HR Technology & Outsourcing Solutions

In an earlier Analyst Perspective, I discussed data democratization’s role in creating a data-driven enterprise agenda. Building a foundation of self-service data discovery, data-driven organizations provide more workers with the ability to analyze and use data. I’ve also examined how generative artificial intelligence (GenAI) could revolutionize business intelligence software by using natural language interfaces to lower the barriers to working with analytics software. Today, however, data democratization ensures that access is not limited to analytics software. Users in different roles should be able to use data through whatever applications or tools best align with their business workflow and objectives. This is the driver behind growing interest in a new category of products that enable headless BI.

For years, HR technology has been seen primarily as an administrative tool—handling records, payroll and compliance. But what if its real power lies in shaping workforce strategy, building community and driving transformation?

There are contact centers, and there is customer experience. They are not the same thing, even though we have a tendency to conflate them or at least discuss them in tandem for operational and planning purposes. This is mostly fine, but it does obscure one basic difference that will matter more as enterprises succeed at integrating contact centers into enterprise CX strategies. That difference is in metrics and, by extension, how we define success.

AI, like analytics, must lead to action. Too often, in both cases, too much of the exercise is left to the reader. We have tools to provide sophisticated analyses, including AI platforms that can be used to predict many types of behavior, but we fall short in helping the workforce know what to do with that information. Some examples are more obvious, such as fraud detection. If a transaction is predicted to be fraudulent, the transaction should be blocked. But even this example is not as cut and dry as you might think. I’m sure many of you have been frustrated standing at a hotel check-in desk or at a retail counter attempting to make a purchase when your credit card transaction has been denied. What is the appropriate action or set of actions that should be taken?

Agents and “agentic AI” are all the rage now, eclipsing last year’s focus on artificial intelligence (AI) and generative AI (GenAI). They are a way to automate work almost effortlessly so that repetitive and boring tasks get done with the least amount of effort and perhaps, more consistently. In business software, a broad range of software providers are claiming agents to be a panacea that can improve performance and lower costs. They are alluring, with an almost unlimited number of potential use cases. Agents are an important evolutionary step in the design of business software, similar to the transition from procedural programming to event-driven programming that accelerated in the late 1980s. That paradigm shift enabled business software to be more flexible and responsive in replicating how work is performed. Adding agents to the considerable body of well-developed business applications will take the capabilities of these applications to the next level.