I recently attended the Fortune Workplace Innovation Summit in Atlanta alongside our CEO, Maria Colacurcio. The sessions covered ground that will feel familiar to anyone working at the intersection of people, technology, and organizational strategy: AI and the future of work, pay transparency, DEI, workforce flexibility, the changing role of HR.
Here’s my read on what CHROs are focused on in 2026 and beyond based on my time there.
Across three days of sessions and instructive conversations in the hallways, the same deeper tensions kept surfacing underneath whatever topic was nominally on the table. And those tensions tell a useful story about what is top of mind for CHROs right now.
The power pendulum has swung, and we’re still catching up to it The COVID era created a specific set of conditions: employers needed workers, workers had leverage, and the resulting shift produced four-day workweeks, unlimited PTO, expanded flexibility, and a broader renegotiation of what work could look like.
That era is over.
The clearest illustration came from Ryan Breslow, CEO of Bolt, who described rolling back the four-day workweek and unlimited PTO. He also described eliminating his HR department and attributing the disappearance of problems to that decision. There was an audible gasp in the room. In the conversations afterward, people split roughly into two camps: those who saw a values conflict they couldn’t get past, and those who said, frankly, that if you want to survive as an HR leader right now, you need to be a “pretzel” — to adapt and flex based on what the CEO needs.
The power shift isn’t only showing up in benefits decisions (and Bolt isn’t alone in the rollback). It’s visible in how organizations are handling DEI. Some dismantled programs publicly; others are continuing the work without the press release. One speaker made the point that employees may disagree with a decision, but they will respect consistency. The organizations taking the most damage right now aren’t necessarily the ones that changed course. They’re the ones whose actions don’t match what they say. One example discussed how one company’s proxy filing that was boring but sincere had fared better on employer reputation and talent than another whose public positioning and internal reality diverged.
The power shift is showing up in AI. A panelist in a session on organizational structure acknowledged what many leaders are thinking quietly: the gains from AI are flowing to shareholders and leadership while the risks flow to workers. That will remain the case, they said, until the resistance becomes significant enough to force a rebalancing. That’s not a new pattern in economic history, but it’s arriving faster than the AI governance structures designed to manage it.
AI has entered a reckoning phase and the hallways were ahead of the stage
The on-stage AI conversation was a mix of familiar and new. Adoption enthusiasm is still present, but the texture has shifted from a year ago.
One of the sharper moments came from a Gusto panelist walking through their approach to AI fluency: tracking both how people were using AI and what impact it was having, not just whether they were using it at all. The implicit warning in that framing landed: Measuring use without measuring outcomes produces behaviors you don’t want. There’s a name for the extreme version: tokenmaxxing, which treats high AI use as an indicator of productivity. It’s a pattern organizational psychologists have documented for decades: give people a metric, and they’ll optimize for the metric, not the underlying goal it was meant to represent. People are adaptive.
They’ll find the path with the least friction to satisfy the objective.
The more interesting conversation was in the hallways. Leaders are asking harder questions than they were 12 months ago:
- Where is AI actually reducing work versus generating new kinds of work?
- Where is it improving output versus quietly eroding the quality of human thinking and skills over time?
- Does the cost math that seemed clean — AI cheaper than headcount, therefore scale AI — hold up under scrutiny?
Recent reporting has surfaced how some organizations are learning the hard way, including burning through annual AI budgets in months after aggressively incentivizing adoption. Others have faced situations where compute costs exceed what they pay the employees using the tools. And projections for agentic AI suggest token consumption could increase dramatically by 2030: even as per-token costs fall, total bills are likely to keep rising.
The point isn’t that AI doesn’t create value. It’s that value is not evenly distributed across tasks, roles, or organizations, and the economics of broad adoption need more precision than the initial wave of enthusiasm applied. Organizations are moving from “use as much as possible” to “use where it actually works.” That’s healthy. It will also require new ways of managing that are only now starting to emerge.
There’s another thread here worth naming. The cost pressure from AI doesn’t stay in the tech budget. It bleeds into other decisions like benefits and headcount. When AI spend runs over, the pressure lands somewhere and it doesn’t always land where it started.
Pay is where all of these tensions converge
The session I keep coming back to featured Syndio CEO Maria Colacurcio, who was in conversation with Hannah Williams, founder of Salary Transparent Street. Even though Maria came from the perspective of employers, and Hannah from the perspective of employees, they met in the middle on the most critical point: that most organizations can’t explain why they pay what they pay.
Organizations need flexibility to differentiate pay based on role, performance, and market conditions, manage budget constraints, and navigate a regulatory environment that looks very different in the U.S., the EU, and the 100-plus countries in between. Employees want to understand why their pay is what it is. They want reasoning, not just a number. When they can’t get it — because the organization doesn’t have a clear answer, or won’t share one — they fill the gap with whatever’s available. Social media, employer review sites, a colleague who mentioned their offer in passing, and increasingly, AI tools.
Maria also spoke to the people caught in the middle: recruiters. They sit across from candidates navigating pay transparency laws, internal equity constraints, and competitive market pressure simultaneously, often without adequate tools or guidance in the moment they need it. When even the people closest to the work can’t explain the rationale behind a pay decision, that’s usually a signal that the tension hasn’t been resolved upstream.
Explainability is where employer and employee interests intersect. Not full disclosure of every salary in the organization. Not the opacity that erodes trust over time. The ability to explain the reasoning behind a pay decision clearly, consistently, in a way a person can understand and engage with. That intersection is achievable, but it requires organizations to understand the reasoning behind pay, scale that context across the org, and govern pay at the moment a decision is made, not reconstruct it six months later during an audit.
The thread underneath everything: tensions managed, not solved
The conversations at the summit, on stage and off, kept framing structural tensions as problems with solutions. Most of them aren’t.
The gap between what organizations need and what employees need around pay isn’t going away. The conflict between AI adoption pressure and the governance required to make it work isn’t going away. The strain between holding organizational values and adapting to a changed power environment isn’t going away. All of these are the permanent conditions of operating in a complex environment where multiple legitimate interests are in play at once.
The most useful capability right now isn’t better answers to the questions on stage. It’s the organizational infrastructure to hold the tension in a way that aligns with what the organization actually stands for, even when the external environment is pulling in multiple directions.
A note on where this is heading
On the day the Summit opened, Syndio announced a new market category — Decision Intelligence for Pay — and launched Decisions, an AI-powered product that puts real-time pay intelligence into the hands of recruiters, managers, and compensation leaders, guiding human judgment in the moment. The timing felt relevant.
The themes from Atlanta are the same dynamics driving the category: how organizations govern the use of AI, manage the employer-employee demands around pay, hold values under pressure, and build explainability into how they operate. Compensation is up to 70 percent of total operating costs for the average enterprise and, by most measures, the least governed part of the business. Syndio’s research puts the lifecycle value of a single well-governed pay decision between $5,257 and $10,454. For a 60,000-person organization, that aggregates to $31 to $62 million in recoverable value annually across overpay that compounds through every merit cycle, turnover from underpay, remediation costs, and compliance exposure that builds quietly until it doesn’t.
Governing pay well and running a lean, competitive organization are fully compatible goals. Ungoverned pay decisions are expensive: in overpay that compounds through every merit cycle, in turnover from underpay, in remediation costs that dwarf what governance would have cost.
The financial case and the human case point to the same place.
That’s the false tradeoff the Summit kept circling. What’s good for organizations and what’s good for people aren’t as opposed as the current moment makes them feel. At the point of the decision — when reasoning is captured, values and policies are encoded into the process, and the person making the decision has what they need to do it well — there’s real shared ground. Getting there is the work.
Interested in learning more about how Syndio can help you govern pay decisions? Talk to our team.
