Why "waiting for clarity" stalls modern people leadership
SaaS in 2026 looks very different from what it did five years ago, and the idea of having a perfectly mapped-out path through AI-driven transformation is, at best, optimistic. As Sarika Lamont, Chief People Officer at Vidyard, put it: “We don’t have all the answers. My CEO doesn’t have all the answers.” And really, that’s the reality most people leaders are navigating today.
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Uncertainty is part of the job now, but it doesn’t have to slow things down. It’s easy to wait, for strategy, budgets, or alignment, but change isn’t waiting. The teams that fall behind aren’t lacking resources; they’re waiting for clarity instead of building it as they go.
Sarika takes a different approach. When she saw an opportunity to use AI to improve onboarding, she didn’t wait for permission. “I didn’t ask for permission… I was just going to go do it.” She ran a small pilot, invested about $2,500, and within 60–90 days saw manager task completion jump from 55% to 95%, and new hire satisfaction from 75% to 97%.
The clarity came after she started. That’s the shift: build while you’re figuring it out.
From HR initiatives to business outcomes: the operating model shift
Sarika is direct about how she sees her role: “I look at myself as a business executive first rather than an HR executive.” Instead of leading with HR programs and hoping the business recognizes their value, she starts with business strategy and works backwards, using people as the lever to drive outcomes, not the other way around.
The logic is simple, and hard to argue with. Business success and people success are deeply connected. As Sarika explains, the business needs to perform in order to reinvest in its people, whether that’s through development, compensation, recognition, promotions, or equity. And at the same time, the business only performs because of its people. You can’t separate the two without weakening both.
That perspective also reframes the “seat at the table” conversation that HR leaders have been having for years. In Sarika’s view, the leaders who earn that seat don’t ask for it, they build it. They ground themselves in strategy, in revenue, in how the business actually runs, and from there, align their people decisions to what truly moves the company forward. The credibility comes from showing that you understand the business and can translate that into meaningful people strategy.
And importantly, this way of thinking challenges a common misconception, that focusing on business outcomes somehow comes at the expense of people. Sarika pushes back on that idea. Leading with the business isn’t less people-centric; it’s what enables real, sustained investment in people in the first place.
Accountability = clarity + ownership
Most leaders treat accountability like a pressure valve, like something you apply when performance slips. Sarika's definition is different, and more useful. "Where this notion of accountability and holding each other accountable is done well, at the core of it is really about clarity and ownership, right?" That means explicitly defining what good looks like, being clear on who owns which decisions, and connecting individual work to company strategy all the way down to IC level. Not as a motivational exercise, but as operational infrastructure.
The mechanics matter here. It's not enough to set goals and hope people connect the dots. Sarika describes driving that clarity down to the IC level so people feel genuine ownership over their work, understanding not just what they're doing, but why it moves the needle for the business. That link between daily work and company strategy is what makes accountability feel like empowerment rather than surveillance.
She's also honest that it ebbs and flows. When the business is under pressure, when change is constant, when people are already paying a high tax on volatility, accountability gets harder to sustain. Ignoring that reality doesn't make it go away. It just means you're holding people to a standard without acknowledging the conditions they're operating in.
The other piece leaders often skip: modeling it themselves. Accountability requires leaders to have the tough, clear conversations, with other leaders, with managers, with ICs, when expectations aren't being met. Sarika admits she hasn't always pushed hard enough on this in her own business. Accountability is a practice requiring maintenance, and it starts with how you show up in the feedback loop.
A practical AI transformation playbook: pilot, measure, scale
Sarika spotted a real problem, onboarding was generating too much manual work for managers and not enough signal on new hire experience, and went looking for a tool to fix it. That tool was Kinfolk, an AI-native people ops platform she heard about through an HR online community. She negotiated a nominal pilot fee, offered to be a case study in return, integrated Kinfolk with her HRIS and Slack, and gave herself 90 days to prove it out.
"I didn't ask for permission from him, like, can I go do this thing? I was like, no, I'm just gonna go do it." She funded the experiment by making deliberate trade-offs within her existing HR budget, not backfilling a role at full cost, renegotiating tool spend, and made the case to finance with a simple P&L argument: the savings she'd already generated covered the pilot cost several times over.
The results were hard to argue with. Manager task completion on onboarding jumped from roughly 55% to 95-97%. New hire onboarding experience scores moved from around 75% to 97%, all within 90 days. When she walked her CEO through the data, the conversation shifted immediately from "should we do this?" to "how do we scale it?"
The broader principle here is deliberate: start with something repetitive and measurable, pick an AI-native vendor willing to build alongside you, integrate where your people already work, and run a time-boxed pilot before asking anyone for permission. Proof of concept is a far more persuasive argument than a business case built on projections.
Change management that reduces fear and accelerates adoption
When Sarika's CEO asked whether they should send a Shopify-style "AI or else" email to the company, she pushed back hard. Not because the urgency wasn't real, but because she knew her people. Mandate-first messaging creates resistance. She wanted adoption, not compliance.
Her approach started with a simple reframe: lead with what's in it for the employee. Career growth. Getting back time lost to admin and repetitive tasks. Learning skills that would matter. She anchored every communication there first, and only then connected it to business outcomes. Alongside that, she made a deliberate choice to be honest about what she didn't know. She wasn't going to stand in front of the company and promise AI wouldn't change jobs. Instead, she told people what was known, what wasn't, and committed to bringing them along as things evolved.
The tactics she used to make AI feel approachable were deliberately low-stakes. She launched a dedicated Slack channel, named by employee vote, and seeded it with memes and a ChatGPT roast of herself. ("It was really mean," she admits, which is exactly the point. Leaders being willing to look human is disarming.) She published clear guardrails: dos and don'ts that gave people a framework to experiment without fear of getting it wrong. And she made sure executives modeled the same vulnerability, visibly learning alongside the rest of the organization, not performing expertise they didn't have.
"AI adoption succeeds when you create psychological safety," she explains, and psychological safety comes from watching your leaders figure it out in public, not from polished all-hands decks telling you everything's under control.
Redesigning people ops with "AI employees" and personalized coaching support
Once Sarika had CEO buy-in, she built a system with named personas, defined scopes, and real performance feedback loops. The first AI employee, Yardley (they/them), runs on Risotto and handles documentation queries, surfacing answers from Google Workspace and public Slack channels. The second, Kinley (she/her), is powered by Kinfolk and focuses specifically on people processes: career development, competencies, compensation questions, and performance-related guidance. This resulted in two distinct tools with their own purposes, clear guardrails on what each one pulls from and responds to.
The reason for the persona structure isn't cosmetic. Giving each AI employee a name, pronouns, and an avatar makes it easier to communicate scope to employees, measure performance, and iterate. Sarika tracks how Yardley and Kinley are performing the same way she'd track any team member, gathering feedback, identifying gaps, retraining where needed.
The forward-looking piece is where it gets genuinely interesting. Sarika is working to integrate Kinfolk with Klar, her AI-powered performance and engagement platform, so Kinley can pull from one-on-ones, OKRs, performance reviews, and competency frameworks. The goal: an employee wondering how to get promoted can ask Kinley and get guidance that's actually personalized to their situation, not a generic answer, but one grounded in their own data. She's already introduced the two founders and is exploring either a custom API integration or a Zapier connection to make it work.
The philosophy underneath all of it is consistent with how she runs her entire people function. "Your manager does not own your career. You do," she says.
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