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Charting AI value creation

According to McKinsey, the use of artificial intelligence (AI) will increase the global gross domestic product by 16% by 2030. PwC even expects an increase of 26%. In both scenarios, this means growth in the double-digit trillion-dollar range. However, the question of where the value will be created is far more exciting than the exact percentage.

In their pitch memo, the founders of French startup mistral.ai, which raised €105 million a few weeks ago in the biggest seed round ever for a European company, assume that the main value creation in the future will be in large language models (LLMs) themselves. With that in mind, the company says it is important to build alternatives to LLMs offered by U.S. tech giants.

Especially security and compliance aspects have so far made the adoption of generative AI difficult or impossible for many companies, as it is often unclear how the data is processed and stored. European players such as mistral.ai or AI21 Labs from Israel could position themselves as alternatives to ChatGPT or Google’s Bard, thus creating value for both users and providers.

However, the key will be to distribute the service successfully. Otherwise, a scenario similar to that seen with Slack after the launch of Microsoft Teams could arise: In 2019 (two years after the launch), the tech giant’s service had more daily active users (DAU) than the startup had managed to gain in five years. By the end of 2022, it had more than 10 times as many, with around 270 million DAUs.

At the same time, the value of an LLM is manageable if it is not linked to industry-specific know-how. Because then, it is possible to define the framework for AI applications and create actual value. This should give an advantage to AI companies that have already developed their own applications for specific industries. The use of AI at companies is still often driven by individual employees and is not part of the corporate strategy. An Accenture survey of 1,200 companies confirms this: 63% of companies do not have developed sufficient AI strategies or capacities.

Only 12 percent of the companies surveyed have a sophisticated AI strategy, the vast majority are still experimenting

Source: Accenture Research – The Art of AI Maturity

AI’s significant impact on global GDP is undeniable. As is the fact, that value will not be created solely by LLMs. Moreover, it is unlikely that this future market will be left to a few (large U.S. tech) companies without resistance: Data provider PitchBook predicts that investments in generative AI startups will amount to $42.6 billion in 2023 – up 16 times from the previous year.

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