“How will we win tomorrow if no-one knows that we build world-class products that we are able to distribute fast to the market by making it easy for the current workforce to adopt them right away?”
The only logical way for Denmark to not only compete but also to win the AI race is to make sure the AI products we market can be adopted already today by the current workforce in the companies.
That’s the opinion of the Founder and CEO of the Danish AI-tech startup Certainly, Henrik Fabrin.
Since change in any industry happens faster, the ever shortage of programmers, the fast-growing cloud sector and Software-as-a-Service being the primary way of selling B2B software, most companies and organizations choose to buy pre-made AI-solutions, as opposed to developing them from scratch.
Companies don’t have the desire or human- or capital resources to design, develop and maintain their proprietary solutions to how they run their business, so they turn to the internet and try to find suitable products there.
At the same time, the decision-making process of what products to adopt have moved from C-level to people working with the products to solve particular problems.
That could be customer service or e-commerce teams.
Denmark’s AI race – AI to adopt right away
Another factor is time. There are 1.7 million small and medium-sized businesses in the EU with between 10-249 employees, 44,000 with 250+ employees and thousands of public organizations and municipalities.
There is an estimated shortage of 20,000 to 80,000 people with deep analytical skills by 2030 in Denmark alone.
This shortage is similar in most other European countries.
At the same time, you have nations like the US and China (and nation-like companies like Facebook, Google, Amazon) putting more public and private money into developing and commercializing AI products in a day than what we have set aside for the next five years.
The only logical way for us to not only compete – but also win the AI race – is to make sure the products we market can be adopted today by the current workforce in the companies.
In this case, the market of approximately 1.8 million EU based small, medium and larger companies and a large number of organizations in the public sector.
How not to win the AI race
If you live in that reality, you will also realize that this changes how you – as a creator of products that companies use to improve how they run their business – want to think about how you design and make them available to the market.
We can build the best products in the world, but if no-one knows about them and they are not quickly and fast distributed in the market and adopted by the current workforce in companies of today how will we win tomorrow? We. Will. Not.
AI for everyone
We will do that by ensuring the products that we create and sell are easy to adopt now so that we have the upper hand.
The upper hand being, it is much easier for a person working at a company to grow the usage of the current product she is using than to find a replacement product.
It is much easier for a company to keep an existing customer than to find the next one.
The above given, the companies out there need products they can subscribe to and enable their current workforce to use them immediately to solve their problems of today and to trust they can solve the problems of tomorrow.
At the same time, they have to be able to adjust the product over time to tailor it to their particular needs.
That is, providing products that may include advanced AI/Machine Learning and other modern tricks but can be understood, purchased, launched, maintained and moulded by the hands of the line of business people to keep improving how they run their business.
Not only by developers or data scientists, but the people in customer service, sales, operations, etc.
Only tools change – not jobs
This will, over time, require a more in-depth technical understanding of how AI works or how APIs work, but at an incremental pace.
Upgrading of the current workforce’s skills should focus on deepening their general understanding of new technology such as AI but without having to re-educate them to becoming data scientists or data engineers.
In other words: Your job function will stay, but the tools you use will change. And now it is AI-based tools.
If we want to win, then we have to understand this battlefield. We will not win the race because of ethics in AI or by ensuring more data scientists in the companies.
We will earn if we make sure the product not only solves the companies’ problems but is also quickly adopted by the current workforce in the companies and organizations.
Hot topics like ethics in AI may be part of the unique selling points, but the easy-of-adoption will win the deal.
Article written by Henrik Fabrin