Analyst Perspectives

Compensation data is everywhere. Internal equity metrics, market benchmarks, performance history, pay transparency requirements—there’s no shortage of data coming in from every direction. But volume does not always guarantee clarity. It is not about the data your system can collect, it is about whether that system—and the people behind it—can turn the data into decisions that actually make sense. That is what it means for your compensation tech to speak the right language.

Frontline work is being reshaped from every direction: tighter labor pools, unpredictable demand and a workforce that expects more than just a paycheck. Yet too many organizations are still treating workforce scheduling like a game of Tetris—moving blocks around and hoping they fit. It’s time to admit that smart scheduling isn’t just a nice-to-have—it’s a frontline imperative. And if the enterprise is still thinking of it as “just logistics,” it's already falling behind.

One of the key questions that will need to be solved if agentic artificial intelligence is to fulfill its potential is which technologies and providers will serve the role of orchestrating communication and integration between the various models, applications and data repositories involved. ISG Research defines agentic AI as software designed to execute business processes through autonomous actions, potentially controlling multiple processes and systems through the orchestration of one or more...

The learning management system (LMS) market is evolving, with the lines that once rigidly defined categories becoming increasingly blurred. Today, an LMS that lacks Learning Experience Platform (LXP) capabilities risks becoming obsolete in an environment where user expectations are shifting rapidly. In a similar vein, an LMS and LXP that fail to harness the power of artificial intelligence (AI) to guide learners through their diverse learning journeys face a similar fate.

If a single phrase could sum up the big data craze of a dozen or so years ago, it would be “more data beats better algorithms.” Attributed to Google research director Peter Norvig, the quote effectively summarized a research paper Norvig jointly authored called The Unreasonable Effectiveness of Data and was embraced by big data enthusiasts as articulating the prevalent thinking that enterprises with the largest volumes of data have an advantage over rivals. The phrase was, of course, an...