Kromann Reumert is a partner of Thinkers50 European Business Forum, which brings together the world's most sought-after business thinkers to a two-day conference. As part of the conference some of the greatest business thinkers have written essays called "Letters to the CEO" containing recommendations to the CEOs around the world based on the latest trends in the business world.
Perspective on Enrique Dans' letter to the CEO
In his letter to the CEO, Enrique Dans notes that the ability to comprehend and absorb the new idea of computing as exemplified by machine learning as an alternative to pure automation, is a crucial and ultimate game changer for the survival of any business. Enrique Dans urges businesses to make an effort to understand the changes that have taken place in computing as this is undoubtedly the most important decision for a CEO. This is a clear-sighted statement which we at Kromann Reumert endorse. However, it instinctively gives rise to the complex question - how should businesses then act in this new "battle for survival"?
Comprehension and absorption of a new mindset on computing
There is no clear-cut answer to the above question as it depends on a number of uncertain elements. This is due to the simple fact that new technologies within e.g. machine learning are in their early stages, making it hard to predict their practical development, significance and potential in specific industries. In addition, machine learning gives rise to new legal challenges in terms of security, privacy and IT services which are also 'terra incognita' and will require new IT management practices.
Even though we have only seen a fraction of the machine learning potential, we believe that all businesses – across industries – can benefit from preparing and optimising their organisation with the purpose of implementing machine learning at the time which is right to them. This point of view was also expressed in our Insight on robotics earlier this year (see our Insight Enter the robots – are you prepared? in which we suggested a process with practical and operative steps towards proper implementation of AI in the business.
The art of proper equipment
We suggest that businesses should, as a minimum, take the below measures which may serve as general indicators in an area characterised by great dynamics and uncertainty.
- Identify your business processes and tasks in order to clarify which tasks (in partial) may easily be automated
- Get your business fully digitised – prepare your business knowledge for use of AI tools.
- Be curious and pay special attention to new computing technologies which may offer functions that can be applied directly by your business.
- Implement new tools, redefine existing jobs and tasks, and restructure your business organisation.
- Clarify which regulatory requirements (e.g. data protection) your business is (and will be) subject to and whether you are already in compliance at the time of implementation.
In summary, one of the central messages is that the above approach to new technologies should be adopted by the management in an accommodating and positive manner. A mindset based on curiosity to identify exciting business opportunities rather than fear of risky challenges is decisive. Taking such an active approach will spread to the rest of the organisation, instinctively diminish any latent resistance to change, and prepare the ground for the management's next job: to adapt and adjust the organisational structure.
As a final observation, Enrique Dans predicts that the radical change within computing will unfold within the next five years. Even though such time frame is subject to uncertainty, we are sure of one thing: It is better to embrace the unknown change and create the best possible basis for its integration rather than closing one's eyes to the inevitable.
Torben Waage, partner, Kromann Reumert
In the space of a few years, computers and computing in general, has changed dramatically, a change not yet understood by most people in business. Changing the way we understand technology, and being able to understand what technology can do for our businesses is a more pressing need with each day that passes. For many years, we saw computers simply as another form of automation. We increasingly use them to carry out any repetitive, tedious, or demanding tasks. This is how computers entered corporate environments, taking over routine activities such as calculation, payroll, accounting, etc., as well as those areas where there was a legal requirement for safeguarding information.
Computers were machines that could do the same things as people, but faster, cheaper and with fewer errors. This idea of computing as automation has been a constant in our approach to investing in technology since businesses first started using computers. Some time ago this approach began to change radically. When we see on the news that a computer has beaten Garry Kasparov at chess, won Jeopardy with scores way above those of previous contestants, or has annihilated the best Go players in the world, it’s clear that we’re not talking about the same computing we have known to date: to perform these kinds of feats more is needed than a faster, bigger computer.
The new frontier is now machine learning, and it will bring about a bigger change to the world than the internet has. This is the kind of change that will decide which companies survive and which disappear. It will change what we mean by work, transforming our societies, and all within the next five years.
This means that right now, if a company wants to have any kind of competitive advantage it’s going to have to get hold of the data needed to feed machine learning algorithms that are better, more efficient and more competitive than its competitors. It’s as simple as that.
For a computer to beat Lee Sedol or Fan Hui, the two best Go players in the world, it has to do more than calculate very quickly. To achieve this, Google not only had to get its hands on the moves made in every game of Go on record and make sure that its machine, AlphaGo, was infinitely better at remembering what it learned, it also had to apply and combine techniques of deep learning and reinforcement learning: pitting the machine against itself, inventing moves that had not been played by a human player, as well as deriving new moves from these, which were later fed back into the system. And so on and so on. The chance of a human making some of the moves played by AlphaGo, which have been praised for their elegance and beauty, have been calculated as one in ten thousand, and described as so complex that no human could understand, let alone anticipate them. This is the same process that occurs when every self-driving vehicle on the road automatically contributes to the learning experience of all the self-driving vehicles circulating in the world owned by a particular company. How they are defined and parameterized radically changes the competitive advantages.
That said, the mindset required is not necessarily about winning, but instead improving levels of cooperation between humans and machines and using this to try to solve the many pressing problems we face.
Soon we will have autonomous artificial intelligence able to take business decisions by studying everything that is going on around them in a much more comprehensive, thorough and rigorous than any team. Other will set the European Central Bank’s interest rates, decide tax levels, and calculate pension increases. We are entering the most radical change we have experienced in the history of mankind.
Catching this wave is absolutely crucial to our survival: it’s the ultimate game changer. Understanding the changes that have taken place in computing as soon as possible and preparing for the bigger change that is coming is absolutely crucial for our company and undoubtedly the most important decision of your life as a director.
Thanking you for your time and attention.