For Moxie's Chief Operating Officer Kate Connor, the AI budget has to come from somewhere, just not from people.
When companies cut parental leave or scale back a 401(k) match to free up budget for artificial intelligence, they're not making a neutral operational decision. They're making a statement. That's the view of Kate Connor, Chief Operating Officer at Moxie Communications Group, a New York-based PR agency whose client roster includes Oura Ring, Liquid Death, and Belkin.
Connor oversees HR, finance, and AI transformation at the firm, a combination of responsibilities that gives her an unusual vantage point on one of the more fraught tensions in the modern workplace: how companies fund their AI ambitions, and who ends up paying for it.
“When you’re making those decisions, you’re saying we’re valuing this technology more than we’re valuing you, because benefits are compensation. Make no mistake about that,” she said.
It’s a trend that’s already well underway. In April 2026, Deloitte announced it would cut parental leave from 16 to 8 weeks for employees in its internal operations division, effective 2027, and eliminate a $50,000 adoption and surrogacy benefit. Around the same time, Zoom reduced paid parental leave for both birthing and non-birthing parents.
Connor’s argument is that the money doesn’t have to come from people. As companies increasingly use AI to justify workforce cuts, the pressure on HR budgets is real, but she argues there are smarter places to look for savings than the benefits line.
Find the money somewhere else
Moxie’s own recent history offers one example of where that budget can come from. Last year, the agency made a strategic decision to close its offices and shift to a fully remote workforce. The savings from rent were reinvested directly into the team: improved compensation, better benefits, and expanded learning and development programs.
“There’s always places in your budget where you can free up some additional cash,” Connor said.
She argues that AI itself can offset some of its own costs, by replacing legacy software platforms that companies no longer need.
“Software is another area where if you’re spending money on AI, companies should really be assessing: do we really need these legacy SaaS platforms, or can we now build our own CRM tools, our own LMS tools?”
She also pointed to token usage as an underappreciated budget lever. Many AI platforms charge on a per-user basis, but additional features unlock consumption-based billing, and costs can escalate quickly without controls in place. Leadership, she said, has a responsibility to put token budgets in place on a per-team basis, using the controls available on the back end of most platforms.
“A lot of companies, because this maybe wasn’t on their radar last year, didn’t budget for 2026. Hence why they’re potentially scrambling and pulling from other places. It should not be coming from people’s compensation. That is sending totally the wrong message,” she said.
Getting AI adoption right
At Moxie, Connor has spent the past year rolling out AI tools across the agency. Her approach is notable for its deliberateness. Before selecting any platform, the team developed a comprehensive AI policy and security review checklist, consulting with CTOs and external advisors. No tool gets onboarded without passing a data security and privacy audit. It’s a level of rigor that many organizations are still catching up to, with studies finding that up to a third of employees use AI tools without IT oversight.
The training approach is just as deliberate. Research has found that poorly implemented AI rollouts can drive employees to quit, making the how of implementation just as important as the what. Rather than PowerPoint walkthroughs, Connor runs sessions where every employee shows up with their laptop open and works through the platforms in real time, building workflows and configuring personal settings as a group. The result, she says, has been unusually low resistance.
“We’ve been very transparent about our intentions with AI. At Moxie, AI is meant to augment our team and our workflows. It is not replacing our team and our workflows,” she said.
She credits that transparency with defusing the fear that typically accompanies AI rollouts. According to a Pew Research Center survey, more than half of U.S. workers are worried about AI’s impact on their jobs. By involving employees in platform selection through a cross-functional AI committee, and by communicating clearly at every stage of the process, the team has largely avoided the resistance that organizations often encounter when they introduce new technology without context.
“Companies that can involve their team in every step of the process will have evangelists living within each of these departments who can then help quell those fears that people might have if they didn’t have that information otherwise,” she said.
Transparency as the connective tissue
The word Connor returns to most often is transparency, and she applies it equally to benefits decisions and AI rollouts. For Connor, the trust gap that opens during an AI transformation is as much about what decisions signal as what they cost.
The retention numbers at Moxie suggest the approach is paying off. Some 27% of employees have seven or more years of tenure at the agency, a figure Connor describes as rare in the PR industry. She attributes it to a culture of inclusion in decision-making, from how new software gets selected to how the company’s strategic direction gets set.
“If we don’t have trust, then what are we doing?” she said.
Her advice to others navigating the same moment is to build the AI policy before looking at tools, involve the team before announcing decisions, and find the budget somewhere other than people’s paychecks. And through all of it, she says, keep communicating.
“It could feel a bit whiplash if one day we’re using this platform, then next month we’re using this other platform, without the why. It’s my job to make sure we’re sharing and being transparent with our team about why,” she said.
