AI’s Role In The Four Stages Of Technological Business Development

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Alexander Konovalov is the founder and CEO at vidby, a Swiss startup offering AI-powered video translation and dubbing across 70 languages.

The Internet of Things, blockchain, machine learning and smart robotics—these new technologies are transforming our lives, businesses and the global economy. However, among this sea of innovations, one sector particularly stands out: artificial intelligence (AI). The global AI market was estimated at $119.78 billion in 2022 and is expected to reach $1,591.03 billion by 2030, with a compound annual growth rate of 38.1% (from 2022 to 2030).

AI is becoming a key driver in the technology industry and reshaping the market landscape. With a multitude of new projects emerging, competition is intensifying. This presents challenges as well as opportunities for those who focus on genuine product improvement. These companies will maintain sustainable leadership in the final stage of technological business development, which can generally be categorized into four stages. After that, a revolutionary technological turn can occur, bringing us back to where we started.

Stage 1: Nobody is involved.

In the first stage of technological business development, there is little interest from investors or competitors. This is a time when the idea or specific technology has not yet gained widespread adoption and recognition. However, it is at this stage that identifying unresolved problems or needs can be a key factor for success.

At one point, no one believed in the era of personal computers. And what happened? I am currently writing this material on my PC, and Apple and Microsoft are among the most valuable and successful companies, with a combined market capitalization of over $5 trillion.

Stage 2: Only a few are involved.

By closely observing market needs and identifying gaps in existing solutions, technology pioneers can innovate to effectively address these problems. However, being a pioneer is not always about “picking the low-hanging fruit.” In the early stages of technology emergence, investor interest is usually limited. Therefore, reliance on one’s own resources and time becomes necessary. Sometimes, this can be for a very long time.

For example, discussions about AI began actively in 1956 during the Dartmouth Summer Research Project on Artificial Intelligence. One subsequent important milestone was the development of the artificial neural network architecture (the perceptron), which triggered the AI boom. However, in the 1980s, the AI industry entered a period of stagnation. This was partially due to many AI projects failing to deliver on their promises.

The modern era of AI research emerged in the 1990s when technology research and globalization started gaining momentum again. Big data became a driving force behind many successful AI achievements in the 2000s.

As an example from our own experience, we set a goal to address a specific market need for communication tools. Despite the global financial crisis of 2008, the translation services market continued to grow due to the increasing globalization of markets, travel and international contacts. The demand for technological solutions in the translation industry also continued to rise.

In 2013, our team offered the market an approach to communication that combined real-time translation of voice and video calls with the use of AI. With this service, users could easily communicate while preserving language diversity. Later, in 2015, a popular video conferencing platform introduced a prototype with the full functionality of our approach. Their involvement confirmed the validity of our path.

Stage 3. Everyone is involved.

During the third stage of technological business development, a boom occurs when a specific business or industry gains general interest and popularity. This can be the result of significant successes by a few companies that have gained substantial fame and recognition in the market, or it can be due to an increased awareness by the public of the importance of a particular technology.

General interest and popularity can lead to the emergence of many new players in the market who are trying to gain their share of success in that industry.

After the announcement that Microsoft is considering investing $10 billion in OpenAI, the developer of ChatGPT, there has been a race between Big Tech companies and startups to rapidly develop commercial programs related to this technology. According to Crunchbase data, as of today, there have been over 23,000 individual funding rounds for over 9,500 AI startups. The total funding volume has exceeded $150 billion.

Returning to my company’s example, starting as an Android app pioneer that translated video calls, we have evolved into a technological project for automated video translation and dubbing based on AI in 70 languages and have become one of the top 6 players holding over 60% market share.

The main strategy that helped us maintain our market position is continuous investment in development, constant product improvement and providing high-quality customer service. I believe that this is the only way to preserve a leadership position and ensure long-term success.

It is expected that the global market for automated dubbing services will continue to grow and reach $189.80 million by 2030, with a projected CAGR of 5.69% for the period of 2022 to 2030. Almost every day, we witness the emergence of new projects for automated video translation, while just a year or two ago, there were only a few in the market.

Stage 4. Only the leaders remain.

The fourth stage of technological business development involves the formation of sustainable leadership. Key success factors at this stage include reliability and product quality, continuous innovation, the ability to anticipate changes in the industry and a quick response to them.

For example, in the battle for leadership, certain cell phone companies have been unable to withstand the competition and lost to Apple in ensuring long-term success. The same story can happen with AI projects. Venture investors predict that 85% of AI startups will go out of business within three years. It’s possible that this 85% may face a collapse similar to what happened to technological startups during the dot-com bubble.

Conclusion

The future belongs to those who can effectively harness the power of technologies, including AI, to solve real problems and create new opportunities. Each stage of technological business development presents new challenges. The key strategy is to continue creating cool products and staying at the forefront of innovation.


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