Artificial intelligence is about to make your data analysis a whole lot faster.
The process of turning data into an actionable report is crucial for business leaders, with Gartner predicting that the market for business intelligence and data analytics software will grow to $13 billion by 2025. Part of that growth is being driven by businesses that are using A.I. to analyze large sets of data at a speed and scale that would simply be impossible for humans. The leaders behind these companies say that A.I. allows them to deliver high-quality reports in moments, rather than weeks.
Here are three examples of how you can use A.I. to make stronger, better, and faster decisions.
A.I. for saving your supply chain
Disruptions in your supply chain can wreak havoc on your ability to do business. When a company wants to identify the biggest risks to its supply chain, it either has workers spend days or weeks compiling the relevant data from disparate sources, or it pays an outside consulting firm tens of thousands of dollars to handle it, according to Francisco Martin-Rayo, co-founder of A.I.-powered agricultural supply chain management tool Helios. The firm, founded in 2022, uses A.I. to exponentially speed up that process, enabling procurement specialists to easily keep track of all their suppliers and analyze each supplier's current risk level.
Helios compiles billions of data points related to historical weather trends, commodity-based economic indicators, and political signals to create its analytics. Those historical signals are compared with the supplier's current indicators to predict disruptions before they happen. Helios is also working on a generative chatbot called Cersi (named for the Greek god Helios's daughter). By eliminating the time-intensive process of generating reports, Martin-Rayo says procurement and analysis teams can spend less time identifying risks and more time mitigating them.
A.I. for learning more about your customers
Perfecto Sanchez and Christina Van Houten, co-founders of A.I. stakeholder intelligence program Equity Quotient, say that you can use A.I. to simultaneously reach new customers and deepen relationships with existing ones through "demographic alignment," defined by the pair as the process of tweaking elements of your business so that they algorithmically appeal to the specific customer demographic you're trying to reach.
As an example of how Equity Quotient's platform, which is powered by a massive set of public and private socioeconomic data, can be used to achieve demographic alignment, Van Houten related a recent experience she had working with a national mortgage lender's CMO. The CMO wanted to gain a better understanding of how to secure new loan business from second-generation Hispanic populations across the country. With help from Equity Quotient, the CMO was able to identify specific cities and counties with high Hispanic populations and significant access to affordable housing stock. That data informed a targeted marketing campaign and sparked an initiative to hire more Hispanic loan officers. Van Houten says that studies have shown minority borrowers are more likely to be approved by minority loan officers than White ones. "We see our opportunity for growth in giving leaders a clearer view of the individual pieces that make up their business," says Van Houten.
A.I. to make sense of your raw data
Companies are leaving a lot of data on the table. According to a 2023 report from Seagate, only 32 percent of data available to enterprises is ever analyzed, while the remaining 68 percent goes unleveraged. Arina Curtis, co-founder and CEO of DataGPT, an AI-powered platform for analyzing internal business data, believes that by analyzing 100 percent of a company's data, businesses can understand the context and meaning hidden within the numbers, leading to better decisions. Once DataGPT connects to an organization's data warehouses and other data repositories, users can ask natural language questions to a chatbot and get detailed analysis back, according to Curtis.
One of DataGPT's largest clients, the ad-supported streaming service Plex, used DataGPT to understand what was driving a decrease in new users on a specific streaming device. The company found that conversion rates were actually up overall, so the issue had to be related to the Plex app's performance on that specific streaming device. The Plex product team discovered that glitches were hampering the app's performance on the streaming device. Within a week, fixes had been deployed, and the conversion rate immediately began shifting back to normal with a healthy flow of new user registrations.
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