To address this, we convened a panel of experts to glean their insights on the challenges facing CHROs in 2026 and the practical solutions that can help.  

The problem: Siloed, opaque workforce decisions  

One of the biggest challenges for people professionals, and one area where the savvy use of technology can really help, is decision-making. Workforce decisions are rarely broken because of poor policy, says Maria Colacurcio, CEO of Syndio, a pay equity software platform. Instead, they often break down in the execution. 

“What happens is, once those policies are set, they go out into the wild,” she says. This could mean that a recruiter needs to close a deal by Friday to get a candidate in, or a retention bump gets approved because a specific manager makes a really good case for it. “These decisions happen in massive silos, so, in spite of really good intentions, there are unintended consequences when you can’t see all of these decisions together.” 

This means that it is no longer enough to simply formulate excellent policies once a year and let them go, says Sara Morales, senior vice president for people and communities at Cisco. “Now, with the pace of change, we need to be proactive and reactive. Culturally, what we’re seeing is an evolution of highly structured teams’ organizational decision-making to much more dynamic and fluid ways of making decisions at speed.” 

Read more: The unspoken rule: Is English really the key to success in Europe’s boardrooms?

Laura Weis, global human-AI strategy lead at WPP, agrees. “Ways of working are fundamentally changing, and you only get value from technologies like AI if we’re moving away from this siloed, waterfall, process-heavy way of working towards something more integrated and cross-functional.” At WPP, this means moving more of the HR function into cross-functional product squads which work together to shape work design.  

Practical takeaway: Break down decision silos by mapping where key workforce decisions (hiring, promotion, pay, performance) are made and introducing shared governance or checkpoints across functions. Move from isolated decisions to connected workflows—ensuring HR, finance, and business leaders are working from the same data and principles. 

The pressure: Why this is reaching a breaking point 

This particular challenge is coming to a breaking point owing to a confluence of factors. Regulation, AI adoption, and workforce expectations are all accelerating simultaneously, and this is fundamentally changing the role of people leaders.  

“There are 657 things that leaders are trying to work through every day—maybe even every hour,” says Morales. “To move through that with clarity, leaders need to establish what are the few most important things to focus on.” 

One such important thing, for European Leaders, is the EU Pay Transparency Directive, the measures of which member states must have implemented by June of this year. The result of this, says Colacurcio, is a greater need for explainability. “All of your folks now have access to so much more information,” she says. “They’re going to be showing up in a way that requires your people leaders on the front line of these difficult conversations about pay to be able to explain things.”  

Practical takeaway: Shift from annual planning cycles to more frequent, cross-functional workforce reviews, and equip frontline leaders with clear frameworks for explaining decisions—especially around pay, progression, and performance. Prioritization is critical: Define the few decisions that matter most and ensure consistency in how they are made and communicated. 

The misstep: A fixation on outcomes, not decisions 

One of the tools leaders will reach for when it comes to workforce issues is AI, but many fall into the trap of thinking that simply implementing the technology will be enough to solve the problems. Not so, says Weis. 

“It leads to a lot of frustration because people feel like they should generate huge value with these tools,” she says. “But the way we have designed work is totally not suitable for the way of working that needs to happen in order to unlock value with AI.” 

Read more: Fortune on the ground at Mobile World Congress

Weis explains that too many companies are seeing the productivity and efficiency gains AI can bring as a solution to employees being overworked and burned out. Unfortunately, workers under pressure are highly unlikely to change their way of working or experiment with new tools. Instead, if they do use AI it is in relatively unstrategic ways which creates more frustration and increases cognitive load.  

“The story was that AI makes work easier, but actually what happened is that AI took away the easy work,” says Weis. “AI is a multiplier. If you have a mediocre performer or team, AI will simply make that worse.” 

Practical takeaway: Don’t treat AI as a quick fix; focus first on redesigning how decisions and workflows operate day to day. Create the conditions for effective AI use by reducing overload, clarifying expectations, and aligning teams on what “good” decision-making looks like before layering in technology. 

The Shift: From remediation to prevention 

So, what can people leaders do? “You have to start by collaborating differently,” says Morales. “We have to create space, time, and energy for people to learn and think and strategize.” At Cisco, this involves a new practice called Time to Grow where all employees have four hours blocked out in their calendars every month for each of them to go and invest in themselves and develop the skills they will need to be ready for the AI transformation.  

For Syndio’s Colacurcio, the organizations she sees as winning in this area have changed the way they do governance—particularly when it comes to pay. “It’s not governance after the fact, with this big bucket of money that you then have to dole out to fix your mistakes,” she says. “It’s thinking about a manager getting guidance in the moment when a pay decision is being made so you can prevent issues from happening in the first place.” 

At WPP, Weis says it’s a question of embracing a total mindset shift throughout the organization. “We’re moving from a knowledge economy to an innovation economy,” she says. “So we’re trying to get people to act in an innovative and creative way, to continuously reimagine and to question their ways of working. AI gives us speed, but it also gives us space, and we’re really trying to ensure that space is being used in an effective way, rather than just being absorbed by the system.” 

Practical takeaway: Embed guidance and governance into decisions as they happen, rather than relying on retrospective fixes. This can include introducing real-time decision support, setting clearer guardrails for managers, and carving out protected time for learning and experimentation to build long-term capability.