There’s been a lot of talk about the potential of artificial intelligence (AI) and machine learning over the past couple of years—so much so that it hasn’t always been easy to tell if it’s all just hype.

From quirky animatronics to fully-operational digital concierges, the most commonly discussed uses of AI and machine learning often sound like something straight out of a low-budget 80s sci-fi movie. But, for your business, they now present very real and very significant opportunities.

Regardless of your personal level of excitement (or terror) at the thought of autonomous machines making choices for you, one thing has recently become clear. AI and machine learning mark the next logical step forward in how businesses make the most of their data.

 

Taking your hands off the wheel

From a business perspective, it’s not always clear what sets advanced machine learning apart from the current analytical processes and tools that organizations have grown reliant on in recent years.

With traditional analytics capabilities, you can dive into data and use specific queries to manually identify trends and turn that data into actionable knowledge. The big difference with deep, machine-based learning is that you don’t need to give the technology anywhere near as much direction.

Instead of looking for something specific, deep learning technology processes gigantic volumes of data in real-time, gleaning a significant amount of insight from both the consistencies and inconsistencies between individual entries.

Through that processing and analysis, it builds knowledge of what that data should look like, giving it the ability to flag things that look out of the ordinary—which is where the most valuable nuggets of insight tend to hide.

For an organization such as a bank, for example, deep machine learning can be used to process millions of transactions in real time and spot the tell-tale signs of fraudulent activity while it’s happening.

It’s that leap from retrospective analysis to real-time insight that has so many businesses believing in AI and machine learning.

 

So, where does AI fit into all of this?

Machine learning provides the real-time insight, but AI is what turns that knowledge into automated actions.

The real beauty of using artificial intelligence and machine learning together is that they effectively fuel one another, and help each other become smarter.

Take simple AI like an automated customer assistant, for example. It gathers data constantly while it’s in use, remembers every interaction, and when paired with deep learning capabilities eventually builds up a robust knowledge of the best ways to react and help someone in a given situation. It’s strikingly similar to how humans learn, just without the human error.

Google used its own voice-powered digital assistant/search tool Google Now to help improve the accuracy of its own voice recognition capabilities. By collecting millions of successful and failed voice recognition snippets, identifying common errors, and gaining a deeper understanding of subtle dialect differences, Google was able to make huge improvements to its voice search capabilities

 

Finding your own way with AI and Machine Learning

Ultimately, what you can get from AI and machine learning will depend on what your business does. They’re great at improving operations, but it’s up to you to decide exactly how you want them to do that.

To help get your ideas flowing, here are a few common ways we’ve seen businesses putting AI and machine learning to use:

  • Improving the quality of customer experiences by intelligently anticipating customer needs and providing personalized service
  • Protecting against fraudulent requests or malicious activity by analyzing transactions in real time
  • Increasing sales and improving marketing through deeper understanding of customer preference and behavior
  • Putting the right information in front of the right people at the right time—both customers and employees

 

Better learning. Smarter business.

Perhaps the most exciting change that the rise of machine learning represents is that learning is finally becoming an “always-on” part of our working lives. With very little human effort, we can gain exceptionally deep knowledge of just about anything.

It’s what business intelligence was always meant to be—the business, learning for itself, and using that information to make operations smarter, leaner, and more efficient for everyone, in real-time.

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