Artificial intelligence may be advancing at extraordinary speed, but the companies set to gain the most from it will not necessarily be those building the models. The larger opportunity lies in rebuilding how businesses operate—from decision-making and customer service to reporting, acquisitions, and physical automation. In this interview, technology entrepreneur and investor Dmitry Khanov explains why the next decade will belong to companies that become AI-native, rather than those that simply add AI features to existing workflows.
Khanov is the co-founder of Allbionics, a Ukrainian medtech company developing affordable bionic prosthetic arms, and an investor through Talentir Capital. Over the past two decades, he has built, scaled, and acquired businesses across software, digital infrastructure, internet platforms, and technology services.
Now working within the European technology ecosystem, he focuses on AI, operational transformation, and technology-enabled industries, collaborating with founders, investors, and companies at different stages of growth.
You’ve mentioned that AI is no longer just a software story. What convinced you that operational transformation, not model development itself, will create the biggest opportunities over the next decade?
Watching companies adopt AI convinced me.
Almost every executive now agrees that AI is important. Yet many organizations struggle to generate meaningful business results. The reason is simple: they’re trying to insert AI into workflows that were designed for people.
The real value doesn’t come from replacing a task. It comes from redesigning an entire operating model. Once you rethink how decisions are made, how information flows, and how work moves through an organization, AI stops being a productivity tool and becomes an economic advantage.
That realization has fundamentally changed our own business. At Trinetix, we spent years helping enterprises build software through traditional services and time-and-material engagements. Today, our conversations with clients are increasingly about something much bigger: how to redesign their organizations to become AI-native businesses. We are no longer just delivering software – we are helping companies rethink how they operate in the AI era.
Many companies are investing heavily in AI, yet relatively few are seeing transformational business outcomes. What separates companies that genuinely become AI-driven from those that simply add AI features?
The companies that succeed don’t ask, “Where can we use AI?”
They ask, “If we were starting this company today, how would we build this process differently?”
That’s a completely different conversation.
Most organizations are optimizing existing workflows. AI-native organizations redesign them from scratch. The difference is similar to putting an electric motor into a horse carriage versus designing an automobile.
What’s one assumption about AI that you believe the industry is getting fundamentally wrong today?
That AI itself is the competitive advantage.
Models will continue to improve and become more accessible. Competitive advantage will come from proprietary data, operational execution, organizational learning, and the speed with which companies redesign themselves.
Technology diffuses. Better operating systems are much harder to copy.
You build companies, invest in them, and sometimes acquire them. How does wearing all three hats change the way you look at AI compared to a traditional VC?
Traditional investors often ask whether AI will improve a product.I ask whether AI can fundamentally change the economics of the business. Can it reduce the cost of delivering value? Can it increase revenue per employee? Can it shorten cycle times? Can it create a business that competitors structured around human workflows simply cannot match? That’s an operator’s perspective.
Has operating businesses yourself made you more optimistic or more skeptical about the speed at which AI can transform companies?
Both. I’m far more optimistic about AI’s long-term impact than most people. But I’m also much more realistic about implementation. Technology moves exponentially. Organizations don’t. The limiting factor is rarely AI. It’s management, incentives, culture and the willingness to redesign processes that have existed for decades.
You’ve argued that AI is becoming an acquisition strategy rather than just another software layer. Can you explain what that looks like in practice?
Historically, acquisitions were about buying market share, customers or revenue.
I think AI is creating an entirely new type of acquisition opportunity.
Imagine acquiring a traditional healthcare business, such as a network of dental or fertility clinics. Most investors would focus on occupancy rates, EBITDA and expansion potential. I would ask a different question: How would this business look if it were built today with AI at its core?
Instead of simply improving the existing operation, I would redesign it from the ground up. Patient acquisition becomes AI-driven and highly personalized. Administrative workflows, scheduling, documentation and billing are largely automated. Clinical teams spend less time on repetitive tasks and more time with patients. Management decisions are supported by real-time operational data rather than monthly reports. Every layer of the organization becomes more efficient.
In that scenario, AI isn’t another software tool—it’s the mechanism that fundamentally changes the economics of the business. The same clinics, the same doctors and the same demand can produce a completely different business simply because the operating model has been rebuilt.
That’s why I believe the next generation of acquisitions won’t be about buying assets. They’ll be about buying operational transformation opportunities.
Which industries do you believe are still dramatically undervalued because investors underestimate AI’s ability to redesign operations rather than products?
Professional services, healthcare and other service industries. Mostly, industries that employ millions of knowledge workers and still rely on workflows designed decades ago. AI doesn’t have to invent a new market. It simply needs to redesign existing ones.
When evaluating acquisition opportunities today, what operational signals tell you that AI could create disproportionate value?
I look for operational friction. How much manual coordination exists? How fragmented is information? How repetitive are decision processes? How much of the company’s value depends on moving information between people?
Ironically, businesses that appear operationally inefficient often present the greatest AI opportunity.
If you acquired a traditional company tomorrow, what are the first three operational processes you would redesign with AI and why those first?
First, internal knowledge management. Most organizations already possess the knowledge they need. They simply can’t access it efficiently.
Second, customer support and customer operations. Not just automation, but intelligent routing, prioritization and decision support.
Third, management reporting. Executives spend enormous amounts of time collecting information instead of making decisions. AI should eliminate reporting work and maximize decision-making time.
Many people see robotics as the next frontier after generative AI. From your perspective, what’s missing from today’s conversation?
I think we’re looking at robotics the wrong way.
Today, AI is automating digital work – everything we do behind a computer. The next logical step is for AI to enter the physical world, and it will do so through robots.
That’s why I pay close attention to companies like Tesla, Figure AI and others investing heavily in humanoids. Elon Musk has repeatedly said he believes Optimus could become even more significant than Tesla’s car business. I don’t see that as hype – I see it as a signal.
I believe we should already start thinking about a future where having one or even two humanoid robots at home is completely normal. The biggest opportunity won’t be the robots themselves, but the businesses and industries that are redesigned around them.
If you were building your first company today, knowing everything you know now about AI, where would you start?
I probably wouldn’t start with an AI company. I’d start with an existing industry that has inefficient operations. Then I’d rebuild that business from the ground up around AI. The biggest opportunities aren’t necessarily in creating new technology. They’re redesigning how existing industries work. That’s where I believe the next generation of great companies will emerge.
