Artificial intelligence (AI) has recently gained momentum in the business world, changing how people from numerous industries operate and make decisions. However, many businesspeople often need help gathering and utilizing the data that AI tools need to work. That’s because the information often comes from various sources and locations. Fortunately, an emerging option called AI unified analytics can solve that problem and enable companies to harness the power of artificial intelligence. As the name suggests, it combines artificial intelligence with efforts to collect and organize data, regardless of its numerous sources. Here’s a closer look at why AI unified analytics makes sense for today’s companies and why you should strongly consider implementing it in yours. Use your data more effectively Many companies collect so much data that leaders don’t know how to use it or even that it exists. In many cases, that means decision-makers may not have an accurate view of issues the business faces or might lack all the insights needed to make the right choices. Dark data is the information a company collects but doesn’t use, aptly named because it stays hidden and unusable. However, business representatives that commit to reducing it can unlock previously unavailable insights. Minimizing dark data can also and prevent future problems. help company leaders identify risks Consider how companies in many industries, such as food processing and pharmaceuticals, must abide by tight regulations. Businesses with data its leaders don’t know about means executives may be in for unpleasant surprises that lead to fines and other punitive actions from authorities. AI unified analytics can help company representatives get to the bottom of their dark data. That’s the first step to converting that information into useful and actionable insights. Support overall tech upgrades It’s sometimes hard for business leaders to justify the high upfront costs associated with tech upgrades, even if they know they will make the business more efficient or bring another desirable result. However, according to a January 2022 Gartner forecast, global IT spending is rising. It predicted a during the year. 5.1% increase in IT expenditures The options for using technology in a business are virtually endless. For example, companies can use specialized products relevant device statuses on centralized dashboards. Many company leaders are open to using AI but don’t know how to get started. to launch firmware updates and show AI unified analytics can support existing processes, no matter how and to what extent a company already uses technology. In many cases, it provides a distinct path for improving them. A customer service team leader may want to know the common themes in support questions and trouble tickets, and the company has interfaces and databases for employees to use. However, people may engage with customer service workers through various channels such as Messenger and WhatsApp chats, emails, phone calls, and face-to-face interactions. AI unified analytics makes it easier to compile instances from those various sources. Artificial intelligence algorithms work much faster than humans can without help, so they can search for keywords and phrases that show why people most frequently need customer service. Minimize supply chain disruptions The people overseeing supply chains have dealt with numerous disruptions that put them at risk of missing deadlines and disappointing customers. However, AI unified analytics can make such issues happen less often and lessen the severity of any ramifications. Deloitte published a September 2022 survey that over the previous 18 months. Shipping delays were the most common issue, affecting 59% of respondents. Component shortages and transportation slowdowns were frequent problems too, both reported by 56% of those polled. examined the effects on supply chains It’s impossible to predict and prepare for all possible disruptions. However, experts advocate for to strengthen supply chains. Decision-makers that can pull all the information from various sources can feel confident enough to act on it. having a unified data management strategy The use cases for AI unified analytics span beyond, but also include, the supply chain. One of the primary benefits of up-to-date information is that it gives people time to act. Even though individuals can’t predict the future with certainty, reliable data often helps them spot the signs of trouble. Artificial intelligence also enables people to spot worrisome trends faster. Perhaps a once-outstanding supply chain partner has gradually started missing performance targets and minimum standards. AI algorithms allow for confirming such trends, giving supply chain managers the leverage they need to engage in productive discussions with the company in question. How will you use AI unified analytics? These are a few reasons why it often makes good business sense to explore the possibilities of AI unified analytics. Implementing new technologies and associated processes almost always takes significant time and effort. However, it’ll likely pay off over time, especially if you decide how and why you want to utilize AI unified analytics and set associated goals. Sources: https://www.pwc.com/us/en/tech-effect/ai-analytics/how-dark-data-can-unlock-real-value.html https://www.gartner.com/en/newsroom/press-releases/2022-01-18-gartner-forecasts-worldwide-it-spending-to-grow-five-point-1-percent-in-2022 https://www.trek10.com/blog/is-iot-device-shadow-right-for-you https://www2.deloitte.com/us/en/insights/industry/manufacturing/realigning-global-supply-chain-management-networks.html https://venturebeat.com/data-infrastructure/transforming-the-supply-chain-with-unified-data-management/

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