We keep asking whether AI will replace jobs. But I’m at least as interested in what kind of work it will leave behind. Will it create more room for judgment, creativity, and purpose? Or will it turn more workers into monitored inputs in a system optimized to death?
That question has become an obsession for me over the last few months. I keep encountering serious people making compelling cases in very different directions. Optimistically, Matt Hollingsworth has shown how AI can strip rote burden from nurses and clinicians and leave more room for judgment and better jobs. Ryan Wang has argued that even in call centers, one of the earliest testing grounds for AI automation, it’s a choice whether to use AI to surveil people or unlock more human ingenuity. In my essay The Bot Sandwich, I tried to name the coming split more bluntly: one group of workers will direct AI, another will increasingly be directed by it, and we still have a say in how many people end up on each side.
That is why I wanted to talk with Ryan Stowers of Stand Together. Few voices in philanthropy are making the case more forcefully that this moment should be organized around human potential, not fear. Ryan argues that more purposeful work is not a nice-to-have. It is a talent strategy, a growth strategy, and one of the biggest competitive opportunities of the AI era for employers.
In this conversation, he makes a case that is becoming more provocative by the week: the bigger risk is not that AI will be used to inflict harm on workers, but that fear will push us to clamp down too early and miss the chance to discover better forms of work.
He argues that if we get the recipe right across technology design, job design, and skill building, AI could widen agency and deepen purpose. Read on for his case for bottom up experimentation, the role philanthropy should play in advancing a more optimistic AI narrative, and what employers like Walmart and Virgin reveal about purposeful work as a competitive advantage.
On How AI Can Empower the Work Renaissance
ALLISON: I keep hearing two compelling stories about AI and work: one where it increases surveillance and reduces autonomy, and another where it removes rote work and expands creativity, leverage, and purpose. Which future do you think AI is pushing us toward, and what will determine the difference?
RYAN: My thoughts on this question need to be prefaced by a strongly-held premise. I believe that we’re spending too much time fearfully prognosticating and setting up guardrails. Instead, we should be seeking ways to let people create, adapt, and flourish with these technologies. Firm predictions are beyond our capacity anyway, because we consistently discount people and their predictably unpredictable ways of adapting to change.
Think about past technological cycles like the combustion engine and electricity. People living through those moments couldn’t have predicted how those innovations would drive social and economic growth. But as they came to understand what the technologies could do, they pushed them well beyond Otto’s four-stroke engine and Edison’s first light bulb. I’d like us to trust human resilience more as we imagine our relationship with this technology.
But even before AI entered the conversation, we were already trying and failing to build a twenty-first century economy with a talent system to match. Millions of Americans were already being left behind, already losing their connection to the American dream. How we think about who we hire and how we develop people needs to fundamentally change.
Americans are already telling us how to make that change. Seventy percent say they find purpose and meaning through their work. AI gives us the tools to meet that demand by enabling more dynamic, individualized career pathways. That has to be the design mandate for this new talent system: more purpose, more meaning.
If we expand purposeful work to more people, I think we’ll see more win-win outcomes for employers and employees alike. Personally, I don’t think people will tolerate being directed by AI — and I don’t think companies that use AI to extract value from their people will survive long. Those people will leave. And they have more mobility and choice than ever before.
Can I give an example?
ALLISON: I’d love that.
RYAN: The BBC recently reported on companies using computer vision to observe factory workers, which sounds very Big Brother on the face of it. But the application is designed to pinpoint where physical strain and injury risk are creeping into workers’ jobs. The AI watches how they work, provides immediate feedback on preventing injury, and recommends to leaders where technology is needed to reduce accidents and long-term disability. That helps companies retain talent, because workers see how the company is investing in their health — and nobody wants to end up on long-term disability, with all the pain and uncertainty that comes with it.
I like this story because it shows AI being used to help people work better, safer, and with more purpose. But it doesn’t change the fact that we should have been thinking about safer, more human-centered factory work all along. If we only address these issues because AI forced our hand, we’re missing the chance to tackle the true root causes of economic impediment.
ALLISON: That example makes me think about the obsession with bottom-line efficiency over the last two years, which has been largely about reducing costs by reducing headcount. But efficiency is becoming commoditized; every company will be more efficient. The real opportunity is in the top line: imagining new products and services, operating differently, expanding and creating value. That’s exactly the kind of work you’re describing.
RYAN: And I’d add that innovation happens when employers are genuinely trying to help workers find purpose and meaning in what they do. I know that sounds fluffy, but it’s a long-standing HR innovation imperative that has never fully taken hold across the corporate ecosystem.
ALLISON: What companies are using this AI moment to deepen purpose at work?
RYAN: I’m excited by companies experimenting with AI across the org chart rather than developing top-down policies. That bottom-up approach, I think, will create the winners.
Virgin’s 100% Human at Work initiative — built through their Virgin Unite foundation and applied across their global businesses — empowers employees to deploy technology in ways that improve both the product and their own work. They’re helping activate this approach with other organizations as well through innovation clusters that bring companies together to build a future-ready workforce through a skills-first approach. One that will especially help early-career and transitioning workers develop the innate human skills — adaptability, empathy, teamwork — they’ll need as automation and AI gain stronger footholds in the workplace.
Walmart has also been vocal about their human-centered AI strategy, enabling more positive, customer-focused work. Their individualized approach to AI upskilling has produced real gains by zeroing in on what AI does well while building employee skills in things AI will never do well: empathy, relationship building, in-store customer service. They announced last year that they’re training all their employees — 1.6 million people, both frontline and corporate — in AI tools designed to elevate their roles and experience. By doing this, they’re empowering their employees by giving them access to technology that will strengthen their potential, not just through efficiency, but by making work more intuitive and rewarding.
ALLISON: So the AI strategy becomes less about managing employees through AI and more about helping them leverage it for their own gain. But this kind of experimentation requires capabilities that traditional front-line, entry-level work was never designed to build: owning a goal, marshaling resources in service of it, navigating uncertainty. What’s your view on how we support employers and employees in making that skill transition?
RYAN: Employers have an incredible opportunity right now to fundamentally rethink upskilling and own that process in-house. The frontline jobs of the past didn’t leave room for people to connect to purpose, creativity, and meaning. I believe everyone, regardless of role, has an inherent drive for those things. We’re working with employers to find ways to build that flourishing into frontline work.
At our last Human Potential Summit , I remember a story shared of a sales agent with the car rental firm Avis. He noticed that at his location, so much of the customer side of things, from checking people in and processing returns, was still very manual — at the cost of the customer and to the business. He started experimenting in his downtime with a new AI tool available to him through the company and ended up building a dashboard that helped them track and resolve potential issues more proactively. It was a game-changer, and this employee is now part of the engineering team, helping the company find new ways to improve and deliver better customer experiences through AI technology. That type of thing doesn’t happen unless employers create the conditions for people to apply their skills and creativity in service to a greater purpose.
ALLISON: As you’re talking, I’m picturing three levers for realizing this human-centered vision. First, technology design, specifically, technology that augments rather than automates. Second, job design: how do we give people permission and structure to move from rules-based work to entrepreneurial problem-solving? Third, capability building and upskilling: what support do people need to do these more expansive jobs?
RYAN: I like that framework. And I think there will be levers we haven’t discovered yet — we’ll learn more about how to redefine work by actually doing it.
On Why A More Human-Centered Future May Actually Require Less AI Regulation
ALLISON: Let’s dream forward about ten or so years to the time when we have sorted out our constructs around work and AI policy. What happens if we get it right? And wrong? Bring those futures to life for us.
RYAN: I think we’re taking a too cautious, too regulated approach to AI, driven by fear and uncertainty. There are 1,700 new state-based policies focused on limiting AI innovation signed into law in the last two years. That’s how you stifle innovation at the individual level, which is exactly where I see the most potential for human-centered AI to emerge.
Humans have a profound ability not just to adapt, but to surge through change in exciting ways. The risks of unleashing AI are, in my mind, much lower than the risks of overregulating it. I do have a presiding belief in human ingenuity, and I don’t believe in stifling it.
If we get AI and the future of work right, hiring will value creation over credentials, and agency over hierarchy. We’ll invest in what is uniquely human and automate what has always been dehumanizing. People will be able to define purposeful work for themselves, stacking experiences like Lego blocks rather than climbing a linear career ladder. The goal is to empower people in every role, every career choice. But we’ll only get there if we have the freedom and agency to experiment and find new ways AI will augment our progress.
If we get it wrong — if we lean into top-down regulation instead of bottom-up innovation — we will limit autonomy and deepen inequality. Work will remain one-size-fits-all, people will be forced into meaningless, homogenized roles where their value is extracted and their agency surrendered. We will have missed an incredible moment to reach new levels of human flourishing.
This is, ironically, exactly the future that so much regulation wants to protect us from. The problem with a top-down approach is that it’s rooted in a fear that human potential has reached its limit and that technology will outpace our capacity for innovation. I refuse to accept that.
On Why Philanthropy Should Lead the Public Conversation on AI
ALLISON: Let’s talk about philanthropy’s role at this moment. Perhaps consider the AI backlash, which many guests flagged as an emerging signal six months ago, has now become a political lightning rod. The Governors Association meeting, where many pro-AI governors substantially backpedaled on AI support, is a case in point. But beyond managing backlash, what should philanthropy’s priorities be on AI?
RYAN: The political conversation around AI is almost entirely fear-based, and that’s obscuring Americans’ ability to understand both the technology and its potential. Philanthropy can help by amplifying stories and voices from healthcare, education, retail, and other sectors where AI is genuinely empowering people. But right now, nobody has taken the lead on changing this narrative in a thorough, well-engineered way. That strategic work needs to happen.
Beyond shaping public understanding, philanthropy needs to be a balancing, optimistic voice in policy conversations at state and national levels, building coalitions focused on opportunity and pushing the public sector toward a less obstructionist approach. Rather than simply writing regulations, I want to see government investing in AI to solve social problems.
One of our most exciting initiatives right now, Next Ladder Ventures, focuses on exactly that. We invest in breakthrough technologies that empower everyday people to navigate their lives, build stronger communities, and control their economic futures. Give people the tools, and you give them the freedom to make AI work for jobs, healthcare, legal support, even food, and make plans aligned with their dreams and ambitions.
ALLISON: Next Ladder Ventures is a great example of the new wave of philanthropic response to AI. Can you talk about that theory of change?
RYAN: Next Ladder is focused on harnessing AI to help Americans in strategic, localized, and individualized ways, often by decentralizing and localizing information to connect people with resources. One portfolio company, CarePortal, is an online platform that connects families in crisis and those affected by the foster system to local support, in real-time. It’s a decade-long endeavor to amplify this kind of impact across a wide range of economic opportunity challenges.
ALLISON: My guests often raise concern about the erosion of the early career ladder as AI automates routine work — leaving colleges, high schools, and individuals to bear the burden of preparing people for the new entry level. You take the view that employers are a big part of the solution. How does philanthropy incentivize or influence employers to help navigate this transition?
RYAN: This may be the most revelatory insight of the last three to five years: we need to help employers see the business case for job redesign and AI adoption.
For a long time, employer activity in this space was driven by CSR and social impact — worthy things, but we all know a clear business case is what moves large corporations. The environmental factors we’ve discussed today — AI, the failure of the existing talent system, Americans’ demand for something better — are making that business case crystal clear.
The task now is to socialize it everywhere, constantly. Established organizations can be rigid, so the best tactic is building a movement of early adopters who are genuinely redesigning their approach to talent — not just tweaking at the margins — and amplifying those stories across ecosystems.
That’s where philanthropy can help. McDonald’s just celebrated the 10-year anniversary of their Archways to Opportunity program. This program has provided access to education and training for more than 90,000 employees, and we partnered with them to tell the stories of the real individuals who grew their careers — often while working with McDonald’s — through Archways. By publishing these results on our Forbes BrandVoice platform, we were able to share how these initiatives benefit both the individual and the business with thousands of other employers.
So, there’s a unique role here that philanthropy can and should play in leading AI’s public narrative. That includes building coalitions that both advocate for and actively construct that vision. We have a clear line of sight into the problems our democracy faces. And without a profit incentive, we’re better positioned to build public trust around a positive vision for AI.
One Small Signal
ALLISON: What’s one small thing going on in the world right now to which we should be paying more attention?
RYAN: For whatever reason, AI’s positive virtues are not getting the visibility they deserve, even despite the work of organizations and publications like the Abundance Institute and your work. People are missing these stories, and thus all the positive case stories of AI in service of humanity that already very much exist. The call to action for AI advocates will be, as you say, to write a narrative that helps people see themselves in the AI economy of the future — and then strategically engineer AI’s ability to unleash human potential.
The framing of two groups — one that directs AI, one that's directed by it — resonates inside large companies in a way that's uncomfortable to name. The fear of ending up on the wrong side of that split is real. And inside a constrained environment, the path to the "directs AI" side is harder because the tools are limited and the practice is invisible.
The people who are building the directing skills are doing it on personal time, with personal tools. Their companies can't see it and won't reward it until the tools catch up. That gap between where the practice is happening and where the recognition lives is the tension nobody's naming. While the recognition will catch up eventually, the question is what you build while it's still invisible...