An Interview With Chad Silverstein
AI doesn’t solve problems on its own — it amplifies your approach. If your logic is flawed, it will amplify that as well.
As a part of this series, we had the pleasure to interview Nick Filatov.
Nick Filatov is a technology executive and entrepreneur with over 25 years of experience in tech, including 14 years in TravelTech. He built and successfully exited a major online travel agency, gaining deep insight into both legacy systems and modern digital platforms. As the CEO and founder of GDS42, he focuses on leveraging AI and automation to transform travel operations and bridge the gap between traditional infrastructure and the expectations of next-generation travelers.
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?
What brought me to this path was a very practical problem that I had been trying to solve for quite a long time within an online travel business. Earlier in my career, I built one of the large online travel agencies in Eastern Europe. We were selling more than two million airline seats per year, and the team grew to over 200 people.
The main focus was always on sales, but post-booking service was a constant pain point. A significant part of the team — almost a third — was dedicated to support and post-sales operations. These were highly manual processes, difficult to scale, and they became especially painful during situations like the pandemic.
At that time, we tried to automate these processes using traditional, fully algorithmic approaches, but it simply didn’t work economically. It turned into endless development with no real efficiency.
AI became the turning point. On the one hand, it’s clearly a major technological trend, and companies that don’t use it risk falling behind. But more importantly, in our case, AI made it possible to solve a problem that was previously impossible to solve in an economically viable way. It became the cornerstone that allowed us to rethink the entire approach.
Can you share the most interesting story that happened to you since you started working with artificial intelligence?
One of the most fascinating aspects of working with AI is how it can surface insights that even experienced professionals might miss.
In our case, we trained AI on massive volumes of documentation — fare rules, booking system logic, historical cases. Even the most experienced specialists cannot hold all of that knowledge in their heads at once. AI, however, can instantly retrieve and connect that information.
What surprised us was that sometimes it would highlight patterns or edge cases that even domain experts hadn’t considered or had simply forgotten. Not in a “hallucination” sense, but in a way that actually expands the understanding of the system itself. It’s those moments — when AI doesn’t just replicate knowledge but augments it — that are the most interesting.
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?
- Openness to change and experimentation: Right now, there is a clear divide between people who embrace innovation and those who resist it — often out of fear. Being open to trying new things is critical.
- The ability to stay a learner: It’s important not to rely on past achievements. The willingness to “become a student again,” to continuously learn and adapt, is essential. The pace of change requires constant reinvention.
- Critical thinking: AI should not be blindly trusted. It doesn’t replace you — it amplifies you. That means it can accelerate both good and bad decisions. Maintaining critical thinking and validating outputs is crucial.
More broadly, I don’t believe AI will make people less intelligent. Instead, it will change the set of skills that are valuable. Just like in the past, when entirely new industries emerged, the definition of “useful skills” evolved over time.
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?
A good example is automating fare rule interpretation and ticket servicing. Traditionally, this requires months of training and a deep understanding of booking systems, as well as the ability to process large amounts of context for each individual reservation. It’s complex and time-consuming work.
With AI, we were able to process all of this much faster. What was surprising is that we initially expected AI to perform worse than humans and require a lot of fine-tuning. But in reality, we are now seeing that it often makes fewer mistakes than humans when interpreting rules and executing these processes.
What are some of the common misconceptions you’ve encountered about using AI in business? How do you address those misconceptions?
One of the biggest misconceptions is that AI is some kind of magic box. People think you can just throw in an unstructured problem and it will magically solve everything for you. That’s not how it works. AI doesn’t solve problems on its own — it amplifies your approach. If your logic is flawed, it will amplify that as well.
Especially in industries like travel, where every action is tied to financial transactions, you cannot rely on AI alone. There must be strong control, validation, and a combination of deterministic and AI-driven approaches. If you rely entirely on AI without safeguards, it will inevitably lead to errors.
In your opinion, what is the most significant way AI can make a positive impact on businesses today?
The most significant impact is acceleration. AI reduces manual work, which is often inefficient and error-prone, and speeds up processes dramatically. In industries like travel, this directly improves operational efficiency and scalability.
Ok, let’s dive deeper. 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. If possible, please share examples or stories for each.
1. Automating complex, knowledge-heavy tasks
AI can handle processes that require deep contextual understanding, such as interpreting rules or documentation. For example, in the travel industry, fare rules are extremely complex and require months of training for specialists. AI can process large volumes of this documentation instantly and apply it to real cases, reducing the need for deep manual expertise in every operation.
2. Reducing human error
In repetitive and detail-sensitive operations, AI can outperform humans in consistency and accuracy. In practice, we’ve seen that even experienced specialists make mistakes when dealing with large volumes of similar tasks, especially under pressure. AI, when properly controlled and validated, can significantly reduce these errors and improve overall quality.
3. Increasing operational speed
Tasks that previously took hours can now be completed in seconds. This is especially noticeable in workflows where multiple systems or manual checks are involved. What used to require back-and-forth between teams can now be handled almost instantly, which changes not only efficiency but also customer experience.
4. Unlocking previously unsolvable problems
Some challenges were not economically viable to solve before AI. Now they are. There were cases where automation was theoretically possible, but required endless development and still didn’t justify the cost. With AI, these same problems can now be solved faster and more efficiently, making them viable from a business perspective.
5. Enabling scalability without proportional headcount growth
Businesses can grow without linearly increasing operational teams. Traditionally, scaling operations meant hiring more people, especially in support and back-office functions. With AI, companies can handle significantly larger volumes with the same or even smaller teams, which fundamentally changes unit economics and scalability.
How can smaller businesses or startups, with limited budgets, begin to integrate AI into their operations effectively?
For smaller businesses and startups, AI is actually a huge advantage. Right now, we are seeing a clear split between companies that adopt AI and those that don’t. Companies that try to continue operating with old processes and without understanding AI will quickly fall behind, especially if they don’t have strong market protection.
At the same time, small teams can now be extremely effective. Even teams of three to five people, if they have domain expertise and understand how to work with AI and modern development approaches, can build very powerful products. In many cases, being small is no longer a limitation — it’s a competitive advantage.
What advice would you give to business leaders who are hesitant to adopt AI because of fear, misconceptions, or lack of understanding?
The real risk is not adopting AI. If you choose not to implement it, competitors who do will move faster and outperform you. So the main question is not how to adopt AI, but what happens if you don’t. If you don’t, the market will eventually leave you behind.
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?
Right now, we are in a phase of rapid growth, but this pace will not continue indefinitely. At some point, the development will stabilize and move into a more mature phase. We are already seeing signs that instead of one universal AI, there will be more specialized models focused on specific domains.
AI will transform industries rather than simply replace them. Just like past technological shifts created entirely new ecosystems, the same will happen here. Some roles will shrink, but new ones will emerge. It won’t be an overnight change — this will happen gradually, and people will adapt over time by developing new skill sets.
How do you think the use of AI to solve business problems influences relationships with customers, employees, and the broader community?
AI will definitely change how people interact. Technology has always shaped communication norms. For example, phone calls used to be normal, but now they are often perceived as intrusive because messaging has become the default. AI will drive similar changes.
We already see this in hiring processes, where AI is used for screening, evaluation, and even matching candidates to teams not only by skills but also by psychological compatibility. On one hand, this can make hiring more selective. On the other hand, it improves the quality of teams and helps build stronger, more cohesive organizations.
Overall, AI will redefine what is considered normal in communication and collaboration.
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. 🙂
The most impactful area would be education. The best thing we can do is give people knowledge — help them better understand how the world works and how to use AI effectively.
AI itself is just a tool. The real value comes from how people use it. And the more people are educated and capable, the more value society as a whole can create.
How can our readers further follow you online?
Our official website — https://gds42.ai/
My personal LinkedIN account — https://www.linkedin.com/in/nick-fil/
Company’s website — https://www.linkedin.com/company/gds42ai
Thank you for sharing these insights!
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.
Nick Filatov of GDS42.ai 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.