AI-based systems have long ceased to be science fiction and have been solving real-world problems for years — reducing call center costs, diagnosing medical conditions, and even assisting in research aboard the International Space Station. Investor interest in the technology is also growing: in Russia, by the end of 2024, investments exceeded RUR 300 bln ($3.7 mln), marking a 30% increase. How long will this AI market boom last? What approaches help identify future unicorns among emerging projects? And most importantly, what challenges does the rapid development of artificial intelligence pose? These and other questions were discussed at the Investing in AI Projects conference co-organized by the Russian Chamber of Commerce and Industry’s Council for Financial, Industrial, and Investment Policy and the Investment Networking Club.
More than just a technology
Regulation remains the key challenge surrounding AI. While there are no unified, clear legal frameworks in the industry yet, they will inevitably emerge as they are essential for AI project investments. Especially since artificial intelligence is already more than just another new technology.
“It is no longer merely a technological tool but a core component of global economic and security strategies. At the same time, AI has become a competitive battleground involving major development hubs, including Russia, China, the United States, and the EU,” explains Artem Genkin, Professor, Doctor of Economics, and CEO of the Consulting and Analytical Union.
Thus, there is increasing concern about the potential misuse of artificial intelligence to create pathogens or toxins. Equally troubling, in the absence of regulation, is the use of AI in autonomous or semi-autonomous systems, particularly those deployed in military operations.
“The challenges of regulating intellectual property generated by artificial intelligence, along with issues surrounding the authenticity of AI-created content, are supranational in scope,” Artem Genkin explained.
“Artificial intelligence can produce replicas of real-world objects that people may mistake for genuine. Without proper regulation, we’ll be forced to rely even more on AI itself to distinguish between what is real and what is fake,” says Vladimir Gamza, Chairman of the Russian Chamber of Commerce and Industry’s Council for Financial, Industrial and Investment Policy.
“AI-driven projects have already brought to light a range of previously less prominent issues, including ethical concerns, which now have a direct impact on investment in the industry,” agrees Sergei Orekhanov, an expert with the Russian Chamber of Commerce and Industry’s Council for Financial, Industrial and Investment Policy, and founder of an investment-focused AI studio.
Regulate or ban
Today, most countries are only beginning to develop legal frameworks for artificial intelligence, and a unified global regulatory approach has yet to emerge.
“So far, 39 countries have enacted at least one law that includes the concept of artificial intelligence. Russia leads globally in this area, with the concept featured in seven separate laws,” Artem Genkin explains.
At the same time, countries take markedly different – and often opposing – approaches to AI regulation. In Europe, the focus is on consumer protection and safety, with AI systems categorized by risk level, from “unacceptable” (such as social scoring systems) to “minimal,” which require no regulation at all (like email spam filters).
The U.S., by contrast, follows a more innovation-driven model, embracing the principle of “let all innovations develop.” Regulation is largely decentralized, with around 46 federal agencies currently involved in overseeing various aspects of AI.
“I believe Russia needs a unified and consistent legal framework – nationwide legislation with lasting applicability. In my view, it should place strong emphasis on protecting consumer rights, rather than allowing unchecked innovation,” Artem Genkin says.
The new superhype
Despite the absence of clear regulatory frameworks, investor interest in artificial intelligence continues to grow, and is expected to increase even further in the near future. This trend is creating new challenges for the broader market, as projects outside the AI sphere are finding it increasingly difficult to secure funding.
“There are two key innovation priorities looking ahead: artificial intelligence and cybersecurity,” says Lyubov Simonova-Yemelyanova, Director of Projects in the Strategic Initiatives Division at Rostelecom.
“When a company seeks to raise capital on the public market, any mention of artificial intelligence in its solutions is emphasized repeatedly, it becomes a central part of the investment pitch. AI has become a super-hyped area that businesses are eager to spotlight,” adds Leonid Pavlikov, Managing Director for Equity Capital Markets at FG Finam.
A unique window of opportunity
A major incentive that drives investment in the AI niche is a real chance to build a supergiant AI-based company.
“Opportunities like this arise only once in each major technological cycle. It’s nearly impossible to create another Google or Tesla today; those journeys should have started a decade ago – while the door is still open to build an AI global company capable of drastically transforming the world,” notes Yevgeny Kuznetsov, General Director of Orbita Capital Partners.
However, this also presents a new set of challenges, such as increasing corporate interest in disruptive AI startups. According to Leonid Pavlikov, companies with functioning AI solutions are likely to be acquired by major ecosystems, including through pre-IPO or over-the-counter (OTC) deals. These acquisitions help tech giants bolster their platforms with critical expertise, or replicate solutions themselves.
“We are unlikely to see AI companies evolve into large independent businesses in Russia,” the expert emphasizes.
The road to corporate integration
The Russian market already has an increasing number of AI-driven projects, including the so-called horizontal AI platforms that can be applied across various industries, as well as vertical AI solutions designed for solving specific tasks, according to Kirill Tishin, partner and co-founder of KAMA FLOW. However, it is the infrastructure-level AI solutions that hold the most interest for investors, although it is not always easy for them to be scaled within large corporations.
What are major companies actually willing to pay for? At the very least, Time to Market (T2M) and a competent team, says Dmitry Kalayev, a partner at FRII Invest venture fund.
Still, even then, major companies remain hesitant about purchasing AI-based solutions, let alone finished projects, always asking a question as to who else has bought them.
“We observe a high level of mistrust within large companies,” notes Anton Pronin, managing partner at Malina Ventures venture fund.
Additionally, there is also a talent risk: project founders can be recruited into large corporations to develop their ideas within a major company.
Thinking like a futurist
With AI evolving at an extraordinary pace, it is essential to identify promising teams and projects as early as at the research stage in order to stay ahead. However, this approach brings its own challenges.
“In Russia, we’re not seeing a steady stream of companies that transform scientific research into actual technological products, let alone commercial businesses,” clarifies Grigory Leshchenko, Huawei’s Chief Investment Officer for Russia and Eastern Europe.
Certain corporations are making attempts to bridge this gap by utilizing AI while focusing internally. For instance, Rosatom has established a dedicated entity, Rosatom Science, which employs some 12,000 people to drive innovation from within.
“We all need to become futurists – those who map out societal trajectories for the next 100 years rather than predict future business developments,” Lyubov Simonova says. “There are roughly 400 possible future scenarios. We must consider which of them are likely to materialize in the next 30-40 years.”
Efforts to recognize global user demand are equally important. So far, many Russian AI startups mostly follow a technology push model – that is, developing solutions based on popular technology, notes Yevgeny Kuznetsov. Focus should be shifted toward solving issues that affect billions of people rather then chasing technology trends.