Demian Shevko reports in New Voice of Ukraine:
After the invasion, Ukraine accelerated decision-making technologically. A new generation of defense startups, data-processing teams, and AI developers emerged. Integrated battlefield awareness platforms aggregate drone feeds, satellite imagery, seismic and acoustic sensors, reconnaissance, and frontline reports into a unified operational picture, enabling faster, decentralized decisions. Reaction time has been compressed to minutes. Fighting within a kill zone means processing large volumes of data as the technological scale and intensity of the battlefield is redefining how information itself determines combat. Targeting effectiveness could increase 50% by choosing the right tool for the right target. Optimizing data flows can raise effectiveness to 90%. The remaining 10% - the part that cannot be solved through conventional programming - is where AI becomes critical.
Since the first days of Russia’s full-scale invasion, the war between Moscow and Kyiv has been not only a clash of armies, but a race of technologies. In an interview with G-NEXT INTELLIGENCE CEO Oleksii Teplukhin, we explore how data-driven warfare, artificial intelligence, battlefield awareness systems, and the rapid integration of drones have reshaped combat — and why traditional military doctrines, including NATO’s, no longer fully apply to this conflict.
At the outset, many assumed Russia’s larger defense-industrial base would provide a decisive advantage. On paper, the imbalance of resources seemed overwhelming. Yet battlefield reality quickly proved otherwise. Ukraine’s advantage was not scale — it was speed, flexibility, and the ability to turn frontline experience into technological innovation.
Beginning in 2014, Ukrainian engineers and volunteers integrated unmanned aerial systems into reconnaissance, artillery adjustment, logistics, and strike missions. Improvised solutions evolved into a dynamic ecosystem of drone operators, software developers, and analysts working in near-real time with combat units. Rapid iteration — testing, adapting, redeploying — became a defining trait.
After the full-scale invasion, Ukraine accelerated decision-making both tactically and technologically. Traditional procurement systems were too slow for modern combat. A new generation of defense startups, data-processing teams, and AI developers emerged to fill the gaps. Integrated battlefield awareness platforms began aggregating drone feeds, satellite imagery, reconnaissance, and frontline reports into a unified operational picture, enabling faster, decentralized decisions.
Artificial intelligence became a force multiplier, assisting with object recognition, target identification, and prioritization, compressing the time between detection and strike. Under pressure, Ukraine’s once underfunded defense sector transformed into a laboratory of wartime innovation.
In just a few years, Ukrainian military tech has moved from near nonexistence to drawing serious interest from Israel, the United States, and multiple European nations seeking cooperation and access to Ukraine’s combat-tested technologies.
Demian Shevko: You’ve often said in previous interviews that modern war is defined by data — that it is, in essence, data-driven warfare. From your perspective, how has the Russia-Ukraine war become a point of no return specifically in terms of information and analytics?
Oleksii Teplukhin: First of all, it became a point of no return in every sense. The simplest example: none of the existing military doctrines of any country in the world fully apply to this war. Not even NATO doctrine.
You simply cannot fight according to a doctrine that does not account for FPV drones operating at this scale. Traditional doctrine says an armored fist operates in a certain way — but it no longer works that way.
The same applies to data. Intelligence standards and data-processing models were built around reporting cycles: collecting data, analyzing it, producing reports. But the war has become so dynamic — primarily because of FPV drones — that the time between detecting a target and striking it is minimal.
Take multiple launch rocket systems (MLRS) as an example. An MLRS fires an initial ranging package — two, three, six rockets. Reconnaissance drones observe the impact. Corrections are made, and then a full salvo is launched. After that, the system leaves.
If an artillery piece remains in position, you might still destroy it later. But an MLRS will not be there. If you don’t eliminate it within seven minutes — sometimes five — it’s gone and will return later. Your reaction time has been compressed to minutes.
This fundamentally changes the entire picture of the battlefield.
Consider the concept of a “kill zone.” Working within a kill zone means tracking large volumes of data about enemy movement and accumulating it. For example, the enemy may advance one by one. Most are eliminated. But we see: one ran through, then another, then another. Aggregated data shows that eight personnel have accumulated in one location. That signals a potential assault forming there.
Without real-time data aggregation and analytics, you simply cannot see that pattern — and you lose the initiative.
Demian Shevko: Is all of this analyzed automatically? In other words, is it done by machines rather than people?
Oleksii Teplukhin: That’s precisely the issue. No army in the world is fully prepared to work with data in a way that is 100% effective. If we talk about the most experienced armies in terms of data usage right now, it’s the Russian and Ukrainian armies. And in both cases, much of it is still improvised — maybe 5% of what it should ultimately be.
It cannot be normal that if Telegram goes down, the Russian army loses communication. Or if Starlink is down — for Ukraine or Russia — and suddenly we are offline. That should not be possible in the long term. Yet we see this everywhere: the volume of data is growing exponentially, and it must be processed much faster.
At the same time, innovation is emerging in every direction — especially in detection. New sensors are appearing. Take seismic sensors, for example. Few would have imagined they would play a role in this war. Some developers claim these sensors can detect moving equipment at distances of up to 700 meters based on seismic data. There are also acoustic sensors.
Who could have predicted that drones would be everywhere? In practice, the traditional “fog of war” is disappearing. Previous wars operated on the assumption that there were blind spots — unknowns, areas where information was incomplete. That uncertainty shaped strategy.
Now the question becomes more philosophical. We are not the only war in the world. NATO, the United States, Israel — they all conduct operations. The Israel-Iran confrontation, for example. The difference is that here, at this scale and intensity, the technological density of the battlefield is redefining how information itself determines combat.
Demian Shevko: Why do you think this particular war became such a Rubicon? Is it because two more or less technologically comparable countries are confronting each other? Or was it simply a matter of time?
Oleksii Teplukhin: First, this is the only full-scale war in the world right now. There is no other war with a 1,500-kilometer front line.
It is also the only war where both sides are using the full spectrum of weapons. This is a complete, high-intensity military process. And why did it happen this way? Largely because of Ukraine’s resistance.Ukraine understood something fundamental. I realize a country doesn’t “understand” in a literal sense, but collectively Ukraine grasped that our only chance to survive was to achieve technological superiority.
If we talk about the military sphere today, the main problem is not simply a lack or surplus of data. It is the inability to use data effectively everywhere it is needed. Data arrives too late. It arrives in the wrong format.
Take counter-battery radars. They detect artillery fire across the front. That’s valuable information for an artillery intelligence officer. But if decisions are made based on single shots, efficiency suffers. You might redirect reconnaissance drones to investigate a position that fired once from a forest two days ago, wasting resources on a minor target.
Or consider strike statistics. A drone unit operates with artillery support. If we do not collect and analyze all that data, we cannot maximize effectiveness. We may fail to see that a certain type of target in specific terrain should be hit with a particular munition that delivers 90% effectiveness, while another system delivers only 50%. If we adjust accordingly, the unit’s effectiveness could increase by 50% simply by choosing the right tool for the right target.
Information loss is critical. A radar shows a detection on the screen; then another replaces it. If you miss it, it’s gone. Or someone sends crucial information via voice message — you miss it or fail to act on it. Your operational effectiveness drops by exactly the value of that lost information, because time passes and the window closes.
Demian Shevko: Artificial intelligence has already influenced many areas of our lives. Even journalists use AI extensively. If all AI modules were removed from your system today, how much would that affect its effectiveness? How significant is the role of AI?
Oleksii Teplukhin: The system would remain effective. And I would say the role of artificial intelligence is still far from fully realized — very far. In my view, it currently delivers perhaps 5% of what it is ultimately capable of. That’s not based on formal research, just my professional intuition.
Right now, AI’s role in decision-making is more like the “cream on top.” Let me explain. If we aim for 100% operational effectiveness — meaning everything that can be optimized is optimized — then without proper data-processing systems and technologies that structure and streamline information, efficiency can drop by a factor of ten in certain situations. Simply organizing and optimizing data workflows can raise effectiveness to roughly 90% of the maximum.
The remaining 10% — the part that cannot be solved purely through conventional programming — is where artificial intelligence becomes critical. That’s not universally true in every case, but broadly speaking, AI fills the gap that traditional systems cannot.
I wouldn’t say AI is fully decisive yet. It will be. There are already areas where tasks are impossible without it. Take image recognition, for example. There is simply no way to hire a million people to manually review all the video footage collected across the front and identify equipment in real time. It’s impossible. AI makes that feasible.
So today AI is an accelerator and an enabler. Tomorrow, it will likely become a defining element.
Demian Shevko: Let’s touch on cooperation between the state and the private sector in defense. From your experience, how has the interaction between tech companies, startups, and the government — particularly the Ministry of Defense — changed during the war?
Oleksii Teplukhin: These are very complex relationships; they cannot be simple. There are certain things the state objectively cannot delegate to private companies. At the same time, the state can no longer function without the private sector if it wants to deliver everything that’s required.
We see this in practice. There have been cases of solutions developed under state oversight that turned out to be inefficient. I don't want to name concrete produces but, some systems were formally implemented through private contractors, while in reality they were essentially state-led projects. It could not have been built effectively in that framework. A strong private IT company operating independently would likely have delivered a better result.
So we constantly find ourselves in this tension.
At the same time, I can say clearly that the state has not taken the negative path one might fear — trying to monopolize everything and block private initiatives. That has not happened. And that is very positive.
Could the state be more effective in organizing cooperation? Absolutely. One hundred percent — a thousand percent. There needs to be deeper engagement and more structured institutional work. It requires deliberate design: how to involve private companies, how to scale solutions, how to integrate them properly.
That said, there are initiatives that are genuinely effective and producing results. Brave1, for example, is undoubtedly one of the strongest and most successful initiatives in this space.
Demian Shevko: There has been a view that Ukraine is more effective at inventing and developing new technologies, while Russia, because of its centralized vertical structure, is more effective at scaling them. Fiber-optic drone control is often cited as an example. The idea was proposed in Ukraine early in the war but did not take off at scale. The Russians later adopted and scaled it.
Oleksii Teplukhin: I don’t work directly on analyzing the Russian side. That is a very difficult and sensitive job handled by specialized intelligence units. I wouldn’t place myself alongside the work they do.
From my own level of expertise, I can say this: in terms of innovation, they are significantly behind. We see from intercepted messages that they are trying to create analogues of systems like Delta and Griselda. But copying rarely makes sense. If you lack the innovative capacity to develop something originally, attempting to replicate it later will not close the gap. By the time you copy it, the other side has already moved several cycles ahead.
Even if something is stolen or replicated, it doesn’t automatically deliver strategic advantage. In this sense, I believe they lag considerably in innovation.
At the same time, the state’s role is crucial. I cannot imagine a scenario where a Russian state bank or security structure would allow a private company to operate independently with large-scale intelligence data. In Ukraine, private teams have processed millions of data points and delivered actionable outputs directly to units.
That openness and integration between the private sector and operational structures is a key difference. It creates speed and flexibility that are difficult to reproduce in a rigid, centralized system.
Demian Shevko: Can we say that you are, in some sense, pioneers globally in the technological direction you’re developing? Or are there already similar players?
Oleksii Teplukhin: First of all, it would be an exaggeration to say we have no competitors. There are companies with similar models that address comparable tasks. But in terms of the specific concept you described — no, we don’t see direct analogues so far.
At this stage, we believe we have strong prospects at the European and international levels. Much depends on us. If we manage to execute everything as planned — if it proves technologically feasible and we overcome the challenges of scaling — then we could secure a very strong position.
There are many companies in Europe working in related areas. At the same time, there is a growing demand in Europe to replace certain existing platforms with alternatives. This is not just a trend; it is a clear request. Not all countries are comfortable placing sensitive data within U.S.-based infrastructures. That creates an opening.
Many companies are competing to meet that demand. We believe we have certain advantages. Strategically speaking, could we occupy that niche? Potentially.
However, I don’t believe there will ever be a single “operating system of war” that dominates everything. That would be too dangerous and too risky from a security standpoint. The future is more likely to involve multiple interoperable systems rather than one centralized solution controlling the entire battlespace.
Demian Shevko: There is still an argument among some European politicians is that Ukraine is “Not quite Europe,” and some ask what concrete value Ukraine brings to the EU. Could Ukrainian miltech — including your know-how — become a serious argument for European stakeholders deciding on Ukraine’s EU accession? How attractive is Ukrainian miltech to Europe today?
Oleksii Teplukhin: My perspective may be somewhat biased because I mostly operate in circles where questioning whether Ukraine is part of Europe would sound absurd. But speaking practically: this year, at an exhibition in Bonn, I had a queue of generals waiting to speak with me.
There is genuine interest. European military leaders openly state that they are studying Ukraine’s experience. If we talk about Ukrainian miltech as one of our strategic assets, then yes — from my point of view, most understand its value. Poland, the Baltic states, Finland — they absolutely recognize it.
This should not be framed as something we “trade,” but it should be part of our overall offer. Because even if the war ends and Russia weakens — which I believe it will — no one will be able to fully prepare to confront Russia simply by reading our lessons. That experience belongs to us.
The same applies to military technology development. Without access to real, high-intensity battlefield experience, it is extremely difficult to design and validate effective systems. Europe understands that Ukraine currently possesses that experience at scale.
Demian Shevko: And in five years, how do you see your company, G-NEXT? Will it remain a Ukrainian startup, become a European defense-tech player, or evolve into a global technology company?
Oleksii Teplukhin: If we’re speaking about five years ahead — it will be a global technology company.
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