Investments in artificial intelligence are rife. According to Statista, the global AI market is expected to reach $7.25 billion this year, fueled by investments in image recognition, object identification, detection, and classification, among various other developments. But that’s nothing compared to future forecasts. By 2025, the AI market is expected to reach nearly $90 billion.
But while AI is disrupting industries across the board, no area is currently benefiting more from AI than enterprises data analytics, which presently makes up the majority of AI-generated revenue with the biggest potential impact in marketing and sales, as well as supply chain management and manufacturing. However, industries like travel, transport and logistics, and retail stand to benefit the most incrementally compared to other non-AI analytic techniques.
Collecting data and using business intelligence systems to get a leg up on competition and improve internal processes has existed for decades. But leveraging AI-powered tools offers unprecedented insights and speed, and at scale. Companies that can adopt AI-powered data initiatives into their organization stand to benefit in a variety of ways compared to their competitors.
Here are four ways AI is already flexing its muscles in enterprise data efforts.
Leaner Operating Expenses, Better Margins
Every company that’s ever existed would like their operating expenses to be lighter, even if they’re already lean machines. AI-powered data analytics can not only highlight companies’ inefficiencies, such as repetitive roles or investments that aren’t contributing to growth, but it can identify areas that’ll increase revenue, for example, tapping into a company’s supply chain to identify a cog that’s having a slight, but sizable effect on annual production, and thus revenue.
Stellar Customer Experiences
According to IBM, by 2020, 80 percent of all customer interactions will be handled without a human agent. The standard customer service medium for decades, the phone call, is slowly being phased out, with 72 percent of millennials believing it’s not the best way to solve a customer-service issue. We’ve seen the rise of chatbots, some more graceful than others, but the medium will inevitably improve.
What’s so compelling about this medium is the abundance of clear, actionable data it generates. Chatbot data provides insights on the most commonly asked questions and highlights routine pain points customers are experiencing. Instead of needing to dig through piles of data to learn about these issues, AI-powered platforms can tap into the data, allowing an employee to ask a simple question and be provided answers. Some artificial intelligence in business tools even uncover hidden insights, identify data anomalies and correlate trends to lead employees to questions they might not have thought to ask, or information they may not have found. AI is providing a clearer picture for the employee, the company, to improve their customers’ daily experiences.
Improved Internal Collaboration
A major thorn in many business’ data efforts is getting the entire organization on the same page. When the majority of employees can’t easily access data, and ad-hoc reports are requested seemingly at random by different teams, there’s no shared info stream for cross-collaboration to occur. With AI-fueled tools, teams can work together with a general goal and leverage the immediacy of a platform’s answers to build a plan and generate next steps.
There’s also the general issue of employee buy-in that AI solves. Historically, no matter how robust an org’s data foundation, it was tough to get all employees to buy into data. Without all roles believing in the information a data platform is telling them, highlighting issues and developing solutions becomes incredibly difficult, if not downright inefficient.
Better ROI on Data Hires, Reduced Turnover
Making a bad hire is expensive. It’s worse to drown good talent with tedious, short-term tasks. In the case of hiring data professionals, it’s really expensive. Consider the average data scientist salary is north of $113,000 and that a reasonably large company needs at least a few employees to run a successful data program. If those employees spend most of their time doing tedious tasks like building report requests and pruning datasets, a company isn’t seeing any long-term benefit.
Artificial intelligence eliminates a lot of these repetitive tasks for data scientists, allowing them to focus on higher-level data initiatives aligned with a company’s long-term goals. Giving data hires a more meaningful, impactful workload will also improve their morale and reduce long-term turnover, all of which saves significant costs.
Of course, the real benefits of adopting AI-powered data analytics tools for companies won’t be realized until a data culture’s in place. As unique as every business is, leveraging the speed, scale and hidden insights of AI will give early-adopters a leg up on their competition and pave the way for long-term growth.
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