Artificial intelligence and machine learning (AI/ML) will move out of the shadows and into the mainstream in the 2020s.
AT DMI, we’re already seeing these forces at work in our engagements with enterprise clients. Increasingly, B2B companies are putting learning algorithms to work to streamline operations and develop predictive capability. Chatbots and other conversational AI technologies are getting more sophisticated, opening up new avenues for improving customer service. While these trends have transformative potential, they also pose thorny ethical questions that cannot be ignored.
Here’s a quick look at three of these factors.
AI/ML is moving into the B2B space in a big way. Retailers are using mobile apps, image recognition and robotic-process automation to streamline transactions and improve efficiencies in the storefront and the distribution center. As more consumers shop online but pick up their products in stores, retailers are turning to back-office AI to upgrade their supply chains and inventory controls to ensure these hybrid transactions don’t leave buyers empty-handed.
Intelligent bots also can track in-store traffic patterns to help retailers optimize their store layout and streamline service and checkout. In the automotive sector, back-office AI can help companies improve the driving experience and help dealers deliver offers to the customers most likely to want them. In the world of finance, AI is making it easier to develop more accurate assessments of credit risk and merger/acquisition potential.
Siri and Alexa were early chapters in the story of natural language processing. In the new decade, conversational AI will broaden its appeal in multiple sectors.
In healthcare, chatbots will increasingly know how to identify users and help them navigate to information they need right away. That can put patients in the driver’s seat — letting them decide whether to wait a half-hour to talk to a human or to read a few articles or support threads that solve their problems. Government agencies also will be keen to adopt these tools to bolster constituent services.
Companies like banks and consumer brokerages, meanwhile, will use more chatbots to help customers select investment vehicles, balance portfolios and map out their financial futures.
The accelerating pace of AI technologies creates vast potential but also must confront questions only human can answer.
Consider the possibility of an AI engine predicting the success or failure of a clinical trial. This raises a host of issues in the underlying modeling. How accurate is the data? How trustworthy are the recommendations? It’s no exaggeration to say these are life-or-death challenges.
AI is also enabling sophisticated data-tracking sensors that follow people’s actions and predict their behaviors. Should AI applications secure people’s consent before conducting these scans?
The problems of black-box AI — where users can’t be sure why a bot decides to act — require companies to develop traceability and clarity on the mechanisms driving AI bots. Failing to account for these kinds of challenges could be the one roadblock to the progress of AI adoption.
Moving Ahead with AI/ML
Though advanced automation has raised enthusiasm and unease in equal parts in recent years, inroads in the B2B sector reflect growing acceptance of these next-gen technologies.
At DMI, we’re seeing these trends across the major sectors we serve — automotive, financial, healthcare, government and retail. And we’re helping companies find the best way to adopt transformative algorithms while staying true to their values and their customers.
The coming decade will test everybody’s ability to cede a measure of control to machines while leaving ultimate authority in the hands of humans. Our experience with machine intelligence gives us the grounding to help clients find thoughtful, humane ways to strike that balance.
— Venkat Swaminathan, director, data analytics and artificial intelligence
— Niraj Patel, senior vice president, artificial intelligence