Many people I talk to—especially those in the C-suite—are excited about artificial intelligence (AI), and machine learning (ML) in particular. However, they’re a little fuzzy on exactly how it can help them. There’s a lot of information flying around about AI and ML, but much of it is contradictory, and it’s hard to discern the truth from the hype.
AI and ML will revolutionize the way you do business in the future—in ways we can’t imagine now. In this blog, we’ll take a look at some potential uses of AI/ML in finance, retail, and manufacturing/supply chain. My guess is you’ll find something that applies to you, and my hope is that it will incent you to get started with your own journey to optimize your own business.
The Future of AI and ML in Finance and Insurance
Soon, instead of chatting with a customer service representative, you’ll chat with a bot that has natural language processing capabilities and is armed with tons of customer specific interaction data—and that will mimic the human-to-human chatting capabilities available today. You’ll be able to ask the bot questions such as, “How much did my 401k gain/lose last year?” or “What’s the outstanding balance on my credit card?” Bots won’t replace humans, but humans will be freed up to handle more complex cases.
AI and ML will also enhance security and market analysis capabilities. Biometric data such as face, voice, or even retinal recognition will become the norm for security measures. And, investment banks and hedge funds will use AI and ML to perform deep analysis to better understand the human and social factors that influence markets and use that sentiment analysis to optimize decision-making.
AI and ML in Retail
In the next half decade, retailers will use AI and ML to make predictions about inventory needs and adjust levels in real time. These systems will make suggestions to store managers about which items to order, and in some cases, companies may enable them to make purchases without human intervention.
Product placement will also get a boost from AI. Gaze detection technologies will be used to analyze customer interest and place products in ways that optimize foot traffic patterns and visual attention. These systems will also analyze that foot traffic and direct product placement based on not just seasonal, but demographic trends such as age, gender, etc. Think: older women tend to shop on Thursday, so we’ll put products of interest to them in high-traffic areas.
Another obvious trend for AI/ML augmentation will be in loss prevention. Detection of customers (and employees) exhibiting suspicious behavior will be made easier by algorithms that leverage big data to better understand behavior patterns. Much care is needed here, however, to scrupulously avoid profiling behavior at all costs.
AI and ML in Manufacturing/Supply Chain
Over the next five to ten years, AI and ML will also revolutionize the business for large logistics companies and manufacturers. AI and ML will be used to eliminate many manual processes now handled by humans: invoice exception tracking, responses to inquiries, purchase order corrections, etc. Think of how much this could free up employees to engage in productive tasks.
Other leading companies will use chat bots (see finance above) to engage with suppliers in routine communications, place purchase orders, monitor regulatory compliance vis-à-vis materials, and to keep up with the voluminous documentation that often bedevils—and slows down—logistics operations.
Another obvious application of AI/ML (and one that syncs well with retail) that will become prevalent is inventory forecasting—correlating supply with demand and optimizing decision-making processes with intelligent algorithms and ML augmented analysis of big data.
The Future is Now
Many AI/ML applications I’ve discussed are only one to five years out on the horizon—the blink of an eye. Get ready, because the future is coming. Humans won’t be replaced, but our capabilities will be greatly enhanced by AI/ML. Companies that use AI/ML to enhance their processes will improve their top and bottom-line revenues and grow at rates that outperform the competition. Those that don’t, well…