Listening to your gut will be much safer if you also listen to the machine crunching the data. Decision-making remains one of the ultimate tests for leadership in new entrepreneurs.
copyright by www.entrepreneur.com
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.
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.
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
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.
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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.
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. […]
read more – copyright by www.entrepreneur.com
Listening to your gut will be much safer if you also listen to the machine crunching the data. Decision-making remains one of the ultimate tests for leadership in new entrepreneurs.
copyright by www.entrepreneur.com
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.
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.
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:
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.
Thank you for reading this post, don't forget to subscribe to our AI NAVIGATOR!
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.
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. […]
read more – copyright by www.entrepreneur.com
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