Artificial Intelligence Can Help Leaders Make Better Decisions Faster Listening to your gut will be much safer if you also listen to the machine crunching the data.
By Jacky Chou •
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Decision-making remains one of the ultimate tests for leadership in new entrepreneurs. Even experienced leaders who have a track record of sound decision-making have, at some point, made a drastically poor decision that shook their reputation.
As the talk about AI promises a radical transformation of the organization, leaders are especially curious to know if it will make it easier for them. While a lot of them are excited, some of them don't want decision-making made easier. Their ability to make sound decisions without complex technology is the very foundation of their reputation as good leaders.
Related: Why 'Cognitive Computing' Is the Next Big Thing for Business Growth
The good news is that AI is quite unlikely to make it easier for decision makers as they'll be required to input judgment in the machine predictions. As the real impact remains to be seen, there are ways in which AI is set to inevitably affect business decision-making.
1. Prediction.
Through data mining, many businesses are already using predictive analytics to make better decisions. Predictive analytics allows businesses to anticipate events by looking at a data set and trying to guess accurately what will happen at a certain time in the future.
AI brings with it machine learning, another technique used in predictive analytics. The variation is that while data mining involves merely identifying patterns in large data sets, in machine learning, machines are not just designed to learn from the data, they are also built to react to it by themselves.
With the information provided, decisions can be made on such issues as:
- Which ads are served based on cost-effectiveness and potential ROI
- How to optimize the buyer journey by analyzing consumer behavior
- How to reduce customer churn
- How achievable are the set goals
2. Less decision fatigue.
Various psychological studies have shown that when we're faced with many decisions to make within a short period of time, quality declines because we gradually deplete our mental energy.
A case application of this is when supermarkets place candy and snacks at the cash register. Marketers know you'll be making decisions throughout your short shopping trip and will be less likely to resist the sugar rush by the time you're done. But you know who can resist the sugar? A machine.
Algorithms, not prone to decision fatigue, can make an infinite number of decisions per day, each as accurate as possible. Executives who use AI will be at an advantage by using it to bypass human weakness.
Related: The Sooner You Get Your First AI Job, the Better for Your Career
3. Multi-tasking.
When making complex decisions, executives typically need to look at a set of different factors. Where there's too much data to be considered, the decision-maker may get overwhelmed, leading to disastrous decisions.
On the contrary, a machine can easily handle multiple inputs without exhaustion or confusion. All that's needed is a set of instructions or programs that guide the machine to use probability and suggest or implement the most logical decision.
4. Better human judgment.
Until we can instill emotional intelligence in AI, the human will be the one to make judgment calls. Sure, a machine can be left to make decisions on simpler tasks that don't require emotional intelligence and experience -- two factors that form the basis of judgment in business. But for the more critical ones where the probability and cost of a mistake is high, a human is needed. As argued by Ajay A., Joshua G. and Avi G., the ability to make trade-offs when necessary is another important aspect in good judgment that cannot be left to AI. This is because it requires an insider understanding of the organization in terms of values, goals and risks to give sound judgment.
But AI can and should still be part of making judgment. Its role is to provide the human with all the facts and possible outcomes or predictions.
5. Deciding who gets the job, if anyone.
To find the best person for the job, the hiring manager needs to go through the pool of applicants and vet each one individually. But who has time for that when there are so many applicants? AI does.
In the future, HR will be able to actually select the best candidate from all applicants by automating most of the responsibilities that make the process slow and inefficient. Machines will sift through hundreds of CVs to find the best, analyze online activity and find out enough information about them to suggest the best.
With the mundane tasks out of the way and facts already compared for them, all the hiring manager will need to do is use their judgment to make the best decision.
Related: 6 Common Hiring Practice With Unintentional Bias
