If there’s one key message for HR leaders to consider as we step into a new year, it’s this: 2026 is the year artificial intelligence (AI) hype turns into practical, agentic AI reality—technology that reduces complexity and drives down cost. At the same time, employees will expect experiences that feel more personal and frictionless, as the technology gets increasingly better at predicting what people need.
Given the swinging economic pendulum HR has navigated for decades, that convergence of cost efficiency and experience matters. When the economy is thriving, the focus shifts toward attraction and retention. When the economy cools, the focus swings hard toward cost containment. In 2026, I believe we will start to enter an environment where both pressures can be addressed simultaneously, largely because new tools make it possible.
Predictions for 2026
Here are my predictions that HR teams, employers, and brokers should keep top of mind as they plan for 2026.
- The HR tech experience starts to catch up to consumer tech.
Employees know what “easy” looks and feels like. ChatGPT alone had 800 million weekly active users as of November 2025, doubling since February 2025. The workforce is regularly interacting with tools that are intuitive, tailored to their preferences, and fast. Historically, that standard has not carried over into HR technology. There’s been a gap between consumer expectations and HR experiences that people used to tolerate because they didn’t have a better alternative.
That tolerance is already eroding. When people can type a question into a tool in their everyday life and get a clear answer in seconds, navigating through SharePoint folders to find information buried deep in PDFs feels too cumbersome. In 2026, the organizations that raise the bar on HR and benefits experiences will stand out. Others will feel dated, even if they claim to be “using AI.”
- Virtual assistants become the new front door, and interoperability matters.
Much of what people call “AI in HR” will end up being virtual assistants, but the bigger change is where those assistants live. Employees shouldn’t have to hunt for links, portals, and logins just to get a basic answer. The better model is meeting people where they already spend time, like Slack or Microsoft Teams—bringing answers seamlessly into their flow of work and creating experiences that feel intuitive, not disjointed.
I also expect more interoperability, where HR, benefits, and point solutions can connect into experiences that feel unified to the employee. There will still be complex algorithms behind the scenes, but the front-end experience has to be simple or it won’t get used.
- The biggest misstep will be AI that is half-baked or “AI for AI’s sake.”
There’s plenty of AI-washing sweeping through the industry. Old technology wrapped in new language does not create a better experience. Even worse, rushed AI features can create lasting skepticism.
Let’s say an implementation assistant launched at roughly 70 percent accuracy for work that is highly complex. While on the surface, this may feel like it reduces effort significantly, in practice, the human operator is left spending more time finding what the AI missed. Or worse, correcting what it got wrong. That kind of experience can make buyers pull back and say, “This tech is not fully baked yet. I’ll wait a year.” It raises the bar for everyone else who is trying to launch AI thoughtfully. If you are going to introduce AI into high-stakes HR workflows, you need to be serious about quality and accuracy, because the cost of getting it wrong is loss of trust.
The alternative is using AI with intention that delivers high-confidence outcomes, and designing it as decision support that helps people who are not experts make smarter choices.
- We start onboarding fleets of agents alongside groups of new hires.
In 2026, we’ll see the start of a transition: Onboarding AI agents becomes an operational reality. That does not mean entry-level work disappears. Rather, this allows new entrants to the workforce to be the first truly AI-native knowledge workers. With new skill sets focused on managing human-agent collaborative workflows.
Where someone used to do “fingers on keyboard” work, such as any data entry, that work becomes automated, and the person’s role shifts toward managing a fleet of agents, monitoring outcomes, and providing feedback to improve AI outcomes continuously over time. That human-in-the-loop model will matter a lot in HR, as HR buyers tend to be risk-averse. Many do not want AI to do the entire job without oversight.
This is one of the most practical ways AI changes work without creating a hollowed-out talent pipeline; a kind of collaboration between people and technology will define the next chapter of work—where AI amplifies human impact instead of diminishing it.
- Cost containment and engagement become a combined goal, not a tradeoff.
To build on the possibility of another “pendulum swing,” benefits leaders have felt forced to choose between driving engagement and controlling cost. In 2026, that could become less true. With predictive and agentic tools, HR can do more with less, and employees can be guided toward decisions and programs that improve outcomes for both sides.
Personalization will be a driving force here. If a system can use data responsibly to surface the right benefit at the right time, utilization improves. A concrete example is claims-driven nudges: If the system sees a pattern that suggests an employee would benefit from a preventative digital care program they already have access to, it can drive awareness and onboard them, improving the employee experience and health outcomes and driving down unnecessary claims costs and absenteeism over time.
- AI governance becomes table stakes before regulation catches up.
It’s unlikely that U.S. regulations regarding AI usage will concretely take shape in 2026. What I do expect is more companies setting their own standards and demanding clarity from vendors. In what may seem like a paradox, some of the most tech-forward companies currently have the strictest policies around how employee data is used to train AI systems, how AI is disclosed in decision support, and how virtual assistants operate. This abundance of caution from companies on the digital frontier is due to familiarity with the risks posed by ungoverned use of AI models.
For the next 12 months, we could expect AI governance to be a patchwork of rules and policies across HR vendors. Different legal teams will triangulate toward what they believe is responsible. Over time, you may see standardization as HR and benefits tech companies put clearer AI policies front and center, similar to privacy policies today. As AI continues to evolve, transparency and accountability will become the new hallmarks of trust—because a better experience can’t come at the cost of confidence.
What HR Should Do Now
First, HR teams need to get comfortable with AI as a tool, not as a threat. That mindset will be hard to maintain as employees’ day-to-day expectations change.
Second, think about AI through a risk lens, not only a cost lens. AI should eliminate manual, error-prone processes that have created avoidable issues for years. Automated testing, anomaly detection, and better monitoring are not flashy, but they lower risk in tangible ways.
Third, if you are going to personalize experiences, do it with transparency. HR is built on trust. A better experience cannot come at the cost of employees feeling a lack of privacy.
2026 will reward the organizations that innovate with intention—using AI to make HR and benefits simpler, more intuitive, and more reliable. Employees will notice. If the experience lags too far behind what people encounter elsewhere in their lives, frustration will rise, and it will manifest as disengagement, churn, and constant noise directed back at HR.
