Entrepreneurs must warm up to AI — or risk their own ‘AlphaGo loss’

The evolution of AI continues apace. Deep learning has established its place in the world of tech but its next iteration is Evolutionary AI, which, as well as driving AlphaGo to victory over world Go champion Lee Sedol, is now available for commercial solutions.

Following his defeat, Sedol announced his retirement, concluding that the AI technology driving his virtual opponent was now of such a standard that he could no longer beat it.

This is a profound moment for a few reasons. An AI-based system has mastered a game that human players have grappled with for decades. This means technology has reached the point where it can learn new strategies from its experiences rather than being trained by people. And this capability is now being used to find optimal strategies for all kinds of decisions in every industry — from insurance underwriting to bank reconciliation, from supply chain optimization to HR employee retention.

Most people think of AI as being very good at narrow tasks like recognizing images and voice, and that is true with deep learning, but it is capable of far more when you use evolutionary techniques — and of helping people perform their jobs better.

[Read: Your startup’s culture should revolve around quality-focused product development]

Put simply, Evolutionary AI can help decision makers to find the best strategies and find the optimum solutions. No longer relying on human input, it uses AI to train AI — it doesn’t just do what it’s told, it can come up with every possible scenario or variation of possibility to solve challenges.

Human beings only work with a fraction of the information that matters and cannot explore every possible decision to find the ones that maximize multiple goals. To cope with our limitations, humans have learned to filter out a lot of data and possibilities when making decisions. As a result, a good strategy may be developed, often very good, but not the best possible one. Evolutionary AI can and does handle all available data and does not have to be selective, allowing it to help people find the best strategies to optimize decisions.

All workers, but especially key decision makers, will need to become “AI-aware.” Evolutionary AI means there are now AI systems in business which can find better answers to day-to-day decisions than a human can. The way we currently crawl through data, produce reports and guess root causes — and it is guessing, based on experience — to make decisions will come to be seen as being as outmoded as faxes and adding machines.

To be AI-aware, leaders need to:

• Embrace data as the source of wisdom and value for their business. Not all data matters, but the data that does matter currently may not be harnessed as it should. Leaders need their associates to see data for its potential and need staff who can bring in and understand new types of data that will matter, be that social data, images, IoT data, text, voice, local data, or any other kind.
• Ask better questions and expect more. Instead of asking for another report or another spreadsheet from their team, leaders should keep asking “Why?” until they understand the root causes, or until they find out that the team in fact lacks the data or AI tools to find the root causes. Leaders will find that in far too many cases they are operating on anecdotal experience or data with correlation but not causation. When the same problems come back every month or quarter, this still has not been resolved. Only by continuing to question processes and refining the use of data, enhanced by technology, will progress begin to be made.
• Reinvent themselves. Nobody at any stage in their life or career should be afraid to learn. Once a leader understands the principles of how techniques like Evolutionary AI work, they will start to see the potential of their business differently. This new perspective will allow leaders to identify the need to hire people with the right skills and to change the way their business makes decisions.

The advent of Evolutionary AI in business does not spell the end of people’s career, it is the start of a new chapter. Unlike Go, which is a single, complex challenge, Evolutionary AI does not succeed in a business setting by forcing someone to retire, as business is continually filled with new challenges.

However, it is only through embracing AI and thinking in terms of the value of data that the shrewdest leaders will most effectively solve today’s problems and recognize the challenges ahead for their business. If not, they risk being left behind by the latest technological advances, and facing their own Lee Sedol moment a few years down the line when they realize, too late, that the future is now.