According to Andrew McAfee, principal research scientist at the Massachusetts Institute of Technology (MIT) Artificial Intelligence is quickly disrupting companies’ economic models, strategy, culture, and even the very nature of how they are structured and run. But to fully benefit from that, it is important that you are the first. And if you are too small to make the investments to be the first, you need to team up.
Based on multiple conversations with corporates of all industries, The Growcery has compiled our favorite collaboration topics:
1. Cybersecurity
For some industries (like finance) this is obvious, but whether you have digital or physical products, every company has an increasing digital presence. Therefore, cybersecurity should be on the strategic agenda for all corporates. However, the investments are large: keeping your online channels and products secure is a continuous struggle. It's a race. And that's where Artificial Intelligence makes the difference. Both the attackers and defenders are using A.I. to detect and resolve vulnaribilities. The stakes are high, as the data or money from customers are on the line. The winner of the race holds the trophy, but not for long. It is an everlasting race, with multiple laps that need to be won. So both sides cannot rest. So how can we make sure that the corporates win and the hackers lose? One giant advantage that the defending side has, is scale. If corporates collaborate in protecting their digital assets, they are well armed in their fight against hackers. So it pays off to collaborate, even with competitors, to keep the hackers in the rear view mirror. However, this also means collaborating with smaller service providers and vendors. The current platformization and interconnectivity between corporates also means more vulnerabilities. At the basis for collaboration, it is essential to have a common minimum understanding of the cyber risks, and the A.I. techniques to mitigate those risks.
2. Digital enablers
Artificial Intelligence cannot exist without data. The quality and quantity of that data is key in training the A.I. However, in Belgium, we are at a disadvantage. Countries like China, the US, India or Russia, have vastly more data to process. Multinational corporates active in those regions have easy access to big pools of data. So if we, in Belgium, want to make the difference, it is important that we are highly organized in our data, and collaborate to maximize the impact of that data. Of course this does not mean that we need to share customer data between corporates all over Belgium, there are lots of pricavy concerns that need to be taken into account. But there are possibilities to use that data, without sharing it, and still be able to train an A.I. As an example, take the voice recognition technology in Dutch (Flemish). Lots of corporates would like to have this technology perfected, for multiple purposes. But alas, Dutch/Flemish is too small to be an interesting market for big voice tech players. And for one corporate to develop the technology themselves is too big of an investment. But even if money wouldn't be an issue: one Belgian corporate does not have enough voice data to train the A.I. technology. Cases like these are important in a small market like Belgium. If we want to stay competitive in A.I., we will need to share some training data!
3. Talent
One could argue that talent is the most important competitive aspect of A.I. And it is (for now). However, we need to increase the general level of the entire country to be competitive. Even if the corporates will continuously fight for the handful of A.I. Graduates, it is still in the common interest to keep increasing that talent pool. Like the adoption of mobile technology before, we need to make sure that the entire population learns how to use A.I., especially in their working environments. This means increasing general awareness through public campaigns, upgrading our schools and upskilling the workforce. Everyone should know the basic function of neural networks, just like everyone knows what fotosynthesis is, even if it is often a very, very rudimentary explanation. Everyone student should learn the basics of programming by the age of 12, and know the basics of neural networks by 18. Every study program at universities should contain an A.I. 101 course, and most of them even beyond that. And every training catalogue at every corporate should include basic A.I. trainings. In a world that will soon be dominated by A.I., at least everyone should know the basics of what is dominating them ;-)
But let's not end on that philosophical note. The key message is: to stay competitive, especially in Belgium, we need to elevate our A.I. expertise to the next level. And we need to collaborate, to make that happen.
Did we miss something? Don't agree with this? Comment, and let's start a discussion!