But with integrated digital infrastructure and automation, they were able to respond in hours. Emergency supplies were rerouted, housing was secured for displaced families, and aid was delivered with a level of speed and precision that saved lives.
That case showed to me what’s possible when we stop treating integration as an IT problem and start seeing it as a human imperative. Technology is at its best when it disappears into the background and just works seamlessly, intelligently, and in service of real people.
The subtitle of your book references “The Human Element” of AI-driven transformation. How do we ensure people remain at the center of this technological shift?
That’s the most important question of all. In Digital Impact, I argue that the most powerful AI strategy is a human strategy. We’re not building AI for machines. We’re building it to serve people. But it’s easy to lose sight of that in the rush to automate, scale, and optimize.
To keep people at the center, we must design AI systems that enhance human capacity, not replace it. That means creating tools that reduce digital friction, support better decision-making, and free up time for more meaningful human work. It also means being deliberate about transparency, fairness, and ethics when AI makes decisions that affect people’s lives.
Most importantly, we need to equip every employee with the skills, access, and confidence to work alongside AI. It’s about melding the best of human and machine intelligence. This task isn’t relegated to just data scientists or engineers. This is a moment for inclusive transformation, not exclusive innovation. If the human element is overlooked, AI will become just another tech fad. But if we get it right, it can be the most humanizing force in the digital age.
You mention that organizations are building skyscrapers on sand. What are some of the most common architectural mistakes companies make when adopting AI?
The most common mistake is treating AI as a plug-and-play solution rather than an ecosystem evolution. Leaders are often dazzled by the promise of AI and jump straight into implementation without addressing the digital sprawl beneath it. That’s like building a penthouse suite on top of a collapsing building.
One major architectural issue is siloed systems. Most enterprises run dozens, even hundreds, of disconnected applications. Their data is locked in proprietary formats, spread across clouds, departments, and platforms. AI can’t thrive in that environment. It needs clean, consistent, real-time, interconnected data.
Another big mistake is underestimating the importance of integration and automation. Companies implement AI pilots that work in isolation — but they don’t scale because the underlying workflows aren’t automated or integrated across systems. It’s like putting a rocket engine on a bicycle.
Digital Impact lays out what I call “AI-readiness” architecture, which is a set of principles for building modular, connected, secure, and scalable systems. Without that, AI is just window dressing.
Many leaders believe throwing more AI at problems will drive results. What’s the risk in that mindset, and how can your book help reset expectations?
The biggest risk is mistaking activity for progress. More AI doesn’t automatically mean better outcomes if you apply it to broken, fragmented systems. If you don’t fix the underlying process, AI will just amplify the existing flaws. You’ll automate inefficiency, scale bias, and accelerate chaos.
We’ve seen organizations spend millions deploying AI models only to hit a wall because they lacked clean data, integrated workflows, or change management strategies. In Digital Impact, I call this the “shiny object trap.” Leaders chase the latest model or tool, but they forget to ask the most important question: Is our organization ready to use this well?
The book is a wake-up call. It helps reset expectations by grounding AI transformation in business reality. It’s not about how much AI you deploy but how thoughtfully you apply it, how well it integrates with your ecosystem, and how it serves your people.
This is the moment for clarity over hype, architecture over acceleration, and people over platforms.
You’ve said, “SaaS as we know it is dead.” Can you elaborate on what replaces it in an AI-first world — and how agents will transform our interaction with software?
Absolutely. SaaS as we know it – tabs, logins, dashboards, manual workflows – is already on life support. The next era is about intelligent agents: AI-powered copilots that autonomously take actions on your behalf based on the parameters you set and the data you provide.
In an AI-first world, software becomes invisible. You won’t “use” apps in the traditional sense. Instead, you’ll tell agents what you need, and they’ll execute those tasks by accessing apps and systems. Want to onboard a new employee? An agent will spin up the right tickets in IT, provision access, update your HRIS, and send the welcome email – all without a human clicking through five systems. It’s fascinating!
Agents are replacing interfaces. They’re redefining productivity. SaaS isn’t going away, but how we interact with it is fundamentally shifting. The companies recognizing this now will outpace those still optimizing for clicks and dashboards.
Boomi is pioneering AI agents that can work across apps. In practical terms, what kinds of tasks are these agents taking over today — and what’s next?
Our Boomi Enterprise Platform automates time-consuming tasks humans hate, and systems can’t handle alone. It’s the messy middle. Think about syncing customer data between Salesforce and NetSuite, resolving supply chain discrepancies, or validating invoices across finance platforms.
These aren’t flashy use cases. They’re foundational. And that’s the point. We’re not talking about replacing humans. We’re talking about augmenting teams by removing digital friction and connecting data across systems so people can focus on high-impact work.
What’s next? Context-aware agents that don’t just follow rules but learn. Agents that understand business intent and adapt to change. We’re building toward a world where every employee has an AI partner that works across apps, learns preferences, and proactively solves problems before they escalate.
What role do platforms like Boomi play in helping organizations shift from traditional software use to intelligent automation powered by agents?
Boomi is the connective tissue. You can’t deploy agents effectively in a fragmented, disconnected ecosystem. Without integration, automation, and clean data, agents are like brilliant minds stuck in a digital traffic jam.
Boomi clears the road. We unify apps, automate workflows, and expose data in ways agents can actually use. Think of us as the infrastructure layer for agentic AI. We’re plugging into hundreds of systems, enabling automation across them, and delivering real-time intelligence to agents so they can act with context.
We’re not just enabling AI. We’re empowering it to be useful. That’s the difference between cool tech demos and scalable transformation. With Boomi, organizations can make the leap from software as a destination to AI as an action engine.
What inspired you to write this book now, and how do you hope it will change how tech and business leaders think about transformation?
I wrote Digital Impact because we’re standing at a pivotal moment in the history of technology. I believe most leaders are focused on the wrong thing.
Right now, everyone’s talking about AI. But few are talking about how AI actually works in the real world. The truth is you can have the most powerful AI on the planet, but if your systems are fragmented, your data is stale, and your infrastructure is brittle, that AI is useless.
I’ve seen too many digital transformation efforts fail because they ignored the plumbing: the connections, the automation, the data readiness. I wanted to expose that hard truth, but also offer a way forward. This book is a blueprint for how to make AI and transformation actually work, not just theoretically, but practically, system by system, team by team.
Is there a core message or call to action you want every reader of Digital Impact to walk away with?
Yes! Fix the foundation.
We can’t keep building tech empires in digital quicksand. Before you chase the next AI headline, ask: Are our systems connected? Is our data flowing freely? Are our teams aligned around outcomes, not tools?
Digital Impact is a call to return to first principles. Integration. Automation. Human-centered design. These are not “back office” concerns; they’re the front lines of transformation.
The leaders who succeed in this era will be the ones who build infrastructure that’s intelligent, agile, and invisible. My hope is that this book helps more leaders focus on what matters most, so we can all deliver on the promise of AI and create a better digital future for everyone.
Thank you for the great interview, readers who wish to learn more should read Digital Impact or visit Boomi.
