5 ways Europe can become a global leader in AI

Artificial intelligence (AI) is continuing to develop at startling speed. The technology is expected to shape global competitiveness and productivity over the next several decades, prompting billions to be poured into AI R&D every year. 

For early adopters, there are tangible economic and strategic advantages on offer. According to McKinsey, AI has the potential to contribute around $13 trillion to the global economy by 2030, with 70% of companies expected to have adopted at least one type of AI technology in the same timeframe.

With this in mind, it’s no wonder why countries all around the world are fighting to lead the AI race. This new AI economy has some unique traits and China and North America are currently in the drivers’ seats. Over the weekend, ex-Google boss Eric Schmit warned that China was gaining an advantage over North America, both in a military sense and economic power. NY Times: https://www.nytimes.com/2020/02/27/opinion/eric-schmidt-ai-china.html

So where does that leave Europe? In most commentator’s eyes, firmly in third place, and that’s before you split out the UK element from the rest of the EU.

The need for Europe to keep pace is clear, as the economic benefit – potentially adding €2.7 trillion to Europe’s combined economic output by 2030.

The good news is that Europe doesn’t have to go head-to-head with North America and China. It must play to its strengths to outperform its high-powered competition by focusing on four key areas”

1. From academia to business

Europe leads the way in published AI research but historically lags behind North America and China in turning this research into a thriving tech economy.

If it wants to catch up with North America and China, Europe must protect its research base and keep investing in academic-business collaboration through vehicles like the European Commission’s Horizon 2020 research & innovation programme and Innovate UK’s Knowledge Transfer Partnership. This is an area that we’ve benefited greatly from here at Filament, thanks to our applied AI research partnerships with the universities of Essex and Warwick. While cultural differences can pose challenges, closing the gap between these two pillars will be vital to driving innovation and realising tangible benefits from AI.

Linked to this is the need to create a Venture Capital environment that enables continued investment through R&D cycles to support high-growth AI businesses. The European VC scene has progressed significantly in recent years, with record investment and a greater willingness to make the big bets. As testament, see recent European success stories like Spotify and Adyen passing $50bn in market cap.

2. Making the most of data

Europe has always had a rich source of data – including societal, consumer, instrumented data and much more – that is more heterogeneous than any other region around the world. 

While the sovereignty of data across Europe represents a challenge to overcome, it is clearly an opportunity if those silos can be broken down. The great work of organisations such as the EU Open Data portal, which provides access to open data published by EU institutions and bodies, means that continents-wide datasets can be accessed much more freely.

This work was boosted earlier this year when the European Commission announced a €2 billion investment in the creation of an EU Cloud Alliance to support the development of AI technologies. As the complexity of AI technology continues to evolve, enabling efficient data sharing and collaboration across Europe will be vital to monetising AI solutions in the future.

3. Innovation through regulation

One area that Europe is legitimately known for global leadership is in the area of regulation. In its new tactic to pursue the global tech giants with anti-competition measures, it is showing that innovation in the field of regulation can be a differentiator too. While not cutting off its nose to spite its face, the objective should be to open up competition. For example where the tech giants own a marketplace role (like Apply in digital apps or Amazon in retail), this new policy direction seeks to rightly level the playing field. The outcome, in the european market, should encourage more money to flow into the smaller challenger tech, and since it follows the money, for innovation to blossom outside the tech monopolies.

Here’s a good debate on the topic:

https://hbr.org/podcast/2020/02/geopolitics-technology-and-risk

4. Tapping into talent

Europe also has a fantastic and diverse talent pool. This serves the AI economy in two ways: Firstly, to provide the domain expertise to train AI systems. Secondly, to provide the technical talent (most notably data science, software engineering and business execution skills) to turn research into live solutions.

Retaining and growing access to this talent, as well as developing the AI leaders of the future, will be a key component of Europe’s ongoing success. And there are some clear steps businesses and governments can take. For example, training and upskilling ‘near AI’ talent – i.e. those with similar or related skillsets – could double the size of the AI workforce across the EU. Also, with AI being such a male-dominated industry, rolling out diversity initiatives can tap into wider pools of talent while addressing gender and diversity imbalances within the industry.

The top European talent is constantly being chased by the major tech players, especially those in North America so providing opportunities for these workers to grow and develop is vital to their long-term retention.

5. Leveraging Europe’s service excellence

As a distinctive trait of the AI value chain, AI and machine learning-based systems need to be tuned and optimised to their specific operating environments. AI algorithms are rarely one-size-fits-all. A simple analogy for considering real-life deployment of AI is like a restaurant experience. The tools and base algorithms are the ingredients and kitchen equipment, but it is the skill and flair of the chef (and the many sous-chefs) to deliver a successful experience.

This means that the AI value chain requires a strong services layer on top of the plethora of products and tools, and consequently a greater degree of high-skilled professional services than traditional linear-programmed SaaS software. This was recognised in an Andreessen Horowitz blog published earlier this year, which suggested that “AI is creating an essentially new type of business” where software and services are deeply integrated.

The advantage for Europe is that it has a rich pedigree of services businesses and can provide this product-service duality to effectively implement AI at scale. This strong services culture, combined with a preference of investing in companies that make a profit instead of investing to acquire scale like in North America and China, puts Europe in a strong position to capitalise on the future of AI.

Ultimately, the race is well and truly on. The global powerhouses that are North America and China might have plenty of muscle behind them but, by playing to its unique strengths, Europe has an opportunity to catch up and be a global leader in the AI race.