Introducing AI into the Enterprise


Contact centers that understand the tremendous benefits to be had from advanced analytics will likely be the same ones that lead the pack in introducing Artificial Intelligence into the contact center. How could it be any other way? The likelihood of introducing AI is all about innovative culture, realizing the value of data and the conclusions you can draw from it, ease of data integration with legacy systems, etc. These driving principles apply whether using AI or just advanced analytics.

Despite the hype, few organizations are using true machine learning in a meaningful way, but many are using business rules to mimic human intelligence, often as part of algorithms embedded in software, but increasingly in a centralized way, such as in decision engines that can store rules to take action based on analysis of historical patterns and optimal responses. Whatever the decision-making model, there’s a universal axiom we can count on: more data equals better decisions. For example, if you were going to automate the issuance of overtime and voluntary time-off notices to agents, you could do it based solely on WFM forecasted demand for staff vs. actual staffing plan. If you also had detailed information about the skill sets of your agents, you could send the notices only to those staff members that are appropriately skilled. If you had additional information about the preferences of individual agents regarding the time windows during which they are interested in receiving these notifications, you would only send notifications to the appropriately skilled agents during their preferred time windows. The latter is exactly what Aspect does in its Workforce AI solution. Knowledge is power, and more data equals better decisions.

In companies that take analytics seriously, there’s already a pervasive understanding and set of expectations about the power of analytical tools. This naturally stimulates a thirst for better data access to existing systems and deeper integrations that allow analytics to take action, such as in the case of automated notifications about overtime and voluntary time-off. This same broad data access and deeper integrations create an infrastructure in which AI can flourish.