As companies enter 2026, the risk of confusing frantic activity with actual performance has never been higher. For Katya Laviolette, chief people officer at online access management platform 1Password, maintaining clarity about what high performance actually looks like has been essential as the company scaled from 500 to over 1,400 people globally.
“Growth can create momentum, but high performance depends on shared purpose, clarity and accountability, not activity alone,” she says.
Redesigning for enterprise reality
As 1Password evolved from a consumer product into a B2B, multi-product identity security company, Laviolette realized the people practices that worked at a smaller scale wouldn’t hold up in an enterprise environment.
“B2B requires different talent profiles, as well as compensation mixes…across sales, revenue and customer-facing roles and a different operating rhythm around pace, collaboration and time-to-impact,” she says.
The warning signs appeared in the fundamentals: roles became more complex, ramp times stretched longer and performance metrics didn’t fully capture how B2B value is created. “We saw the signal in meaningful ways,” Laviolette notes. “Strong hires needed different enablement to deliver impact. These were system design issues.”
The fix required aligning everything from skills and hiring to onboarding and compensation with the realities of an enterprise security business. “At scale, talent strategy has to move in lockstep with business strategy to support sustained growth,” she says.
Early warning signs of eroding standards
Laviolette identifies three critical indicators that performance standards need attention during growth periods.
The first appears when direction gets lost in translation. “One early warning sign is when clarity degrades as priorities move through the organization. Direction may be crystal clear at the C-level, but further down, teams begin interpreting it differently,” she says. When this happens, people are working hard, but not always toward the same outcomes, and Laviolette says this creates inefficiency.
Manager behavior shifts provide the second clue. During rapid growth, managers can become translators of priorities instead of coaches for impact. “When expectations vary across teams, or accountability feels inconsistent, it usually points to a need for clearer goals, stronger direction and tighter feedback loops,” Laviolette notes.
The last signal reveals a fundamental disconnect between activity and outcomes. “A third indicator is when pace increases, but results don’t improve at the same rate,” she says. “When speed starts to outpace clarity, leaders have an opportunity to step in early and reset what strong performance looks like at scale.”
Distinguishing sustainable performance
When leadership pushes for speed, Laviolette recommends focusing on fundamentals. “The most important questions are about focus and trade-offs,” Laviolette says. “What outcome are we actually driving toward, and how will we measure success? What work is being paused or deprioritized to make room for this effort? And do teams have clear ownership, decision rights and the support they need to deliver without cutting corners?”
The key, she emphasizes, is integration of immediacy with structure. “Sustainable performance comes from pairing urgency with clarity and accountability. If speed isn’t anchored in those fundamentals, it usually results in more inefficient activity, not progress.”
AI’s role in performance culture
For Laviolette, the central concern around AI isn’t efficiency gains, but how it affects the way employees think. “The test is whether AI strengthens judgment or weakens it,” she says. “In a high-performance culture like ours, efficiency only matters if it creates more space for critical thinking, collaboration and accountability.”
She draws a clear distinction between AI that enables and AI that undermines. If AI removes low-value work and helps teams focus on decisions that truly matter, it reinforces performance and development. But if it obscures decision-making, she says that’s a problem.
“When AI supports curiosity, judgment and ownership, it elevates performance,” Laviolette says. “When it shortcuts those things, it erodes performance.
Read more: What CEOs want from HR leaders in 2026
Strategic tech investments for scale
Laviolette advocates for infrastructure that may not deliver immediate returns but proves essential in the long term. She suggests HR should push for secure, intuitive platforms that support performance management, manager effectiveness and clear feedback loops, as well as tools that balance productivity with security in an increasingly AI-enabled environment.
“These investments often face pushback because they don’t promise instant efficiency gains, but they’re what allow standards to hold as complexity increases,” she says.
The cost of poor tools compounds over time. “If a tool adds friction, leads employees to adopt unapproved workarounds like shadow IT or doesn’t scale with how people actually work, it will cost more over time than it saves.”
The human side of AI adoption
Looking ahead to 2026, Laviolette sees AI fluency as a critical organizational capability. “This is the moment when AI stops being a technology story and becomes a people story.”
Success, she argues, won’t come from deployment volume but from capability development. “The companies that succeed won’t be the ones that have deployed the most tools, but the ones that have developed AI-confident employees who know how to use these systems responsibly, question outputs and prioritize security alongside innovation.”
This capability building requires deliberate effort. “Building that capability through training, governance and cultural norms isn’t optional,” she says. “It’s what turns AI investment into real performance, and HR has a critical role to play in making that shift stick.”
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