The revolution of Generative AI

Since its launch in November 2022 by US-based OpenAI, ChatGPT has generated a lot of interest and has immediately experienced revolutionary growth that has triggered a worldwide chain of innovation in artificial intelligence.

When we talk about ChatGPT, however, we are not referring to so-called “traditional” or “analytical” artificial intelligence, but we are referring to Generative Artificial Intelligence (GAI),  an advanced form of artificial intelligence that enables machines to learn from existing data to create new data or content, including audio, code, images, text, simulations, and videos.

That is a new technological frontier with a surprising impact on the economy and the society, that will likely affect most sectors over the longer term.

For example, in the field of information technology generative AI can help teams write code and documentation. Already, automated coders on the market have improved developer productivity by more than 50%, helping to accelerate software development.

Moreover, in relation to product development, generative AI can help companies to rapidly prototype product designs. Life sciences companies, for instance, have already started to explore the use of generative AI to help generate sequences of amino acids and DNA nucleotides to shorten the drug design phase from months to weeks.

In general, the primary benefit of generative AI is its ability to quickly produce high-quality content with minimal human effort required compared to traditional methods such as manual coding or writing scripts from scratch.

This technology can help reduce costs associated with content production. Generative models can also be used for tasks such as natural language processing (NLP), image recognition/generation and robotics/automation applications, which could lead to improved customer experiences across various industries including healthcare and retail sectors.

Not only large enterprises but also SMEs are eager to explore the possibilities that generative AI can offer to accelerate their business growth. Already use cases are emerging that illustrate the potential of generative AI to help small businesses increase efficiency, reduce costs, and improve their marketing and customer services efforts.

In addition, SMEs (such as large enterprises) can harness the power of generative AI to improve cybersecurity resilience.

The economic potential of generative AI

Preliminary estimates of the economic potential impact of generative AI on the world economy are impressive. According to a Goldman Sachs’ report, it could drive a 7% (or almost $7 trillion) increase in global GDP and lift productivity growth by 1.5 percentage points over a 10-year period. McKinsey & Company released similar figures. Having analysed 63 use cases across the global economy, the consultancy’s analysts reported that generative AI has the potential to generate $2.6 trillion to $4.4 trillion in added value across industries. Moreover, generative AI could result in a labour productivity growth of 0.1 to 0.6 % annually through to 2040, depending on the rate of technology adoption and redeployment of worker time to other activities.

The European market of Generative AI

The EU generative AI market is showing rapid growth (though less so compared to worldwide market). According to some estimates, value  in the EU generative AI market is projected to reach $ 8.77 billion in 2023 and it is expected to show an annual growth rate (CAGR 2023-2030) of 24.85%, resulting in a market volume of $41.47billion by 2030.

Among the main Member States, Germany is the largest market for generative AI, covering 22% of the total EU market, followed by France (14%) and Italy (10%). Spain ranks fifth (8%) while Portugal and Greece are at bottom of the ranking , respectively with 2% and 1% of total generative AI EU market.

Taking country population into account, Denmark looks the largest generative AI market at worldwide level, with a market value per 100,000 inhabitant of $ 7.35 million, followed by Finland and Ireland. Instead, Germany – the biggest AI generative market in Europe in absolute terms – ranks in eleventh position with a market value of $2.29 million per 100,000 inhabitant.

Europe shows not bad performance in terms of generative AI startups. It has more than 150 startups that have raised the most capital so far and working on generative AI. The UK is the first country in terms of generative AI startups, with more 50 companies working in the field (36% of total European Generative AI startups), compared to second-place Germany, with 19 startups (13%). Spain and Italy rank far below with 5% and 3% of generative AI startups respectively.

Risks and issues to be addressed

As generative AI is already becoming an increasingly prominent part of everyday business activities and our daily lives, it gives rise to several risks and ethical considerations. For instance, AI-generated content could be used for malicious purposes, such as spreading misinformation or creating deepfakes. It is crucial for developers and platforms to implement ethical guidelines and regulations to mitigate these risks. Other challenges involve security and privacy in terms of protecting user data and preventing identity theft.

Finally, also impact on knowledge work is a considerable issue. However, it is up to us humans to understand how to best use it. If we see generative AI tools as a substitute for workers, we indeed risk high unemployment or wage compression as salaries would then have to compete with machine costs. If we recognise it as a complement that can enhance overall work performance, we can lay the foundation for a manageable transition, where different tasks than before are performed, but in most cases to the advantage of both workers and companies.

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