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The Advantages of AI-Driven Analytics

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Photo by Markus Winkler on Unsplash

In thinking about the advantages of AI-driven analytics, or any new enterprise technology, for that matter, it’s essential to consider two things: What can it do for your organization; and how will it ultimately improve operating metrics? When it comes to the advantages of AI-driven analytics, stakeholders will be please to hear they can find both of these factors.

  • Create Competitive and Cost Advantages
  • Facilitate a Data Culture
  • Receive Query-Driven Suggestions
  • Get Actionable Results Faster

Create Competitive and Cost Advantages

The competitive capabilities of AI-driven analytics comes from the technology having a fundamental leg up on previous iterations. Artificial intelligence empowers some incredible things, which will be looked at in greater detail in the following sections. On the cost perspective, however, the delivery method of AI-driven analytics tools and platforms can give cost advantages.

Much of what’s out there today comes through an “as-a-service” deal, where organizations pay a monthly subscription fee as opposed to an upfront purchase. This means businesses can dip their feet in the water of various platforms without having to make an all-in investment. Furthermore, it allows enterprises to scale more effectively based on active usage as opposed to having to pay a lot now for something that may or may not pan out in the future.

Facilitate a Data Culture

It’s likely you’ve heard people talking about the benefits of fostering a data culture within an enterprise. This is still a relatively new term that hasn’t been totally digested by the greater business world. A recent survey of executives at Fortune 1000 companies found almost all were investing in data, but under 40 percent had successfully bred a data culture. AI-driven analytics can help get your organization to a better place in this regard.

One major benefit of business intelligence tools powered by AI is they tend to be more user-friendly than the monolithic platforms of the past. By democratizing data through self-service applications, enterprises can gradually bring data into the common vocabulary of everyone, regardless of role.

Relational search is an example of an AI-driven tool that can help create a more cohesive data culture with an organization. It essentially works in the same fashion as a search engine, where you just type in a query and receive an immediate response. The simplicity of this vastly increases the pool of people who can use data on their own.

Receive Query-Driven Suggestions

In many areas of our lives, we’ve become accustomed to the invisible hand of artificial intelligence. YouTube is one of the best examples of this, as it does a masterful job of delivering exactly the video you want to watch without you even knowing it. This is possible due to AI, which helps predict what you want to see with incredible precision.

The same principle can be applied to business intelligence, thanks to AI-driven tools. Certain platforms powered by AI can actually steer you in the direction of further insights. This can lead to discoveries that might have taken months to find otherwise, if at all.

Get Actionable Results Faster

Time is of the essence in most things; but this is particularly true when it comes to competitive industries. If you’re taking too long to adapt, someone else is probably finding a way to surpass your progress. AI-driven analytics tools address this by shortening the time it takes to arrive at actionable insights.

For starters, AI-powered tools tend to find answers quicker than outdated ones, as they’re able to analyze more rows of data in less time. Additionally, the fact more people can use AI-driven analytics due to its superior user-friendliness means not as many queries need to be sent to the data team. When you don’t need to send off queries, and can instead run them on your own, it greatly reduces the time required to arrive at an answer.

On another level, embedded analytics, which is often within the capabilities of AI-driven BI tools, can make using data more efficient. Important visualizations and other resources can be placed where they need to be, so people will have access to the information they need, even if they’re not using the tool that created it.

AI-driven BI tools are some of the most useful pieces of technology at any enterprise today. Organizations should seriously consider the benefits of adopting some of these tools to achieve better outcomes.

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