New AI and Data Strategies from the European Union: Aiming for Global Leadership

On February 19, 2020, the European Union published a number of papers as part of its broader digital strategy on data and Artificial Intelligence (AI). These two endeavors are at the core of the European Union’s new agenda, and the papers set out how the Union can become a leader on both technology fronts. First, with regards to the Data objective, the European Union aims to set up a single market in which data can flow freely and securely across borders and sectors and between businesses and consumers. For the AI objective, the goal is to become a center of excellence and to build trust in the technology.

Both strategies mean to create accountable bodies, appropriate policy and regulation (to ensure security, privacy, and transparency and encourage fair competition, but also to lift barriers against data-sharing initiatives), and investment in innovation hubs, funds and promoting the further development of varied supporting technologies (such as cloud services and robotics).

The European Union is riding on the wave of the global acceptance of its data security and privacy efforts—most notably, the General Data Protection Regulation (GDPR). Its stringent data protection requirements mean that many technology giants have had to comply in order to continue serving the 500+ million users based in the European Union.  As such, it has become their global standard (in large part because it is easier to do so than it is to create separate business models for users inside and outside of the European Union). This is significant in that most of those technology companies are not E.U.-based, making the European Union’s reach in this matter rather impressive. 

The European Union is trying to repeat this gambit with its data and AI strategies, taking advantage of the current dissonance in the U.S. government that is hampering tech innovation and China’s current market troubles (in part due to trade wars with the United States) that have left a void for the European Union to fill. The strategies complement each other well, as data is the key ingredient for Machine Learning (ML) algorithms. By ensuring greater access to, and governance of, data within the region, the European Union hopes to accelerate AI development and adoption. The key is to do so in a way that minimizes risk, especially in light of the high-profile debates around the threats of AI. The European Union recognizes that AI is a relatively nascent technology and, as such, requires concerted efforts to build trust for safe use, which in turn leads to acceptance and adoption. This is a departure from the European Union’s data comfort zone, which it has been working on since at least the 1995 Data Protection Directive, but one which the Union is aggressively pursuing with all confidence.

Consequently, the European Union is aiming to create a secure, but open and dynamic data economy that can provide a solid foundation for the development of trusted AI. It is a hefty endeavor, and one that can play out well for the European Union if it doesn’t fall into the trap of overregulation or overly protectionist policies that risk alienating the very technology companies that are at the heart of data and AI creation.

For Internet of Things (IoT) market players, these strategies could be a boon in terms of market expansion. The exponential growth of connected devices is fueling data generation and consumption. For ML and AI technologies, there is substantial opportunity to leverage the data and not only expand existing business models with adjacent applications and service offerings, but also create new ones. The key for IoT industry stakeholders will be to ensure they comply with existing E.U. regulation on data protection and focus on making product development decisions in line with both the data and the AI strategies. While this may include requirements seemingly at odds with some current private sector processes (especially regarding IoT data protection, transparency, and the guarantee of user rights, as well as providing them the tools and skills to stay in control of their data), the potential benefits—i.e., the opening up of new markets and the availability of ever richer data sets to drive new business and revenues—will far outweigh any of these limitations.