December 03 - 06, 2019
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How Do I Build the Business Case for Artificial Intelligence?


06/20/2019

Building a business case for artificial intelligence can be difficult. But if your company is currently experiencing issues that could be easily solved by AI, it creates a larger incentive for your business to invest. The range of areas that intelligent automation can be applied is expanding – as voice recognition, natural language processing and machine learning technologies have become more friendly to non-specialists. The rapid development of intelligent automation is ushering in a new era of productivity and innovation. It sets new standards of quality, efficiency, speed and functionality. Companies that have already implemented AI are likely to surpass competitors that do not adopt new technologies.

According to PwC, artificial intelligence will contribute $15.7 trillion to the global economy by 2030 and MIT Sloan Management Review’s 2017 Artificial Intelligence Global Executive Study and Research Project found that 85% of executives believe that AI will help their businesses gain or sustain a competitive advantage.

It’s safe to say that if you’re not using AI, you should be looking into it. AI-based analytics create the ability to make better business decisions, improve network and storage technology, automate and improve complex analytics tasks, and look at data is real-time with minimal need for supervision. There are various areas where artificial intelligence and machine learning can help solve your company’s challenges – but first you need to take the steps to build the business case.

Building the Business Case for Artificial Intelligence

The first thing you need to assess is what your largest issues are currently that can be addressed with automation. Identify a need and a desired outcome. Do you have enough data to work with for automation? Determining the kind of data that lends itself to pattern identification and decision making are both important steps to building a case. Make sure that the technology is sufficiently advanced to do what you need to do – if not, an existing solution may be the more cost-effective option. MIT Sloan Management Review reports that 76% of companies now use machine learning as a normal part of their business model to boost revenue – so it might be a good idea (as a final step) to determine and figure out how you will measure outcomes and incorporate these new understandings into your existing business model.

General Business Solutions

Cybersecurity

Utilizing AI and machine learning to monitor fraud detection, as well as cybersecurity attacks, can provide a huge advantage in the long run. Not only does it save your customers information from getting stolen, but it saves your company as well. Fraud will be detection earlier, thus resulting in more your clients and customers staying with you. If your company is having trouble with fraud detection, you should really consider adopting AI and machine learning. Fraud detection, as well as cybersecurity threats, is a matter of detecting patterns – so machine learning tools will be able to pick these up and decrease any false alarms.

 According to Clyclance CEP and President Stuart McClure, their AI prediction technology looks at millions of files and attacks to learn exactly what makes them up. By understanding these ‘mathematical DNA’ they can prevent and protect against future attacks.

“It looks like we’re predicting attacks, when really we’ve just learned through AI machines learning what the DNA of these attacks is,” McClure said.

Customer Service

Customer service can make or break a business, so why not turn that into a competitive advantage through the use of AI tools? Integrating AI can help predict customer churn and act on it – AI can analyze post-call comments, categorize them by topic and flag sentiment scores that indicate customer dissatisfaction. Clients now are able to receive insight into customer motivations, concerns and reasons for calling.

Machine learning is constantly running data points on customers based on their profiles and types of things they search in your store or site – which means that you can use AI algorithms to target customers who view certain pages, etc. This impacts the way you can sell to your customers. Algorithms help you offer the right product, at the right time, with the right price based on your user – resulting in more sales.

Chatbots are also a popular and efficient way to improve your customer service. Companies use chatbots to help answer customer questions and comments online. If you’re worried about your company’s voice – don’t be. It’s completely possible to build chatbots to reflect the personality of your brand, help build rapport and acknowledge human slang and jargon to carry on an online conversation as human-like as possible.

Hospitality companies, such as hotels, use AI to monitor their own and competitors reviews to identify guests’ needs. Using a platform called Metis, Dorchester Collection summarizes and contextualizes reviews to gain insights, plan future steps and maintain a competitive advantage.



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