HR tech is consolidating, the AI arms race is overheating, and job boards are feeling the strain. A top WorkTech analyst shares what’s coming in 2026.
If there’s one thing we know about the HR tech market, it’s that it doesn’t care for anyone’s five-year plan. It’s consolidating faster than most TA leaders expected, and AI is crashing into every part of the hiring process. The platforms you’ve relied on for years are suddenly having to prove they still deserve a place in your stack.
George LaRocque, founder of WorkTech, doesn’t pull his punches on this topic. When we brought him into our December roundtable on WorkTech predictions for 2026, he came with hard truths and a few insights that might make you rethink your tech-stack strategy. Here’s what every talent acquisition leader needs to know right now.
HR Technology is in a Significant Consolidation Cycle
Last year, LaRocque predicted that we’d see major consolidation in the HR tech market, with at least one big HCM platform acquiring a frontline, high-volume hiring solution and triggering a wave of follow-on deals. That’s exactly what happened when Workday bought Paradox and SAP moved on SmartRecruiters. Those acquisitions pulled tools built for high‑volume hiring and modern automation directly into the big suites, instead of leaving them as separate point solutions.
Consolidation landed there first is that vendors go where the money is. High‑volume hiring is notoriously inefficient and burns a disproportionate share of TA budgets for relatively fragile results. If a product can shave even a little bit of friction or cost out of that process, there’s a very clear story to tell on ROI.
What this means for 2026: For vendors, consolidations like these look like ordinary market maturity. For TA leaders, they signal that the suites now want to own the most expensive, high‑volume parts of hiring where ad spend and automation have the clearest payoff. That shift matters in 2026, because it changes your options. The point solutions you love may end up embedded in platforms with new offers and pricing, and your ability to swap tools in and out will narrow. If your biggest headaches are in high‑volume hiring, you could be deciding which ecosystem you’re willing to be locked into for the next few planning cycles.
“When you think about the high-volume hiring process, it’s incredibly inefficient. There’s a lot of transactions that need to be tracked or automated; a lot of wasted advertising spend. If you can solve any of those problems, there’s a clear line of sight to ROI.” – George LaRocque
All the Money’s Flowing to AI
If you’re a startup trying to raise money without AI at the core of your pitch, good luck. Investors now expect new work tech products to be AI‑native, and anything that looks like “just another tool” in an existing category struggles to get past the first conversation. Incumbent platforms are faring a little better, since they can bolt AI onto existing products and frame the new features as a natural evolution to attract capital.
The numbers are painting a clear picture. HR tech funding passed $6 billion in 2025 and moved toward the frenzied peaks of 2021 and 2022, but venture capital is concentrating in fewer, bigger deals. Established players like Ashby, Loxo and Mercor are raising rounds in the tens or hundreds of millions; meanwhile early‑stage startups are finding it much harder to get attention unless they’re genuinely rethinking how a category works, not just building the next ATS.
There’s still innovation in other parts of HR, including payroll and adjacent systems. But even there, new TA tools without a credible AI angle rarely get funded, marketed or bought. And for products that do get built, having AI on the label doesn’t guarantee adoption. Categories like interview intelligence have grabbed a lot of venture capital, and teams seem to like the features in pilot projects. But those trials don’t always turn into subscriptions because the tools don’t solve a problem that feels big enough to justify a new line item.
What this means for 2026: First, it means that you won’t see as many shiny new tools flooding the market. Most of the innovation will come from well‑funded incumbents and platforms that already own your data. Second, you’ll keep feeling pressure to buy AI‑branded features — but you must put in the work to make sure you’re picking the tools that move a business metric you care about, and saying no to the rest.
“VCs are skittish right now based on what’s happening in the job market, what’s happening happening in the economy. What’s happening is fewer deals, but bigger deals…You’ve got to be rethinking the apply path, rethinking sourcing, rethinking matching, rethinking assessments, rethinking any category where you’d put a tech tool. It can’t just be another version of what we’ve already seen; it has to be something new. That’s what investors tell me they’re looking for.” – George LaRocque
AI in the Funnel Is Forcing Better Verification and Explainability
This year, the bots started talking to the bots about who should get hired. Candidates began using AI to spin up tailored — and sometimes misleading — resumes and apply for jobs en masse, and the pressure nudged more employers to switch on AI at the screening stage, even when the legal and ethical risks make people uncomfortable. It’s now entirely possible for an AI‑written resume to be scored and ranked by an AI‑powered screening tool before a human sees anything. No wonder application volumes feel out of control and candidate fraud is creeping up in the background.
Vendors are already responding with verification and validation tech to verify that the person in front of you can actually do the work they say they can do, and catch bad actors without shutting everyone else out. Multiple layers of verification will become the norm. LaRocque compared it to Swiss cheese: “Every layer of verification and validation you have in this process, it’s like Swiss cheese. There’s holes. So if you just have one layer, the holes are easy to get through, but you’ve got to layer them and sort of diminish the holes so that you have better odds.”
All of this is landing in a market that was built on compliance. Employers have spent years documenting their hiring decisions and defending their selection criteria. As AI takes on more of the ranking and routing work, explainability becomes the real test of whether a tool is safe to use. Some tools are clear about what they looked at and leave humans in charge of the final call; others hand you a ranked list of candidates with no real story about how they got there, and no easy way to defend those choices if someone asks you to prove it. That’s a lawsuit waiting to happen.
What this means for 2026: Explanability is a risk problem – you’ll need to be clear on where AI sits in your process, where it’s making actual decisions, and how you’ll explain those decisions if a regulator or lawyer comes calling. That probably means asking different questions in demos: not just “what does it automate?” but “what does it decide, what does it show me, does it use numerical scoring that could create downstream compliance issues, what can I prove later?”
“Any leader looking at these tools needs to be able to explain how decisions were made and why they were made; if the tech can’t help you do that, you’re taking on risk you probably don’t want.” – George LaRocque
Vertical Solutions Are Pulling Ahead
In LaRocque’s view, horizontal tools that try to be all things to all employers are running out of road. Next year’s winners will be the big platforms and niche providers. The platforms succeed because they already control much of the data that powers AI and automation, which makes it easier for them to roll out “smart” features quickly. Niche providers succeed because they go deep in one industry, labor type, or job family.
Healthcare is a good example. Every role comes with specific credential checks, and you have to treat a traveling nurse very differently from someone you’re hiring into a permanent role. A vendor that understands that reality and builds around it will usually beat a generic sourcing or matching tool when it comes to finding, qualifying, and moving the right candidates.
What this means for 2026: If this trend holds, we’ll see TA teams leaning harder into fewer, but better‑fitting, tools that are built for their world. Pick the platforms you’re willing to bet on for the long term, then leave room in your stack for a small number of vertical solutions that solve hard, specific problems your generic tools never quite touch.
“The more focused a solution is on a specific industry, labor type, or job type, the more likely it is to deliver real value compared to another generic tool in the same category.” – George LaRocque
A Slow, Uncomfortable Turn for Indeed?
Two big shifts are coming that most talent leaders are still underestimating: how candidates find jobs, and how much power the big job boards really have over your funnel. The short version? AI will sit between you and your candidates more often, and the biggest incumbents may not be as untouchable as they look.
Candidates are already using AI assistants like ChatGPT and Perplexity to search for jobs in very specific ways, and they’re starting to see AI‑generated summaries and recommendations before they ever hit a job board or career site. That quiet shift in behavior will steadily drain traffic away from traditional job boards over the next few years and, in that world, job boards will need to think of themselves as marketplaces serving candidates if they want to survive. Brand matters here. What promises are job boards making to their candidate customers? What value do they deliver – tools, learning, training, coaching – beyond just connecting candidates to a job posting?
LaRocque also raised an uncomfortable question: Could 2026 be the year Indeed starts down the same slow, painful arc as Monster? He’s watched Indeed make mistakes with employer customers and implement application and pricing constraints that frustrate the market. Nothing terrible has happened yet, but the cracks are showing.
What this means for 2026: Those cracks only really matter once the market turns and teams feel confident enough to experiment elsewhere. When hiring demand normalizes, that’s when we’ll see innovation. Both candidates and employers will move faster toward new ways of discovering and engaging with each other, and the platforms that refuse to loosen their grip will be the ones that feel the pain.
What TA Leaders Should Do Right Now
As we move into the new year, the work for TA leaders is to stop trying to throw AI at everything and get ruthless about their priorities. Where are the biggest leaks in your funnel, the worst inefficiencies, the clearest, most defensible ROI? Align that list with your business leaders so you are solving the problems they already care about, in the language they actually use. Do they need quantitative results, qualitative improvements, or both? Where is the pain in the business, and how can talent acquisition move it? That’s where you start.
Looking into 2026, that discipline is what will separate teams that make smart tech investments from those that do not. Consolidation, verticalization, and AI sprawl are all real, but you cannot chase everything; you need a clear view of where your process is genuinely different and where it looks like everyone else’s, then invest accordingly. Pick a few high‑impact problems, line them up with what the business values most, prove ROI there, and use that credibility to take bigger swings as the market and the tech continue to evolve.
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