Is compliance enough? Kelly Trindel and Reggie Townsend discuss how organizational culture and trust form the true ceiling for AI success.
Sydney Scott
Editorial Strategist, AI
Workday
Audio also available on Apple Podcasts and Spotify.
AI governance is often framed as a question of compliance: What does the law require? What risks do we need to control? What rules should we put in place?
Those questions matter. But they don’t answer the bigger one: What kind of organization do we want AI to help us become?
In a recent episode of the Future of Work podcast, Workday Chief Responsible AI Officer Kelly Trindel spoke with Reggie Townsend, VP of AI Ethics, Governance, and Social Impact at SAS, about why the choices organizations make about AI today will shape far more than their compliance posture. They will influence how people work, how decisions get made, what capabilities organizations cultivate, and ultimately, the organization’s culture. .
Regulation can establish a floor. Responsible AI governance is what helps organizations decide what they want to put above it.
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"If an enterprise is not a caring organization, then what is it? What's its purpose? Is it just there to extract or is it just there to earn?"
Reggie Townsend
VP, AI Ethics, Governance, and Social Impact
SAS
For Townsend, enterprise responsibility is a core duty of care. When a business lacks this care, it fails its broader social duties to workers and consumers. As he put it: "If an enterprise is not a caring organization, then what is it? What's its purpose? Is it just there to extract or is it just there to earn?"
And when organizations turn responsible AI into a basic legal checklist, they waste a huge chance to shape their workplace—especially, when it comes to governance.
As Townsend notes, governance proves how a business scales its judgment. It gives companies the tools, rules, and limits to make sure core values show up in daily operations.
Townsend said, “I describe governance as the way we scale our judgment. And, I think it's very important for us to deliberately attach definitions and operate from those definitions as we move forward.”
Tech shifts never happen in a vacuum. New tools always collide with human systems and company culture. When physical or digital infrastructure changes, humans often adjust their social norms to fit the new system.
Townsend pointed to electricity as an example: once it diffused through society, manufacturing no longer had to cluster around steam engines, “[It] created opportunities for people to live outside of urban areas. That's why we ended up creating suburbs and highway systems…the culture adapted to the new system."
Adding AI into enterprise software is the same. It changes how employees interact, make decisions, and view their daily jobs.
But these big shifts can carry long-term consequences. Business leaders have to evaluate if new tools protect or break their core identity.
Townsend put it this way, "We can reasonably anticipate that this technology shift—from mobile to internet, now to AI—will have a 100 year effect, for sure. But this AI moment that we're in, specifically around generative, will probably have a quarter century effect in terms of how we need to adjust our organizations."
That impact makes careful planning vital right now.
"Think of regulatory requirements as the floor, then your values and norms for your organization sit up above and beyond that."
Kelly Trindel
Chief Responsible AI Officer
Workday
One of the hardest questions raised by AI isn’t simply which tasks can be automated. It’s what people may stop learning when those tasks disappear.
Early-career work often includes activities that seem ripe for automation: drafting, analysis, research, synthesis, and routine problem-solving. But those activities also provide the practice through which people develop judgment and expertise.
That creates a longer-term workforce question for leaders. If AI removes too much of that developmental work today, where will tomorrow’s experienced professionals and leaders come from?
Responsible adoption therefore requires organizations to look beyond immediate productivity gains and consider the capabilities they want their workforce to retain and develop over time.
Smart leaders avoid rushing into AI just to trim short-term costs—Townsend called decisions made purely for cost cutting “really shortsighted." Instead, they focus on clear business use cases that help employees without taking away their control.
Regulations like the European Union (EU) AI Act set necessary guardrails, but general regulations are just the beginning.
Trindel framed it this way: "Think of regulatory requirements as the floor, then your values and norms for your organization sit up above and beyond that." Townsend agreed, “Your values have to be your ceiling."
Relying only on external rules leaves a company constantly reacting. "As leaders, what we cannot afford to do is wait until things level out,” Townsend said. “From a competitive standpoint, you may be left behind. From a safety perspective, you may end up hurting someone. We just have to start put some measures in place. And we can do that now without waiting.”
Waiting for global laws to settle before taking action leaves businesses behind and opens the door to harm. Real leadership closes the gap between top-level policies and daily work.
And to begin to do this, leaders must confront hard questions about identity. Recounting an internal debate at Workday over a customer request for surveillance capable AI, Trindel noted, "Even if there's customer demand for something, we could make some money on it—is that really who we want to be?"
"Who are we really? That's the identity question, Townsend added.
It’s essential leaders make these calls early so that decisions aren’t hastily made in the moment.
"Technology is always an enabler of our values."
Reggie Townsend
VP, AI Ethics, Governance, and Social Impact
SAS
Turning these ideas into practice starts with treating AI governance as a shared organizational responsibility. Cross-functional teams can bring together the perspectives needed to shape how AI is developed and used, while clear visibility into AI systems and use cases helps organizations understand where the technology is operating and what it is enabling. Staying current on evolving regulation provides another essential part of that foundation.
But effective governance requires more than structures, inventories, and regulatory awareness. Organizations also need clarity about what they value—and a way to carry those values into decisions about AI.
That means asking not only whether an AI use case is permissible or technically possible, but what it could mean for the organization and its people. Does it strengthen or diminish human judgment? What capabilities does it help people build—or potentially allow to atrophy? Does it reinforce the kind of workplace and culture the organization wants to create?
As AI reshapes work, these choices will increasingly shape organizations themselves. Strong governance helps leaders make them deliberately, with a clear understanding of both the opportunities they want to pursue and the human capabilities and values they want to preserve.
AI acts as a massive amplifier for enterprise capacity, but the technology stays neutral on its own. As Townsend summarized, “Technology is always an enabler of our values.” It reflects and scales the values of the humans who set it up.
For top companies of the future, compliance will go hand-in-hand with strong governance that protects human thinking, builds workplace trust, and strengthens company culture.
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