People often ask if I’ve heard of this HR tool or that recruiting platform. Most of the time, I have. The conversation has shifted dramatically over the past few years though. It used to be about whether a tool could automate a task. Now it’s about whether a tool can actually think alongside your team, and whether you’re set up to take advantage of it when it can.

I’ve been an early adopter of HR and recruiting technology for most of my career, across nearly every company I’ve worked with. That experience has given me a pretty clear sense of what separates tools that genuinely move the needle from tools that just add another tab to your browser.

The bar has changed

For a long time, “good” HR tech meant a system that sent the right email at the right time, tracked candidates through stages, and kept your data clean. That was the baseline. Today, that’s table stakes.

The tools that matter now are the ones that connect dots your team doesn’t have time to connect manually. Picture a recruiter who can see, at a glance, that a candidate they sourced six months ago just updated their LinkedIn profile, visited your careers page twice this week, and has a first-degree connection with a hiring manager on the team they’d be joining. That isn’t science fiction. Tools like that exist, and when teams are trained to use them well, recruiting shifts from reactive to genuinely proactive.

AI in the stack: where it actually earns its keep

AI has made its way into almost every corner of the HR tech landscape. Resume screening, candidate matching, interview scheduling, sentiment analysis, workforce planning, comp benchmarking. Some of it is impressive. Some of it is repackaged automation with a new label and a higher price tag.

Here’s where I’ve landed on it: AI works best in HR when it handles the high-volume, repetitive work so your team can focus on the high-judgment work. Sourcing candidates at scale, flagging engagement signals, drafting job descriptions, surfacing flight risk indicators before someone hands in their notice. These are areas where AI adds real value right now, and the gap between teams using these tools well and teams not using them at all is widening fast.

But there’s a deeper version of this conversation that most companies aren’t having yet. The teams getting the most out of AI right now aren’t just adding tools to their existing processes. They’re rebuilding the processes around what AI makes possible. That distinction matters. Adding an AI screening tool to your existing hiring funnel will speed things up. Rebuilding your hiring funnel around always-on, AI-curated talent pools tied to workforce planning forecasts is a different kind of change, and it produces a different kind of result.

Most companies are still in the first category. The ones moving into the second are pulling ahead in ways that’ll be hard to catch up to.

The question I ask is no longer “are you using AI?” It’s “do you know where AI is helping, where it’s getting in the way, and where it’s quietly making the case that the process itself needs to be redesigned?”

Stack size isn’t the point

Whether you have six integrated tools covering the full recruiting-to-employee lifecycle or two essential systems held together with a solid process, what matters is whether your stack is actually working for your team. A bloated tech stack with poor adoption is worse than a lean one that people actually use.

The best HR tech setups I’ve seen share a few things in common. The tools talk to each other. The data is trusted. The right people can see the right information without digging for it. And the team has been genuinely trained on how to get the most out of what they have, not just onboarded to it. That last one is where most companies underinvest, and it’s usually the difference between a stack that works and a stack that frustrates everyone.

Looking ahead

The next frontier in HR tech is predictive and personalized. Tools that can anticipate hiring needs based on business signals, flag retention risks at the individual level, help managers have better conversations with their people based on real data, and free People teams from the reporting work that has historically eaten so much of their time.

We’re already seeing great early versions of all of this, and it’s only getting more sophisticated. The organizations that will benefit most are the ones building strong data foundations now, choosing tools with intention, and pairing the technology with the human judgment no platform can replicate.

If you’re thinking about evaluating or rebuilding your HR tech stack, I’d love to talk through it. The right stack looks different for every organization, and figuring out what “right” means for yours is one of my favorite problems to dig into.