Strive to be Earth's Best Employer asks an interesting question worth considering seriously in 2026: are people ready for what's next?
Just two years ago, I created a course on how HR teams can use AI. At the time, "what's next" meant productivity, and the work was clear. Help HR teams draft job descriptions faster, summarize interviews, generate learning content. A small slice of the portfolio for personalized learning paths if the team was ready. That was the scope for most.
Today the productivity use cases are still there. They got faster, cheaper, and produce better outputs. But they're a footnote. The work I do with HR teams now is about transformation. We build the AI strategy, the use case portfolio, the value-creation argument that lets HR lead the change rather than receive it. What does an HR function do when an autonomous AI system observes performance and attrition trends without anyone running a survey? How does HR keep a seat at the table when the engineering team writes the AI strategy without inviting them? What does Earth's Best Employer mean when "what's next" for your people might be working alongside agents you haven't hired yet?
For context, here's the Amazon leadership principle, in full:
"Leaders work every day to create a safer, more productive, higher performing, more diverse, and more just work environment. They lead with empathy, have fun at work, and make it easy for others to have fun. Leaders ask themselves: Are my fellow employees growing? Are they empowered? Are they ready for what's next? Leaders have a vision for and commitment to their employees' personal success, whether that be at Amazon or elsewhere."
In 2026, "what's next" is not a metaphor. It is a job market where work is being decomposed into skills, redistributed across humans and agents, and rebuilt at speeds the org chart wasn't designed for. The leader who takes this principle seriously has to make sure their people are ready, which means making sure their HR function is ready to lead the work.
That second move is harder than most leaders expect. HR has spent decades positioned as a service function. Payroll, benefits, recruiting, the occasional culture initiative. The AI transformation needs HR somewhere different. At the strategy table, alongside the engineering and product teams who are otherwise going to write the rules of work without them.
Three patterns I keep seeing
I've watched this play out three ways with clients. Sometimes HR or L&D is the one leading the AI conversation, and they bring me in to help. Sometimes engineering tells HR not to disturb, the AI work is theirs, HR can talk to them later. And sometimes an organization stands up an AI team and writes its strategy, and no one thinks to call HR. I unpack those three patterns more deeply in this issue's HR's dual mandate framework. The point for now is that the seat at the table is not given. It is taken or it is missed.
What does it take to take that seat? Four things have to be true about your HR function before the seat means anything.
Precondition 1: Data stewardship
AI in HR is only as good as the HR data underneath it. Mikaël Wornoo, who runs TechWolf and counts HSBC among 50 enterprise customers, will tell you that most large companies have rigid, reliable data on only ten or twenty percent of their employees. One CHRO in Jacob Morgan's Future of Work group spent three to four years standardizing her HR data before any AI tool could deliver. Without quality, governance, and validation loops with managers and employees, every other AI-in-HR conversation is theatre.
Precondition 2: AI confidence
HR practitioners need hands-on fluency with the same tools their engineering colleagues use. This is not a skill we will backfill later. Marketing got digital and later AI fluency a while ago. Operations got it with cloud. HR's turn is now, and it has to be lived rather than briefed.
Precondition 3: The human perspective
Josh Bersin, the most cited independent analyst on the HR function for two decades, recently laid out an HR 2030 vision worth listening to in full. His bet is that the next four years bring an HR architecture in which agents and super-agents handle most of the operational work, while HR practitioners tune the system rather than run individual processes. In that vision, he imagines an autonomous AI system that observes performance, productivity, attrition, and pay equity without anyone running a survey. Then he says the quiet part out loud: "It won't see the human side of work. It won't see the emotional side." That blind spot is the part of work HR exists to keep visible.
Precondition 4: Regulatory ownership
The EU AI Act classifies most HR-related AI systems as high-risk, including recruiting, candidate evaluation, promotion decisions, performance evaluation, task allocation, and worker monitoring. That triggers data governance, transparency, human oversight, and conformity-assessment requirements. NYC Local Law 144 already requires bias audits. GDPR rules apply to employee data. Works councils have a vote in many European countries. This is HR's perimeter to defend, and few engineering teams will know to ask the right questions.
Why all four matter together
Each of these four is a precondition. Lose one and the others compound. HR with great data and no AI fluency cannot use what it has. HR with AI fluency and no human eye optimizes for the wrong outcomes. HR with both but no regulatory backbone gets stopped by counsel six months in. HR with all three but bad data is back to theatre.
So when you ask whether your people are ready for what's next, the prior question is: is your HR function ready to make them ready?
The tension Earth's Best Employer holds
Strive to be Earth's Best Employer holds a tension I find easy to misread. The principle asks whether your people are growing, empowered, ready for what's next. Productivity and efficiency are not the test. Both the business case for AI and the human case for AI are real and pulling on the same leaders. Lean too far toward the business case and you ship a system that optimizes for output and breaks the workforce. Lean too far toward the human case and you ship nothing while your competitors operate with AI-augmented teams. The real work is in making sure HR can do both. Which means treating HR's readiness as a precondition for the transformation, not a downstream effect of it.
If HR cannot take a lead seat, the transformation is destined to fail. Earth's Best Employer makes it the leader's job to make sure they can, with the data, the tools, the human eye, and the regulatory backbone to be useful when they get there.
Your action step
This week, ask your CHRO or head of L&D one question: where in the AI strategy do they have decision rights, and where do they have only consultation? If the answer is "mostly consultation," that is your gap. Do not wait for it to close itself.
Then read the dual mandate framework for what the work actually looks like once HR does have decision rights, and the Findem case study for a concrete example of HR-led AI inside the recruiting layer.
If you'd like to design the HR readiness program your transformation needs, or want me to run a working session with your leadership team on what HR has to lead, I'd love to help.
Sources
- Josh Bersin, HR 2030 vision and writing on autonomous HR agents
- Mikaël Wornoo, TechWolf, on HR data quality (Future Ready Leadership podcast)
- Jacob Morgan, Future of Work community, CHRO data-standardization case study
- EU AI Act, NYC Local Law 144, GDPR
- Amazon Leadership Principles, Strive to be Earth's Best Employer