In MDM’s July 31st webcast How Artificial Intelligence Disrupts Distribution: What You Must Know, Ian Heller, MDM President & COO, and Tony Corley, Senior Product Marketing Manager at Epicor, discussed one of the most pressing, and most complex, issues currently facing distributors: artificial intelligence, or AI.

The actor Stephen Fry, during his time as host of the popular British quiz show “Q.I.”, told a story about when motor cars were first introduced to Pennsylvania. A farmer's group, deeply resistant to the new-fangled, noisy machines, proposed state legislation to require cars travelling at night to send up a rocket every mile and then wait 10 minutes for the road to clear. If a team of horses approached, drivers would be required to stop, pull over, and cover the car with a blanket or dust cover painted to blend into the scenery. If the horses were unwilling to pass, drivers would be required to take the car apart and conceal the parts in the bushes.

Anyone who’s taken the I-76 through Harrisburg can tell you how that one went.  

The story, while it seems outlandish today, retains a contemporary point. Technology isn’t going to go away, so better to get on board than resist. AI, despite its long association with science fiction and the future, is now very definitely part of the here and now, and to ignore it is to run the risk of your business being left stranded by nimbler, more tech-savvy competitors. 

So, to reference the webcast title, what are the most important things about AI that distributors need to know? 

The first and perhaps the most crucial thing to know may be the importance of embracing the new reality, no matter how much discomfort or disruption to traditional business processes it may cause in the short term. If you haven’t yet done so, however, you’re not alone. As Ian mentioned, a review of the 10-Ks of publicly held distributors show that for most, spending on R&D remains negligible. Meanwhile, that of Amazon, a fast-growing presence in distribution, is according to one report the largest in the U.S. and perhaps the world.

The next step is to familiarize yourself with some essentials about AI, what drives it, and its value for your business. There are four different types: 

• Perceptual AI, in which the technology responds to some form of input, such as speech or images; 
• Internet AI, which most people who access websites will already be familiar with, and which is responsible for those lists of products that the site recommends to you based on your past preferences and purchases; 
• Business AI, which makes business decisions, such as triggering an inventory replenishment when stock levels fall below a defined threshold; and
• Autonomous AI, which tends to hog all the media attention and includes autonomous robots, self-driving cars, and machines that communicate with each other (and may, Terminator-style, eventually become our overlords). 

AI is driven by what is known as “big data”, vast repositories of information that are growing ever larger in sync with computational power and that due to sheer size are not dependent on traditional analytical norms like small, representative samples. The overall size, per Ian, overwhelms any messiness that’s in the data. In addition to the business intelligence it provides, data often turns out to have uses outside of the original intent. For example, smartphone-based traffic apps were designed to ping cell phone towers to guide you from where you are to where you’re going, but it turned out that the rate at which the pings travel from tower to tower also alerts the system (and you) to traffic slowdowns, a huge bonus that was not part of the original intent. Businesses can likewise creatively use data to drive innovation in ways they may not have thought of.

To those without a natural affinity for data or technology, it can be comforting to bear in mind that it’s not necessary, or even the best approach, to try and rapidly ramp up from having little or no AI component to the kind of next-gen analytics capabilities of Amazon Business. Smaller and mid-sized companies have no need of most of these, and there is no one-size-fits-all method. A better approach is to research which components of your unique business can be enhanced by AI and data analysis and then integrate those. In fact, at least in the early stages, it may not be even necessary to make any financial outlay – the technologies that you currently use, such as a standard CRM system, may include data-gathering features that are a good place to start.

Whatever your approach, the bottom line is to engage with the subject, and to do so sooner rather than later. Resistance is futile, as the Borg put it. And they’re no strangers to AI.