The Data Daily

5 ways to use artificial intelligence (AI) to improve business efficiency

Last updated: 09-19-2019

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5 ways to use artificial intelligence (AI) to improve business efficiency

Regardless of a company's size or type, its executives typically look for ways to help it operate as efficiently as possible. They understand the link between efficiency and profitability. If employees waste too much time with drawn-out processes or complicated tasks, it'll be hard for the enterprise to remain profitable and adapt to challenges. Fortunately, artificial intelligence (AI) supports the need for effective business operations. Here are five ways enterprises can use AI for help:

Chatbots are an increasingly popular option for businesses to try, and they use AI to work. Companies often build chatbots that can answer any questions from customers that come through outside of business hours. Some identify the nature of a person’s problem, then either attempt to tackle it with preprogrammed answers or pass the communications to a human support worker. The retail industry, in particular, saw success by deploying chatbots.Global data collected by Juniper Research shows an estimated 2.6 billion retail-based chatbot interactions in 2019, and the company forecasts the number to rise to 22 billion in 2023.

Chatbots are excellent for answering simple questions like “How late are you open today?” or “Do you have gluten-free menu options?” Getting quick answers to queries like those increases the chances customers will choose to do business with one company over another. Equally importantly, when chatbots can give responses in a matter of seconds, there’s no need for humans to stop what they’re doing and address the questions.

Company reports reveal things such as which products are selling the fastest and where they’re most popular. They can also confirm the impacts of marketing campaigns on product sales, break down the costs of a new packaging choice or shipping method, and much more. However, as anyone that files reports knows, creating them is a painstaking task, and trying to rush through the process could cause mistakes. Some forward-thinking companies are combining AI with big data analytics. Doing this brings better forecasts and takes some of the burdens off the people who prepare the reports. AI also helps conquer the inevitability of mistakes. Even the most careful people make blunders, often because of mental fatigue.

AI learns to spot patterns in data and gets smarter with time. This means reports get finished faster and contain more-reliable information. The reliability aspect is crucial, especially since recently published research indicated two-thirds of the senior executives polled had no confidence or trust in big data.

Using AI does not mean companies can do without data scientists. However, depending on the technology allows them to reduce the uncertainty that may otherwise exist. It also prevents employees who work with a company’s data from being asked to recheck the findings, even if they initially took appropriate precautions to ensure accuracy.

Fast data transfers help AI technology work. Concerning some information-intensive applications like virtual reality (VR), any slow transmissions greatly interfere with the realism, and content immersion people should enjoy after strapping on a VR headset. As it turns out, AI can improve data transfer speeds, too.

For example, services exist that boost speeds across any wide-area network (WAN). Users enjoy consistently accelerated rates regardless of the kind of information transferred. Some companies have solutions that can reduce WAN job times by up to 98%. These AI-driven options work particularly well when companies need to move information between data centres or cloud environments.

One of the ongoing challenges faced by IT teams of all sizes is to separate the true cyber threats from false alarms. The difficulties associated with categorising the two types may mean cybersecurity professionals waste time getting to the bottom of things that are ultimately nonissues. They might miss the actual threats that could derail a company’s operations.

Besides detecting possible intrusions associated with a network, AI can screen for software abnormalities that may make it easier for cybercriminals to orchestrate their attacks successfully. It can also find malicious software hackers installed. Due to this kind of information and the advantages of receiving it through real-time updates, IT security teams can work more productively. They can use the majority of their resources on the threats that matter most to the company’s stability.

Some organisations have even used AI to help them conquer the substantial skills shortage in the cybersecurity industry. At Texas A&M University, the Security Operations Center deals with about a million attempted hacks each month. The facility has some full-time workers, but students comprise most of the staff. They work alongside AI that aids in threat monitoring, detection and remediation.

Before students see possible threats, the smart technology finds and groups them. This approach saves time and lets the team get to work investigating the problems and deciding how to handle them.

Statistics show the average time required to hire a person for an open position ranges from 12.7 to 49 days, depending on the industry. The timing also varies based on the type of work a job requires. For example, it takes a shorter amount of time overall to find someone for an administrative or human resources position than one associated with a creative or advertising role. Then, of course, interviews are more extensive for high-profile work.

Human resources professionals increasingly use AI to cut down on the time between first posting a job and finding the ideal individual to hire. For example, an AI platform could look for particular desired keywords in submitted resumes, saving hiring managers from poring over the documents themselves. AI can also pitch in during interviews. A company called VCV recently raised $1.7m to further develop its AI tool that has voice and facial recognition components. Candidates are asked to record videos of them answering interview questions, but they can’t prepare for the specific content in advance.

Then, VCV’s tool assesses the interview based on several characteristics. It could see how nervous a person seemed or if they displayed certain mood or behaviour patterns that could indicate they fit the company’s culture. The startup behind this product says its recruiting technology saves companies more than 20 hours of work.

Human resources teams still have to remember that technology can make mistakes like people. Amazon halted development on an AI recruitment tool after realising it showed bias. That’s why users cannot assume any AI tool is foolproof, but they can use it to speed up the parts of the hiring workflow that often take the most time.

The examples here highlight why so many company leaders conclude that if they use AI, they could cut down on inefficiencies. Getting the best results from AI means looking at where bottlenecks exist, then figuring out if and how it might remove or minimise them.

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