The venture capital market is undergoing a fundamental transformation. Artificial intelligence is no longer just a buzzword — it is now the main driver determining where billions of dollars will flow. At the recent AI FUTURE STAGE conference, an in-depth discussion took place on how neural networks are changing approaches to project financing and valuation.
The discussion featured leading experts from the technology and venture capital sectors. Key speakers included Ilya Cheremkin, Head of Ventures Synergy; Svyatoslav Safonov, Analyst at Jets.Capital; Nikita Razhev, Head of the Yandex Cloud Startup Program; Dmitry Reidman, Managing Director of the Global Markets Department at Rostelecom; and Martin Kohlhauser, General Partner at ChuckaVC.
Practical Value of AI: From Hypotheses to Real Cases
The main focus of the discussion shifted from abstract forecasts to specific business metrics. Experts analyzed how large corporations and venture capital funds currently assess the effectiveness of implementing AI solutions. The key question on investors' minds: does the technology actually generate real money?
A whole range of practical aspects was covered, from startup selection criteria to methods for calculating economic impact. Conference participants elaborated on how to properly calculate return on investment, considering both development costs and potential revenue from business process automation.
Global vs. Local Markets: Where to Find Gold?
A separate segment of the discussion was dedicated to comparing investment approaches in Russia and abroad. The speakers concluded that there is no universal recipe. For some investors, speed to profitability is paramount; for others, growth potential; and for yet others, the technological uniqueness of the solution.
The key takeaway I derived from this discussion is: the AI investment market is becoming more mature and demanding. A mere "hype" idea is no longer sufficient. Investors want to see clear metrics, pilot projects, and real-world implementation cases. This is a positive signal for the entire industry, as it filters out empty promises and keeps only truly strong projects afloat.
Common Mistakes and Professional Advice
The experts did not shy away from the "pitfalls" that startups most often encounter. Typical presentation miscalculations, errors in implementing AI solutions, and shortcomings in scaling strategies were listed. The main piece of advice that emerged was: start small — with a pilot project, test the hypothesis on limited data, and only then scale up.
The full recording of the discussion can be found in the new video. The material will be especially useful for entrepreneurs and managers who want not just to "be on trend," but to actually adapt their businesses to rapidly changing market conditions.
My professional opinion: We are at a point where AI is ceasing to be a separate sector and is becoming the infrastructure for all other industries. Investing in this technology is not a bet on a single tool, but a bet on the future of the entire economy. Those who understand this today will be one step ahead tomorrow.