Technology

Five reasons AI is better at making business decisions than you

Anthony Aarons /

Australian government innovation

Chief executive officer and co-founder of epifini Anthony Aarons. Source: Supplied.

There is an adage that all businesses are only three poor decisions away from a failure.

Decision making is the main job of any business owner or leader. So if you are one, undoubtedly the missed opportunities and ‘if only’ moments are part of what keeps you up at night.

Nobody ever pretended decision making is easy. But it becomes complex when you are choosing between options with potentially both positive and negative consequences. For example, you could be deciding between a big client deal with an increased turnover but uncertain profitability, or a deal with less turnover, higher stable profit, but also less brand kudos.

When we agonise about these decisions, we become stressed. And as a result, our decision making becomes impaired. Stressed people tend to make worse decisions — focusing on the rewards only, rather than the possible pitfalls.

To make effective decisions, leaders must access as much useful information as possible in order to gain a clear picture of how and why a challenge has presented itself, and what options are available to take advantage or mitigate damage.

Further, they must:

  • trust the information;
  • know that it is the right data;
  • identify the problems, risks and opportunities;
  • see the possible paths; and
  • make the decision without stress or trepidation.

That’s an almost impossible task for most humans, but it’s something artificial intelligence was born to do, and something the active learning model of AI excels at.

1. AI information is more trustworthy

Trust is built on three distinct pillars: capability, consistency and intention. If any one of these three are missing there can be no trust — either of a person or the information.

Is the person delivering the information skilled to access and present the right information accurately? Do they do this consistently? Are the intentions of the deliverer beneficial to the leader or self-serving?

Data-driven AI can provide a genuine solution to the trust issue. It can do a deep query of your business operations, structures and people, identify success factors and failure risks, and then deliver a road map to advance your business. And it does all this without guesswork, playing politics or following personal agendas.

2. AI provides the right data

Much of standard AI just attempts to exploit ‘big data’ — the masses of information and data on a given business problem. However, big data comes with its fair share of problems.

Making relevant information visible in the sheer volume of all information can be unwieldy.

Sadly, many leaders have found this type of data flood difficult, and time consuming, to understand. KPMG’s Guardians of Trust report found leaders found this data less trustworthy than their own gut instinct.

However, active learning AI uses the principles of efficient exploration to gather relevant, small pieces of data as rapidly as possible and — like a master detective — put all the pieces of the puzzle together to come up with an astonishingly accurate picture of reality, without interrogating everyone about all possible scenarios and suspicions.

NASA used active learning in its Mars Rover. The vehicle ‘knew’ it was on a planetary surface, but that was practically all it knew. It had to explore to find out where to drill, where it was dangerous to go and the most efficient directions to travel in to get its job done. And it did this with perfection.

3. AI explores and targets root causes

While NASA was relying on active learning, this capability hasn’t historically been given much attention in the business world. Now, it can be used to not only explore Mars, but also a business.

It does this by means of online ‘interviews’ with the leaders and other members of the team.

We’re not sitting in front of a robot — yet. Rather, it’s an online deep-query session where you are asked questions based on your previous answers. So, it feels like a conversation with a very intelligent, perceptive and challenging interviewer.

Active learning AI has a ‘brain’ that has representations of multiple experts’ knowledge in everything from growth to culture, and from process management to leadership effectiveness. Its algorithms are guided by particular imperatives, in order to explore and analyse a business.

Active learning takes the emotion out of the exploration and isn’t fooled by people telling it what they think it wants to hear. As a result, it is able to track problems back to their true source, so business leaders don’t put resources into treating symptoms rather than root causes.

4. AI provides elegant and simple solutions, fast

Active learning in this context measures the impact of seemingly disparate issues, and identifies areas of need with impressive accuracy and consistency.

It then delivers a report complete with diagnostics and recommendations that interpret the misalignment of people in the business and ‘root cause’ analysis of problem areas; and provides a succinct priority list of areas that require resources and effort.

It even assesses the likelihood of achieving a business strategy with a ‘net achievability score’.

And it does this faster and more effectively than any individual human or group of human beings — typically in about 90 minutes.

5. AI supports leaders

The beauty of AI, and specifically active learning AI, is its ability to take complex information and produce simple and usable outcomes.

It extracts information that is relevant and important in a way that can be used effectively by a leader. And it does so repeatedly, time after time.

If trust is one of the most important factors leaders require to enable them to make the right choices, then AI is the best mechanism for leaders to find sources they can use with confidence to gain insight — and make the right call.

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Anthony Aarons

Anthony is the chief executive officer and co-founder of Epifini, an AI platform for business analysis, performance and strategy.

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