Leveraging artificial intelligence in management decision making – time to get interested?

Artificial Intelligence (AI) and machine learning are hot topics of today’s digitizing world. Industry research firm Gartner named AI as its number one strategic technology for a second year in a row.

Both technologies are estimated to blossom in 2017 and generate new innovative solutions for business use. Several companies have already started to test AI based solutions in their operations. However, examples for using these same technologies and intelligent applications at the C-level or for management teams are nearly non-existent; hardly any company uses AI to drive better management decisions. Management teams rely still on very traditional ways of periodically reviewing historic financials and other mostly backward looking updates of the market and competition. To answer questions about the future of their business; how the next 3-6 months will look like, some may use scenario evaluation and rating systems, but most companies proceed as they have done for years – using experience based estimates and gut feeling supported by historical and current data. Opportunity to do better? AI and machine learning can definitely provide interesting possibilities.

The reason why AI is not widely used to support management decision making today is threefold. First, AI in general is new technology creating many emotions, not to mention using it in the management decision-making context. Second, the benefits of using AI in the management decision-making are not so far widely broadcasted. Thirdly, not all decisions are suitable for leveraging AI – some say never, some say yet.

The first reason can be understood, since it is still relatively limited to many business leaders how the digitization will impact their business. Or its immense power to completely change the competitive landscape. Given this situation, asking to understand the power of AI in decision-making is a stretch, but perhaps asking to get interested in digitization, AI and machine learning is not?

The proof of AI’s value to generate business results is rapidly becoming evident and more widely broadcasted. A Japan based insurance company has adopted an AI system that will calculate and decide insurance policy payouts instead of the traditional human workforce. The firm believes using AI will result in better payout decisions, increase productivity by 30 percent while saving on salary cost. Uber is driving better decisions for their fleet management by predicting customers travelling habits within its core mobile application. Furthermore, Uber is improving its maps by using computer vision and creating algorithms for its autonomous vehicles. AI can easily release managers from their tedious admin tasks which today may take more than 50% of their time.

Many executives and business people find it cumbersome to work with new technologies. This is one reason why large technology giants are investing enormously to make the interaction with AI easier. The trend is to model the management interaction interface with AI technology primarily like human interactions e.g. conversation based. Many banks have already implemented a natural language processing AI bots which will answer customer inquiries and perform basic banking transactions like money transfers or payments and balance inquiries. In more complicated tasks or when the AI bot is unable to perform the tasks, it will pass the customer over to a human customer representative.

Are conversational interfaces really a big deal? They’re game-changers. They will certainly drive the AI usage among executive teams, leveraging AI more in the strategic business context. Currently the technology is still limited compared to the human’s ability to handle vague, difficult, complex decisions, but the AI technology and its applications are developing at rapid pace.

It is important to keep in mind that the human as decision maker is and will be in control.  No AI system will decide which market the company will ultimately enter, or what acquisition it should make. Neither can they yet predict consumer’s behavior accurately, because it is often irrational. An extreme example of irrational behavior and a good evidence of so called ‘social gravity’ was Pokémon Go about a year ago.  No AI system (or anyone for that matter) could have predicted the speed and momentum it gained.  Purely irrational, based on pull driven demand amplified by social gravity impact.

But AI can provide already today rather revealing facts and arguments for various management activities to enable better informed decisions. Many aspects of artificial intelligence such as using neural networks and deep learning may not be entirely new. However, AI is rapidly developing to provide ever more intelligent recommendations based on real time data through sensors and neural networks thanks to the fast development of IoT. Combine that with historic data, knowledge and insight supported by ever more complex algorithms, it will increase company’s decision making speed and accuracy to a whole another level.

In the end the decision maker must use his or her judgement – based on creative thinking and experimentation, experience, empathy, facts, wisdom and intuition.  What if all that could be complemented and supported by AI powered suggestions and insights. Our prediction is that companies that will have the capability to use both the human and the AI element to its full potential, will have a clear competitive advantage and ultimately perform better. This is no longer science fiction but reality of today.

So why not start today to plan how AI and machine learning could benefit your company?

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