Consider an employee who normally fills out his weekly time card on Thursday afternoon, because he doesn’t work most Fridays. Machine learning that’s built into a payroll application could help the app learn the individual working habits of each employee. Having learned this specific pattern, the app could ask him if he meant to fill out the time card when he goes to log out of the system Thursday. There’s no policy there: It’s a behavior pattern that machine learning can pick up on.

In fact, modern-day AI might be able to fill in the time card automatically, and present it to the employee for review and approval. That save even more time, and potentially eliminates errors. This capability, known as “auto defaulting,” could have applications for nearly every form-based application, from accounting to inventory to sales reporting.

Executives wrestle with how to take advantage of artificial intelligence capabilities. That’s especially true now that cloud computing resources have made the technology accessible to companies of all sizes. One of the fastest roads to AI payoff comes from using AI capabilities embedded in applications that your employees use every day—like that time card app.

Smart classification, smart recognition, and smart predictions. Those are three big buckets that encompass many cutting-edge AI and machine learning capabilities.

  • Smart classification involves studying both structured and unstructured data to take action based on what it means, such as to automatically identity unreliable suppliers, properly interpret complex invoices, and categorize consumers based on their current activities and past history.
  • Smart recognition looks to find anomalies in the data to find innocent errors—not-so-innocent errors. Smart recognition can help stop fraud, enforce corporate and compliance policies, and even speed financial reconciliations.
  • Smart predictions go farther, such as offering proactive advice to sales reps, making recommendations in e-commerce, or providing suggestions for service reps on how to direct a customer. Pattern-matching can come into play here, such as predicting which add-on product recommendation a customer’s most likely to buy.

Learn more in my story for Forbes, “Want A Bigger Bang From AI? Embed It Into Your Apps.”