How AI Helps In Decision Making: It’s incredible how artificial intelligence has drastically changed the way we experience technology. To say that it makes life easier is an understatement. Some may not be aware of it, but AI has become a part of everybody’s life. Here is a close look at how artificial intelligence helps in decision-making.

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SwissCognitive, AI, Artificial Intelligence, Bots, CDO, CIO, CI, Cognitive Computing, Deep Learning, IoT, Machine Learning, NLP, Robot, Virtual reality, learningThose who have Amazon Echo or Google Home in their houses know how convenient it is to have these AI-powered devices, especially given their ability and accuracy. AI can seamlessly process voice commands and execute them or deliver results during voice searches and improve customer experience.

AI and machine learning statistics

If you want to know more about how substantial artificial intelligence has become, check out these statistics below.

  • Voice assistants like Siri, Echo, and more have grown in popularity so much that 97% of mobile users are said to use them.
  • Because of the competitive advantage, artificial intelligence brings, 80% of organizations plan to use AI for customer service.
  • 61% of marketers claim that AI is a critical element of their data strategy.
  • 65% of companies that plan to adopt machine learning (ML) believe it can help business decision-making.
  • The bank system will automate up to 90% of its customer interactions using chatbots by 2022.

A closer look at AI’s decision-making capabilities 

Before answering whether or not you can trust AI in making decisions, especially when the stakes are high, you must first understand what artificial intelligence is capable of now and know AI benefits and risks.

1. AI handles multiple inputs better

Compared to humans, machines are more reliable when handling different factors, all at the same point when making complex decisions. Machines can control and process vast amounts of data and deliver valuable insights in a matter of minutes, a task that would take humans much longer to accomplish.

2. Speed decision-making processes

Everything is always moving at an accelerated speed, no matter the field or location. Whether in eCommerce or other industries, you can use dynamic pricing and see how AI can optimize your margins.

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4. Detect patterns 

Buying patterns may not be that easy to detect when doing human analysis. AI-powered analyses can spot such patterns and impact businesses positively during the discovery of these patterns.

When you can better understand a customer’s buying pattern, you can align your products based on those patterns that show the customers’ needs. Even simpler predictive tools can easily outperform humans in this aspect, and there are predictions for AI being the future of growth hacking.

5. Algorithms are immune to decision fatigue

Unlike individuals who get tired after hours of processing data and making many decisions, you won’t have to deal with this concern when using AI.

As they’re capable of decisive decisions over a long period without tiring, the quality of the decisions made is not compromised. Businesses can mitigate the risk of being exposed to poor decisions caused by exhaustion.

What challenges are there with trusting AI decisions?

What is known now is that AI is already deeply integrated into many aspects of our lives. It’s imperfect and can still be prone to errors, especially when fed with the wrong information or insufficient training data. That said, here are some of the challenges that AI faces today.

1. Human values 

As AI becomes more capable, the concern about whether humans can trust its “human values” grows. People were excited about the idea of autonomous cars until their decision-making process was brought into question how autonomous cars could deal with challenging and complex situations.

Say a truck is coming at a dangerous speed. If a driver swerves, this could result in a catastrophic accident.

  • What would the autonomous car do?
  • How will it arrive at a decision?

It is a complicated issue. Ultimately, the programmer’s bias could be a significant determining factor, and it is this bias can quickly erode people’s trust in AI decisions. […]

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