In our current reality of rapid technological disruptions, it’s critical to understand how and where we can act effectively. The technologies we handle daily are becoming more immediate, their effects more radical, and their consequences more unpredictable. This makes it essential to consider certain aspects when making strategic decisions to avoid falling into the gray zone between pioneers and the backward-looking or naive. The starting point is to use tools to face changes, hypothesize scenarios, and anticipate consequences.
Internationally, technological bipolarity between the United States and China has generated an overabundance of companies with direct influence on all levels and aspects of our lives. While the US maintains its global economic leadership, China is advancing rapidly with developments like Deepseek and other proprietary AI solutions. This competition has allowed new technological innovations, such as AI or quantum computing as a service, to emerge. These innovations are less than a decade old but have generated a seismic effect with chain reactions transforming industries and relativizing the importance of global economies.
Looking at last year’s major technological disruption, generative artificial intelligence has infiltrated all our daily tasks. OpenAI with the GPT-2 model from 2019 held the record as the first digital platform to reach 100 million users in two months and currently has 300 million weekly active users. Similarly, in China, Deepseek has experienced exponential growth, positioning itself as the main Asian competitor and attracting millions of users overnight. In perspective, this represents an adoption rate 2700% faster than Facebook in reaching 100 million users, or 887.5% faster than Instagram in reaching 10 million users per day. Since these percentages are unfathomable to our minds, we can compare the speeds of walking versus driving a Formula 1 car. And this adoption speed is coupled with funding initiatives like the Stargate project, where the United States will invest $500 billion over four years.
This massive usage has generated multiple changes in five aspects of our society. The first, automation and productivity where 75% of global workers claim to use these solutions in their daily tasks, according to LinkedIn and Microsoft’s 2024 Labor Trends Index. The second, job creation and transformation; this innovation redefines roles, supplants some and pressures the demand for others for certain new needs that have emerged in companies. The third, the sectoral impact of tools where certain industries have been more affected than others. The fourth aspect concerns changes in skills and competencies of employees who have to adapt to the new needs of the labor market. And the fifth, the perception and adoption of these tools where there exists great uncertainty among workers because their jobs may eventually run the risk of disappearing.
The Collingridge Dilemma
This is the game on which we play as professionals, companies, and countries. And this is where it’s imperative to stop and reflect to chart the best strategy for personal, professional, and institutional success. Not all of us have the same tools or resources to compete on equal terms, but David Collingridge published in 1980 the book “The Social Control of Technology,” a fundamental concept for evaluating the impact of technology. The Collingridge dilemma is essential to understand when regulating technology and innovation. It poses a timing problem: On one hand, if we regulate a technology too early, when it’s still developing and hasn’t reached mass adoption, we cannot foresee all the negative consequences of such regulation. This could lead to ineffective or even unnecessary regulation. On the other hand, if we wait too long to regulate it, the technology will already be widespread and difficult to modify without significant costs, political conflicts, or industry resistance.
This dilemma makes particular sense today with regulatory proposals such as the EU’s Artificial Intelligence Act, which aims to balance the supposed challenges of AI systems according to their risk level: unacceptable, high, limited, and minimal. Here, the EU seeks to establish safeguards for the reliable and responsible use of AI to ensure transparency, but there are three major insurmountable obstacles to this seemingly laudable mission:
Leading companies in these technologies are private and foreign.
The strategic advantage of the United States and China can establish local regulations for their companies to advance without restrictions to the detriment of European ones, as demonstrated by Chinese government support for Deepseek.
The power of Big Tech lies in offering different services by regions, relegating Europe to a disadvantaged position.
We can state with certainty that these technologies are very incipient, but their great penetration makes them more difficult to limit through regulation. Even thinking that the winning way is proprietary technological development, such as the tool recently launched by the Spanish Government, ALIA. This open-source linguistic tool represents an effort to develop AI in Spanish and promote digital sovereignty, but its practical relevance and capabilities lag far behind those of other market solutions.
In this scenario, where geopolitics has also gained significant weight, EU companies and professionals start with a clear disadvantage. It’s important to define a winning strategy as soon as possible, a winning strategy to promote the use of the most relevant, consolidated, and functional technologies. Only then can innovations originating in Europe exist to compete with other regions.