Why You Must Master Your Data Before You Master AI
Growing up, I’ve always been fascinated by science-fiction films. From Blade Runner to The Terminator, these movies hauntingly depicted futuristic worlds shaped by technological innovations that gave rise to advanced machine learning and astonishing examples of artificial intelligence (AI). These flicks really stirred my imagination and sparked my interest in technology. Today, AI has rapidly evolved from fiction to reality. But instead of doomsday scenarios with humanity cowering at the feet of our robot overlords, AI has led to some amazing advances in everything from healthcare and security to transportation and education. Nevertheless, super smart folks like Stephen Hawking and Elon Musk still warn of the coming AI apocalypse. In fact, Elon Musk’s new company, Neuralink, aims to stop a Terminator-style attack by fusing man and AI through brain links.
Potential apocalypse aside, AI is also being embraced by the marketing community – and for good reason. The complex algorithms that make up the backbone of AI technology are being used to improve the effectiveness of advertising, streamline interactions with customers, and accelerate the efficiency of sales. In just the past few years, several tech titans have introduced AI-powered platforms and services. IBM made a big splash with the introduction of Watson, Salesforce invested billions in Einstein, and Adobe launched Sensei. Sense a pattern here? While each of these product names are designed to elicit thoughts of deep “intellect” and “wisdom,” the heart of AI is, of course, data and not necessarily the complex algorithms that distinguish one AI product from another. After all, AI is only as intelligent as the data that feeds it.
While the AI algorithm story is all the rage, the data narrative is not as prominently discussed. Sure, data may not be as sexy as the cleverly branded automated systems that can learn and process information quicker than a human, but it is equally as important. And don’t get me wrong, everyone knows that AI requires vast amounts of data to continually learn and identify patterns that humans can’t. After all, it’s the ability to process this information and make instant decisions that has led to AI being such a game changer for industries that rely on massive volumes of data.
But the real story is not about the algorithms powering the AI revolution, instead it’s about the quality of data powering these systems. We can’t ignore the fact that we have a serious data problem.
Be honest, how confident are you in the data you’re using to make crucial business decisions? Chances are you recognize most of your data is inaccurate and likely missing essential information. It’s an unfortunate reality that’s effecting countless organizations every day. In fact, according to new research, year-over-year, the current state of data quality has remained “questionable” at best – declining slightly by 10%. What’s more, nearly 1 in 4 marketers lack confidence in the quality of their customer and prospect data within their sales systems, while 40% of marketers don't feel as though their sales teams have the right account intelligence to engage with prospects.
Despite these concerns, marketers continue to build powerful algorithms to fuel their AI systems, seemingly ignoring the fact that no matter how sophisticated the technology is, it will never live up to its full potential until the data is reliable. After all, artificial intelligence is, at its core, artificial. It will do its job based on what its told, whether that information is accurate or not.
This makes me think back to one of my favorite sci-fi films, The Terminator. It’s famous for portraying a dystopian society with artificially intelligent robots hell-bent on the destruction of the human species, not to mention some catchy one-liners from future California governor, Arnold Schwarzenegger. In the movie, the T-800 Model 101 Terminator, a highly-advanced robot with living tissue over a metal endoskeleton, is programmed to find and kill our hero, Sarah Connor. But the machine does not know which Sarah Connor to target. The only data it has is her name the city she lives in. Not knowing exactly who the main target is, The Terminator goes though the phone book (remember those?), dispatching all the Sarah Connors on the list. Being that this is a 90-minute movie, The Terminator intercepts the intended Connor rather quickly and spends the rest of the movie blowing things up with the intention of terminating her.
So, as advanced and intelligent as The Terminator is, it essentially must guess which Sarah Connor to target because it lacks important basic, foundational data. So, AI, whether it’s a homicidal cyborg or customer chatbot, needs the right data to make intelligent decisions from the outset. There’s also no substitute for human interaction and analysis. Our ability to evaluate the accuracy of the data we use and supply to these AI systems will ultimately help make them smarter over time.
What enterprises really need as they develop their AI strategy is to integrate, clean, link, and supplement their data so they have an accurate database on which to build their algorithms. This starts with foundational master data.
You’re going to hear a lot more about master data over the next few months as companies recognize that master data is the most important data they have. Master data is the foundational information on customers, vendors and prospects that must be shared across all internal systems, applications, and processes in order for your commercial data, transactional reporting, and business activity to be cleaned, linked, optimized and made accurate. It’s essentially the foundation of your enterprise and without it not only does your AI infrastructure breakdown, but so does your business.
I’m going to be discussing more about how marketing can take advantage of master data. In the meantime, this article is a great starting point to get familiar with what will be marketing’s next hot topic.