HR and people operations teams are being asked to hire faster, onboard better and answer more employee questions without adding headcount. At the same time, new rules on automated decision-making are arriving in Europe, Canada and beyond. That leaves HR leaders with a practical question: how far should AI in HR go, how fast, and with what guardrails? How HR Leaders Are Adopting AI answers it with fresh survey data from your peers.
The report is built on responses from more than 1,000 HR and people operations decision-makers across Australia, Canada, the UK and Europe. Rippling commissioned the research, which was conducted with Datalily. It is written for HR directors, CPOs and people ops leads who need to set an AI plan for the year ahead, defend it to leadership, and stay on the right side of regulators while doing it.
Where AI in HR is delivering results, and where teams hold back
You'll see how far HR teams have actually moved with AI, from early pilots to workflows where it is fully embedded, and how adoption differs between countries. The report links adoption maturity to company growth, which gives you a useful argument if you are building a business case for further investment.
It then gets specific about where the time and cost savings show up. The operations section follows the employee lifecycle through recruitment, pre-boarding and onboarding, showing what respondents report about speed, operating costs and the ability to scale hiring. If AI onboarding efficiency is on your agenda, this part gives you concrete reference points to compare against your own team.
Just as useful is what HR leaders refuse to automate. The governance section ranks the HR decisions respondents believe should never be left to AI alone, from terminations to pay decisions, and explains why some countries draw that line more firmly than others.
AI compliance and HR governance as new regulations take effect
Confidence in meeting new AI regulations is uneven, and the report shows how that confidence changes with adoption maturity. It covers the safeguards HR teams already have in place or plan to add, such as human oversight procedures, bias testing and vendor contract reviews, and compares how widely each one is used.
You'll also find the barriers that stall broader adoption. Budget is on the list, but it is not the top concern, and the answer may change how you prioritise your next conversation with IT or legal. The report sets the regulatory picture in context too, contrasting European caution under laws like the EU AI Act and GDPR with a more encouraging stance in Australia.
Practical guidance for people operations leaders planning their next step
Each major section closes with an "Apply it" panel that turns the findings into action. These cover:
- Where to start automating if your team is early in adoption
- How to approach a first formal AI compliance review
- Where to keep human review in place as automation grows
- What to look for when evaluating AI platforms for sensitive employee data
Alongside the data, HR practitioners share first-hand accounts of using AI for real tasks, such as pulling an urgent investor report or chasing unapproved timecards before a payroll deadline. Commentary from Brian Elliott of Work Forward adds an outside view on whether HR will lead this change or have it happen to them. The final section includes usage data from Rippling AI customers, so you can see how AI tools are settling into daily people operations work.
The result is a short, readable research report that you can use in three ways: as a benchmark for your own adoption, as evidence for a budget request, and as a checklist of governance questions to settle before regulators or employees raise them. It is especially relevant if you operate across several countries and need to account for different legal expectations.
Download How HR Leaders Are Adopting AI to get the full survey results, the breakdowns by country and growth stage, the complete list of decisions HR leaders want humans to own, and the practical recommendations for building an AI program that is both efficient and compliant.