The Trillion Dollar AI & Machine Learning Use-Case You’ve Never Heard Of
I recently saw a great video of a panel moderated by my friend and ex-colleague Nadim Hussain from Salesforce.com in the MarTech track of TieCon 2017, titled “7 Use-cases of AI & Machine Learning”1.American businesses and consumers spend approximately $1 trillion every year on assets they already ownClick To Tweet
Coincidentally, I also saw a Huffington Post article about “3 Real Use-cases of Machine Learning in Business Applications” featuring my friend Abhishek Kashyap’s company MarianaIQ2. Both were great pieces and certainly topical. But it underscored for me that there is at least one use-case of ML & AI that no one is talking about. And it’s all the more astounding, because it addresses a Trillion dollar opportunity.
Yes, I’m talking about the use-case Entytle addresses for our manufacturing customers. Our B2B industrial manufacturers have a huge “installed base” of customers world-wide. These customers need parts and services. It just happens that the Aftermarket is about 10x of original equipment sales3. So you’d think that the manufacturers would be awash with fancy AI and machine learning tools and technologies to help them grow their Aftermarket revenues. After all, everything from lead-scoring to car-sharing to vacation-rentals have been disrupted through AI.
Alas, manufacturing aftermarket remains the last hold-out against AI. That’s not by design, but it’s really just a function of the fact that manufacturing is so far removed from Silicon Valley and is so vastly underserved by technology vendors. The state of the art at many of our customers is still Microsoft Excel and if they’re lucky, a legacy CRM system. AI remains a pipe dream. But not for long. We at Entytle are squarely focused on manufacturing, and our AI and Machine Learning is slowly but surely changing the way large manufacturers look at their Aftermarket – and how they think about driving Aftermarket revenue growth.
1. 7 Use-cases of AI & Machine Learning (YouTube)
2. 3 Real Use-cases of Machine Learning in Business Applications (Huffington Post)
3. Winning in the Aftermarket (Harvard Business Review)