The age of AI is officially here, even if it’s been a slow transition for many businesses. The sheer range of artificial intelligence (AI) tools has left many wondering what its place is in the real world, particularly if they’ve been burned in the past. Most employees have at least one or two examples of how the promises of AI have fallen well short of reality.
To capitalize on the information provided by AI, it’s clear that companies funding consequential AI are the ones winning the race. With this strategy, leaders invest only in machine learning that can start with a problem and return a real solution (as opposed to endless data).
Edward Scott, the CEO of ElectrifAi, embodies this approach. To him, it wasn’t about extolling how many data points could be collected or stored with these tools, it was about transforming that data into an action plan that would work for his clients.
Strategic Top-Line Revenue Growth
How a company tracks its data says a lot about how they control its costs. Even with the endless innovations of the modern age, many companies are still keeping track of their information through spreadsheets.
ElectrifAi worked with a large restaurant chain that had 50 distribution centers serving 1,000 locations. The freight and logistics data was incomplete, to say the least. Once they had moved away from spreadsheets, they were able to analyze what their routes, trucks, diesel, and repairs were actually costing them. ElectrifAi was able to save the business millions of dollars by optimizing every facet of the operation through the company’s machine learning.
AI learning also helps companies prove their commitment to their customers. For instance, ElectrifAi set up dozens of cameras using edge computing processing in dairy farms, which cut down the costs of processing in the cloud and eliminated latency issues. Owners and operators could show how they were treating their animals in real-time.
Funding Real-World Solutions
Scott knows that even the best-run companies struggle with challenges every day. It’s difficult to know which threats are real and which are a ship in the night, and most leaders don’t have time to wait around for months before they recognize the true value of a project. Machine learning has been honed to quickly generate real answers for company owners and employees.
The machine learning was designed to deliver value back to the client in just 6 – 8 weeks, cutting down on the need for data engineers and scientists. These experts, while effective at scrubbing away irrelevant information, are simply too scarce (and expensive) to hire at an unlimited rate.
Companies like ElectrifAi use pre-built machine learning and pre-trained processing solutions to both streamline and expedite the endeavor. What would take a standard company a full quarter (or more) to build and implement can be replicated in less time without sacrificing the results.
According to ElectrifAi, funding Consequential AI should be a top priority. Funding consequential AI may not always be an easy sell, particularly for medium-sized organizations with smaller budgets. However, the returns on the action items delivered from machine learning can make it far easier to see the true value of the investment.
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