An Interview With Chad Silverstein
Strategic Decision-Making Through Deep Research and Data Synthesis. AI enhances how organizations conduct research and make complex strategic decisions. With tools like ChatGPT, Claude, and Perplexity, businesses can instantly access, analyze, and distill insights from thousands of sources, ranging from academic literature and market reports to internal documents and customer data. That level of deep research was once reserved for large consulting firms, but is now accessible to lean teams and nonprofits, supporting faster, better-informed decisions.
In today’s tech-driven world, artificial intelligence has become a key enabler of business success. But the question remains — how can businesses effectively harness AI to address their unique challenges while staying true to ethical principles? To explore this topic further, we are interviewing Dr. Bogdan Daraban.
Dr. Bogdan Daraban serves as the Dean of the Andreas School of Business and Public Administration and Vice Provost for Innovation and Technology Education at Barry University in Miami, Florida. He earned his PhD in Economics from Florida State University, and his research interests include microeconomics, social entrepreneurship, applied AI and emerging technologies, and innovation in higher education. Dr. Daraban is committed to supporting Miami’s entrepreneurship and technology ecosystem through Barry University’s AI Center and the Digital Transformation (DX) Lab.
Thank you so much for joining us in this interview series. Before we dive into our discussion, our readers would love to “get to know you” a bit better. Can you share with us the backstory about what brought you to your specific career path in AI?
My journey into the world of AI is deeply rooted in my background as an economist. I’ve always been fascinated by the drivers of economic growth, and throughout history, one force stands out time and again: technology. From the steam engine to the internet, each major technological leap has redefined what’s possible in terms of productivity, innovation, and human flourishing.
Early on, I paid close attention to the emerging field of artificial intelligence. I vividly remember watching the 1997 Deep Blue vs. Kasparov chess match. Even then, I had this sense that we were witnessing the beginning of something profound. A technology that wasn’t just automating tasks, but beginning to emulate strategic thinking. For years, I followed the field with cautious optimism, waiting for the moment when AI would break out of the lab and into the broader economy. That moment came with the rise of large language models (LLMs) and generative AI a few years ago. Suddenly, access to powerful AI tools was no longer limited to research institutions or tech giants. Anyone with an internet connection could now harness AI’s capabilities.
What drew me in was the vast range of its applications and uses for this new technology. I saw how AI could improve economic outcomes by optimizing decision-making and reducing waste. But, I also saw its potential for positive societal impact: improving education, supporting nonprofits, expanding access to healthcare, and empowering communities that have traditionally been left behind in previous tech waves.
What led me to fully commit to this space was the belief that AI can be a transformative force for good across education, business, and society as a whole. It’s what inspired me to lead the creation of the AI Center and the Digital Transformation Lab (DX Lab) at Barry University. For me, AI has become a calling grounded in a lifelong curiosity about how ideas, data, and technology can help people build better lives.
Can you share the most interesting story that happened to you since you started working with artificial intelligence?
One of the most interesting and recurring stories in my journey with AI is this cycle I’ve seen play out again and again: I’ll be in a meeting, a classroom discussion, or even just reflecting with colleagues, and we’ll imagine a use case — some clever way to use AI to solve a business problem, transform a process, or rethink a product. Often, the idea feels just a little bit out of reach. The technology isn’t quite there yet, or it’s not practical enough, maybe there’s too much friction to implement. But then, almost like clockwork, just a few months or even weeks later, I’ll read about a startup or a team that’s actually doing it. It’s like the world caught up to our thoughts mid-sentence.
For a project with our students at the DX Lab, we were working on an AI agent concept for academic advising. Imagine something that could help students plan their courses, stay on track for graduation, and even connect them to support resources, all through a conversational interface. At the time, it felt like a bold idea. We were stitching together multiple tools, dealing with limitations around memory, context, and systems integration. It was more prototype than product. Then, a few weeks later, I was invited to a pitch session where a company demoed an almost identical solution. It was fully integrated and already being piloted at universities. Something we had just been sketching out in a whiteboard session was already live in the world. A “what if” conversation turns into a “somebody’s already doing that” moment in what feels like the blink of an eye. It’s a constant reminder of just how quickly things are moving. What used to be a multi-year R&D cycle is now being compressed into a few high-intensity product sprints. That recurring feeling that the future is catching up faster than we can imagine has been the most exhilarating and humbling part of working in this space. It’s a reminder of the power of technology as well as the power of human imagination, speed, and boldness in times of change.
You are a successful leader in the AI space. Which three character traits do you think were most instrumental to your success? Can you please share a story or example for each?
Visionary Thinking and Execution
I see AI as a transformative factor of production that can shift the very frontier of economic growth, societal development, and long-term prosperity. That is why I am very excited to work on positioning Barry University as an AI-integrated institution. Among other things, we are embedding AI competencies across the curriculums — not only in computer science but in all other disciplines like nursing, business, education, and the arts. I have also championed the idea that AI needs to be adopted strategically, not reactively. That philosophy drove the creation of educational programs like our new MBA in AI Strategy, a first-of-its-kind program designed to train leaders who can align AI implementation with organizational objectives. Many professionals are exploring AI tools without a clear roadmap for how to integrate them in ways that create measurable business value, and I wanted to help close the gap in the market.
Inviting Experimentation
When generative AI exploded into the mainstream, we moved quickly. The key here was to encourage as many people as possible to play around and learn from what was available. At Barry, we created courses like “AI Fundamentals and Experimentation” and “Harnessing AI for Good,” brought students into consulting projects through the DX Lab, and launched faculty training workshops. I have always believed you don’t need to have everything figured out before you start because experimentation leads to discovery.
Bridge-Builder Between Academia and Industry
I have made it a point to connect faculty, students, and community partners through our lab model. Whether it’s a local business owner learning how to use AI for inventory management or a nonprofit exploring AI for storytelling, I act as a bridge-builder between academia and business pragmatism. Our students see that they’re not just learning about AI — they’re doing AI, in ways that make a real-world difference.
Let’s jump to the primary focus of our interview. Can you share a specific example of how you or your organization used AI to solve a major business challenge? What was the problem, and how did AI help address it?
One of the most impactful examples of how we’ve used AI to solve a major challenge is the way we planned, launched, and implemented Barry University’s AI Center and the DX Lab, as well as the graduate and undergraduate curriculum. However, these initiatives weren’t meant to solely solve our institution’s needs for AI integration. They were shaped by our community’s needs for an AI-educated workforce. Our students will be better prepared for their next job opportunity and set themselves apart regardless of their discipline because of what they will be learning at our institution.
The way we went about implementing this was at a pace that’s virtually unheard of in higher education, knowing that our community needed these resources sooner rather than later. At the heart of our approach was using AI as a strategic partner in the ideation and research process to bring this to life. We leveraged AI tools to benchmark global best practices, identify gaps in current offerings, and simulate possible models for our programs. We used AI to analyze labor market trends and emerging technologies to inform our curriculum development when we designed our MBA in AI Strategy. We also used AI to generate policy drafts, build microsites, create marketing content, and promotional materials. Everyone across the university and our local community is being challenged to integrate AI in a way that fits their needs, and the AI center is available to provide the tools and education to make this a reality.
What are some of the common misconceptions you’ve encountered about using AI in business? How do you address those misconceptions?
One of the most persistent misconceptions I encounter is the belief that AI is only accessible or useful to large enterprises with deep pockets, massive datasets, and technical teams. This couldn’t be further from the truth. At the DX Lab, our mission is to empower small and medium-sized businesses, even solopreneurs, to explore, experiment, and implement AI tools in practical ways. We encourage these teams to use and learn the powerful and widely accessible tools like LLMs, image generators, and vibe coding.
Another common misconception is that AI is primarily about efficiency — doing more with less — and that it inevitably leads to job displacement. However, its most powerful potential lies not just in cutting costs, but in unlocking entirely new opportunities to create value — launching new products, personalizing customer experiences, and reimagining how services are delivered. That’s why we focus so much on teaching people to lead with curiosity and strategic thinking, not fear.
Finally, many business owners assume they need to understand complex algorithms or data science to get started. What matters most is having a strategic mindset, not a technical background. Know your business well, define the problems you want to solve, and be willing to explore solutions. That is what we teach through awareness, education, and hands-on experimentation at the DX Lab.
In your opinion, what is the most significant way AI can make a positive impact on businesses today?
Personally, I am very excited about the opportunities that AI unlocks by lowering the cost of innovation. You don’t need a full R&D lab anymore to explore new ideas. All you need is curiosity and access to the right tools, which levels the playing field. It means a small business can explore a new product idea with the same creative firepower that used to be reserved for Fortune 500 firms. Plus, we can give workers, at every level, the tools to solve problems, not just follow processes. AI is a multiplier of efficiency, and beyond that, of creativity, adaptability, and resilience.
Based on your experience and research, can you please share “5 Ways AI Can Solve Complex Business Problems”? These can be strategies, insights, or tools that companies can use to make the most of AI in addressing their challenges.
1. Strategic Decision-Making Through Deep Research and Data Synthesis
AI enhances how organizations conduct research and make complex strategic decisions. With tools like ChatGPT, Claude, and Perplexity, businesses can instantly access, analyze, and distill insights from thousands of sources, ranging from academic literature and market reports to internal documents and customer data. That level of deep research was once reserved for large consulting firms, but is now accessible to lean teams and nonprofits, supporting faster, better-informed decisions.
2. Rapid Prototyping and Innovation at Low Cost
Complex business problems often require testing multiple ideas. AI lowers the barrier to prototyping in all sorts of cases, such as generating product mockups, writing software code, simulating customer interactions, or forecasting financial scenarios. We have seen early-stage founders in our DX Lab use AI-powered tools to build investor decks, marketing content, and minimum viable products at remarkable speed.
3. Hyper-Personalization in Customer and Employee Experiences
Generative AI and predictive models allow organizations to deliver tailored recommendations, content, and support at scale. By analyzing customer data (purchase history, browsing behavior, demographics, etc.), AI algorithms can segment customers into granular groups and deliver tailored recommendations, marketing messages, and customer service responses. As a result, each consumer experience is becoming more tailored.
4. Predictive Insights for Proactive Problem Solving
One of AI’s most powerful features is its ability to detect patterns and predict outcomes, often before a human would spot them. Whether it is forecasting supply chain disruptions, identifying early signs of customer churn, or flagging compliance risks, predictive AI models actively support businesses to move from reactive to proactive approaches.
5. Automating Routine Operations
AI excels at taking on repetitive, rules-based tasks — freeing up human teams to focus on higher-value, creative work. For example, AI tools now help faculty draft personalized feedback, generate formative assessments, or even prepare lecture outlines. In business settings, this could include automating invoice processing, customer service triage, or lead qualification. Once again, it’s not about replacing the human, it’s about reallocating their talent and potential.
How can smaller businesses or startups, with limited budgets, begin to integrate AI into their operations effectively?
You don’t need a massive budget or a team of data scientists to get started with AI. Step one is a clear understanding of your operations and a willingness to experiment. A well-thought-out AI strategy allows small businesses and startups to prioritize high-impact use cases that directly address real business pain points. The key is moving from passive curiosity to hands-on experimentation. For example, many small businesses have seen immediate value from using AI to automate repetitive tasks like appointment scheduling, handling customer service inquiries through chatbots, summarizing lengthy documents, or generating marketing content. These kinds of tools are now accessible through user-friendly, low-cost platforms. Businesses that begin now will gain experience with the tools while also developing the agility and AI literacy needed to adapt quickly as capabilities evolve.
Equally important is knowing where to find support. Community resources and partnerships can lower the barriers to entry. At the AI Center and DX Lab at Barry University, for example, we offer workshops, consulting, and student-led projects designed to help local businesses explore and implement AI solutions at little or no cost. Size is no longer the barrier it once was. Strategic thinking, targeted experimentation, and smart partnerships can give even the smallest players a competitive edge in the AI era.
What advice would you give to business leaders who are hesitant to adopt AI because of fear, misconceptions, or lack of understanding?
Don’t wait to be an expert, just be curious and strategic. The most dangerous position a business can be in today is one of passive hesitation. AI is past the stage of being a fading trend. It’s cemented itself as a foundational shift in how work gets done and how value is created. The longer you wait, the wider the gap becomes between you and more agile competitors. It’s completely normal to feel intimidated by AI, as many people do. But you don’t need to understand the math behind machine learning to lead effectively in this space. A willingness to learn and the courage to ask the right questions are what it takes to understand where AI fits into your value chain and to empower your team to experiment. Fear is natural, but the cost of inaction is far greater than the cost of a few failed experiments. If I could give one piece of advice, it would be this: just start. Empower your team. Try things. You don’t need to wait for perfect conditions. The sooner you begin experimenting, the faster you will build momentum, and in this fast-moving landscape, that is everything.
In your opinion, how will AI continue to shape the business world over the next 5–10 years? Are there any trends or emerging innovations you’re particularly excited about?
It is difficult to fully grasp just how transformative AI will be over the next 5 to 10 years, because we are just beginning to explore what it means to build truly agentic systems. These are AIs that can act autonomously, pursue goals, coordinate across tasks, and interface with tools, software, and even other agents. There is massive investment going into this space, from startups to leading AI labs, and we’re watching the early stages of what could become a new digital workforce made up of swarms of intelligent agents.
As these systems evolve, we’ll likely see AI transcend supporting isolated tasks to orchestrating entire workflows. Businesses will move from deploying AI as a productivity booster to using it as a core part of how they operate and make decisions. It raises fundamental questions about coordination, delegation, and organizational design. In a world where your AI workforce can be scaled up instantly and taught new skills overnight, traditional advantages like organizational size, proprietary processes, and legacy know-how may diminish.
What excites me most and what we’re preparing our students for at Barry University is the emergence of a new kind of job: the AI agent manager. These are leaders who understand how to task, train, evaluate, and coordinate AI agents to deliver business outcomes. In the same way that the Industrial Revolution created factory foremen and production managers, the AI era will require human intelligence to direct, govern, and align AI agents. That will be a defining skill set for the workforce of tomorrow.
How do you think the use of AI to solve business problems influences relationships with customers, employees, and the broader community?
AI will increasingly become a natural part of how we organize business and human activity, similar to how spreadsheets, email, or smartphones once did. But while the tools evolve, the fundamental need for human interaction doesn’t disappear. In fact, one of the most powerful insights from economic thinkers like Hayek and Ostrom is how our ability to cooperate, coordinate, and build trust-based systems drives progress. Everything is built on relationships.
AI may change the surface of those interactions by automating support, filtering data, or personalizing content, but the human layer remains necessary. As humans, we will still crave empathy, connection, and trust. That’s especially true in customer relationships, where authenticity matters; in employee dynamics, where meaning and culture drive engagement; and in communities, where shared values sustain long-term impact.
You are a person of great influence. If you could start a movement that would bring the most amount of good to the most amount of people through AI, what would that be? You never know what your idea can trigger. 🙂
Education is very important to me, so it would be the global advancement of evidence-driven education facilitated by AI. The type of education that goes beyond information delivery and drives deep, transformative learning. The kind that cultivates critical thinking, fosters empathy, and empowers people with the tools to distinguish evidence from propaganda, reason from manipulation. I believe an AI that promotes truth and understanding — built with transparency, integrity, and awareness of its limitations — could become one of humanity’s most powerful forces for good.
AI gives us an opportunity to democratize the highest-quality education by bringing knowledge, truth discovery, and intellectual empowerment to every corner of the world. Imagine personalized tutors available to anyone with a smartphone, guiding people not only through reading, math, and science, but through moral reasoning, media literacy, and the fundamentals of civic cooperation. It would help elevate minds and, more importantly, unite people across borders, cultures, and beliefs, fostering mutual respect and peace in an increasingly complex world. That is the movement I would champion: AI that educates the world, not just to know more, but to understand more deeply and live more wisely
How can our readers further follow you online?
LinkedIn is the best medium to connect with me and follow the exciting work we are doing at Barry University through the AI Center and the DX Lab.
This was great. Thank you so much for the time you spent sharing with us.
About the Interviewer: Chad Silverstein is a seasoned entrepreneur with 25+ years of experience as a Founder and CEO. While attending Ohio State University, he launched his first company, Choice Recovery, Inc., a nationally recognized healthcare collection agency — twice ranked the #1 workplace in Ohio. In 2013, he founded [re]start, helping thousands of people find meaningful career opportunities. After selling both companies, Chad shifted his focus to his true passion — leadership. Today, he coaches founders and CEOs at Built to Lead, advises Authority Magazine’s Thought Leader Incubator.
Dr Bogdan Daraban Of Barry University On How Artificial Intelligence Can Solve Business Problems was originally published in Authority Magazine on Medium, where people are continuing the conversation by highlighting and responding to this story.