Topic: Technology and AI

Leveraging AI & Technology to Connect More Communities to Quality Healthcare

Posted on by Brianna Provenzano

Technology is reshaping healthcare access, but progress is uneven. AI, digital tools, and data platforms have the potential to extend care to underserved communities, address workforce shortages, and improve outcomes. At the same time, gaps in infrastructure, trust, and governance risk widening disparities rather than closing them.

On May 5, NationSwell convened a group of leaders from the healthcare, technology, philanthropy, and the social sectors to unpack how AI and technology can be used to connect more communities to quality care. Together, the group focused on practical strategies for deploying technology responsibly, building partnerships that center community needs, and ensuring that innovation strengthens equity, affordability, and trust in healthcare systems. Some of the most salient takeaways from the discussion appear below:

Key Takeaways:

Ensure that technology empowers community health workers as relationship builders. AI and tech are most valuable when they augment the work of community health workers rather than substitute it. The trusted, relational role that CHWs play in their communities is the irreplaceable foundation of effective care connection. All technology deployed should be designed to protect and extend that capacity.

Design AI tools with CHWs and communities. The most responsible AI adoption in healthcare requires community health workers and the communities they serve to be active participants in tool design. Without mechanisms for feedback, bias mitigation, and accountability, technology risks widening the very health inequities it aims to address.

Prioritize data security and trust as foundational. Organizations working at the intersection of technology and community health must treat data stewardship with the same rigor as the healthcare system itself. Achieving certifications, committing to governance structures, and designing platforms that bring AI into the human loop are essential to maintaining the trust that makes community engagement possible.

Address the full picture of need, not just point-of-care data. Existing data systems often capture only what brings someone into the healthcare system, missing the co-occurring social determinants of health that shape outcomes. Continuous, relationship-based data collection with the support of technology can surface a more complete and actionable picture that enables both better resource connection and effective advocacy.

Invest in AI literacy and critical capacity for the CHW workforce. Community health workers need both the practical skills to use AI tools effectively and the critical frameworks to evaluate how those tools are designed and deployed. Approaches that build competency while also developing CHW voice in governance and advocacy are critical to ensuring that the workforce shaping communities is not left behind as technology advances.

Build toward interoperability and sustainable models. For community-based organizations to achieve lasting impact through technology, they must be able to integrate securely with healthcare payer systems. Achieving interoperability opens pathways to revenue that sustains mission-driven work in ways that philanthropic funding alone cannot.

Shift the question from “can we?” to “should we?” Across sectors, the most important orientation toward AI adoption is not simply capability, but intentionality. Keeping the focus on how technology can better serve CHWs, and continuously asking whether each application advances their interventions, is the compass that keeps this work on the right path.

NationSwell op-ed: Predicting the Future of Work

Posted on Jacob Lepiarz and Allie Mahler

We are currently living through one of the most profound shifts in the history of work. As AI, automation, and other emerging technologies redefine jobs, skills, and career pathways wholesale, leaders across sectors are being called to meet these industry-wide undulations head-on and help shape what comes next.

That imperative is at the heart of NationSwell’s new Workforce Innovation Collaborative — a cross-sector effort designed to help leaders explore emerging workforce trends and co-design scalable solutions for a more future-ready and inclusive economy. Through shared learning, strategic dialogue, and collective action, the Collaborative aims to create the kind of trusted space leaders need to navigate uncertainty and create a future-ready workforce where every person has the skills, opportunities, and support to succeed.

To mark the launch of that work, NationSwell invited leaders from the Collaborative to respond to a shared prompt:

Which emerging signals are giving you the most optimism about the future of work right now? And where do you currently see the greatest opportunity to build a system that is more responsive to where work is headed next?

Although their responses reflect different vantage points, they converge around the common belief that the future of work will be shaped by how well leaders connect learning to real opportunity, pair innovation with inclusion, and design workforce systems that can adapt as quickly as the world around them changes.

Prompt: Which emerging signals are giving you the most optimism about the future of work right now? Where do you currently see the greatest opportunity to build a workforce system that is more responsive to where work is headed next?

“We are at an inflection point in the future of work, and I believe the greatest source of optimism and opportunity is in mastering the art and science of building truly responsive workforce systems.

The science is the strategic leveraging of predictive labor market intelligence. By shifting away from reactive measures, we can now leverage data and insights to anticipate skill demands driven by global trends. Our data provides the scientific rigor needed to pinpoint future talent shortages, standardize risk indicators, and replace guesswork with reliable, real-time insights, allowing us to accelerate our workforce investments across the globe.

However, the true opportunity — the art — lies in translating those insights and data into hyper-local execution that allows us to co-create with the communities we work in. This essential human-centered approach ensures our work doesn’t just fill a business gap, but actively builds equitable, transparent systems that deliver a net-positive impact in local communities. We achieve this by cultivating bespoke, long-term partnerships with community leaders, educational institutions, and nonprofits. 

Linking our global data-driven approach to local trust and co-creation is the systemic approach necessary to ensure our interventions foster equity and accessibility, building the sustainable, resilient workforce the future demands.”

— Courtney Williams, Global Workforce Development & Labor Market Intelligence, Google

“Across the Design and Make industries, I’m seeing promising workforce solutions that connect access, applied skills, and real hiring pathways. It’s no longer enough to train people on tools in isolation — what’s emerging now are integrated models that build capability in real workflows, validate those skills through industry recognized credentials, and link learners directly to opportunity. That’s how we ensure both students and experienced professionals can adapt and thrive as technology reshapes the future of work.”

— Kate Buchanan, Workforce Innovation & Investment Lead, Autodesk Foundation

“Right now, what gives me the most optimism about the future of work is the growing consensus that, as AI reshapes roles, human-centric skills — critical thinking, communication, and creativity — matter more, not less. It’s really important that optimism is matched with action in this moment, and through Barclays LifeSkills, our programs are helping people to develop these skills in order to differentiate themselves for current and future roles.

As we look at the workforce development sector, the greatest opportunity is to build a system that keeps pace with change by connecting learning to work earlier and more often, and by updating training as employer needs evolve faster. That means scaling employer-aligned earn-and-learn pathways — apprenticeships, fellowships, internships and project-based work — so learners graduate with an increased level of experience. It also means widening access to growth sectors, including AI-enabled roles and the skilled trades, where we continue to see strong demand. Through Barclays LifeSkills, we’re working across our partnerships to turn demand into clear routes to good jobs.”

— Deborah Goldfarb, Global Head of Citizenship, Barclays

“What gives me optimism is how clearly manufacturing and industrial skills are being redefined as both high-tech and people-driven. Advances in automation, digital tools and connected systems are changing work on the factory floor and at job sites. Realizing the full value of those advances depends on sustained investment in our people through skills-building, learning and clear career pathways. I’m also encouraged by how employers are engaging more intentionally with collaborators beyond their organizations. We’re witnessing stronger coordination among educators, workforce systems and local communities to ensure training keeps pace with technological advancement. This alignment — of innovation, skills and purpose — is a compelling signal that manufacturing can provide meaningful, fulfilling careers in a dynamic industry.

One of the greatest opportunities lies in modernizing workforce systems to evolve alongside the technologies shaping manufacturing. High schools, community colleges and regional training providers are critical anchors in this system, and we need to align more closely and dynamically with them, given that roles and skill requirements are changing faster than traditional training cycles can keep pace.

That means co‑designing training pathways that blend hands‑on experience with digital and technology‑enabled learning. It also means creating opportunities for continuous upskilling throughout a career. When workforce systems are built to adapt — rather than react — they not only prepare people for today’s manufacturing roles, but also for the future. They also help ensure the industry can remain innovative, competitive, and resilient over the long term.”

— Asha Varghese, Head of Corporate Social Responsibility, Caterpillar Inc. and President of the Caterpillar Foundation

“We are seeing a historic surge in systems readiness work at the local, state, and national levels. Stakeholders in the workforce ecosystem sometimes work in silos, but I’m seeing sustained interest in collaboration, especially across sectors. We are collectively examining what worked in the past to determine what must evolve for the future. 

There’s also growing consensus that career journeys of the future will be less linear. We know upskilling isn’t one-dimensional. It might mean deepening expertise to grow within an existing career trajectory, diversifying skills to transition into an adjacent role, or pivoting into an entirely new profession. A big opportunity right now is to reimagine our support systems to recognize this full spectrum of movement, ensuring that our infrastructure is as flexible as the workers it serves.”

— Diana Fischer, Senior Director, Workday Foundation

“One of the greatest opportunities is in building accelerated, more flexible pathways into the skilled trades that are tightly connected with employer needs. A more responsive workforce system should focus on expanding apprenticeships, investing in short-term training, and exposing students earlier to these fulfilling and well-paying careers.”

— Betsy Conway, Executive Director, Lowe’s Foundation

When and How AI Can Improve Grantmaking

Posted on by Brianna Provenzano

AI is moving fast, but grantmakers are rightly cautious. Funders are under pressure to move money more efficiently, learn faster, and support grantees better, all without adding risk, burden, or opacity to an already complex system. The question is no longer whether AI will touch grantmaking, but where it can actually add value—and where it shouldn’t.

On April 16, NationSwell invited philanthropic and impact leaders to take part in a conversation on the practical use of AI in grantmaking. The conversation featured ideas about when AI can meaningfully improve decisions and workflows and how to adopt it in ways that strengthen, rather than undermine, equity, accountability, and relationships with grantees. Some of the most salient takeaways from the discussion appear below:

Key takeaways:

Assess where AI meaningfully adds value across the grantmaking process. Rather than applying AI indiscriminately, organizations should take a step back and evaluate workflows end-to-end to determine where these tools can be most effective. A thoughtful, system-level approach can promote AI application in ways that enhance, rather than complicate, existing processes.

Use AI to streamline manual and error-prone grantmaking workflows. Financial due diligence can be a highly manual, time-intensive, and error-prone process, often involving spreadsheet-based analysis or visual review of financial statements. AI tools like Grant Guardian were developed to improve accuracy and efficiency in this specific workflow. 

Reinvest time savings from AI into deeper grantee engagement. Small grantmaking teams often face hundreds of applications, creating capacity constraints. AI can be used to support summarization, rubric-based pre-review, and prioritization to help manage this volume. The reduction in processing time, from hours to minutes, can allow staff to spend more time having meaningful conversations with grantees and improving the quality of their work. 

Recognize and normalize AI use among applicants and grantees. There is growing recognition that applicants and grantees are using AI to improve efficiency, particularly in drafting and responding to applications. When used thoughtfully, this can help reduce administrative burden, though differentiation still relies on the substance of proposals and outcomes.

Consider supporting grantees’ capacity to adopt AI tools and infrastructure. As AI becomes more embedded in workflows, there is an opportunity for funders to think about how grantees can access and use these tools effectively. Supporting this capacity, particularly through flexible, operational funding, can help organizations integrate AI in ways that enhance their work, rather than treating it as a one-off programmatic expense.

Develop and deploy AI systems with responsible AI principles. Specific principles should guide all AI adoption work in grantmaking, including safety and transparency, community-centered design, bias mitigation, human-in-the-loop validation, enterprise-grade security, and sustainability considerations. Start AI adoption through structured experimentation with clear guardrails, and consider empowering early adopters to test tools within defined parameters (e.g., “stoplight” approaches to acceptable use). These frameworks can also support clearer communication and transparency about how AI is being used.

Consider AI disclosure as contextual and relational: Whether and how to disclose AI use in grantmaking processes depends on organizational policies and levels of AI involvement. While practices may vary between organizations, especially as technology grows and with wider experimentation, keep a relational and trust-based mindset.

Maintain human oversight as a core requirement in AI-assisted workflows. AI is never a substitute for human judgment, and validation and verification by users must be built into the process. Being explicit about this, both internally and externally, can help reinforce trust, particularly in a field like philanthropy that is deeply relationship-driven and values human expertise.

Design for customization of AI tools to reflect different evaluation contexts. Grantmaking organizations assess financial health and programmatic fit differently, and AI tools can be configured with varying metrics, thresholds, and profiles to match those needs. This flexibility can also support more context-sensitive and equitable evaluation approaches; for example, assessing early-stage organizations differently than more established ones. 

Predicting the Future of Work: Using Data to Build More Inclusive Workforce Systems

Posted on by Brianna Provenzano

As AI and automation accelerate change across the labor market, predictive analytics offer powerful tools to anticipate which jobs, skills, and communities face the greatest risk – and where new opportunities are emerging.

On April 14, NationSwell convened a group of cross-sector leaders for a conversation on how data-driven insights can inform equitable training pathways, smarter investments, and workforce systems that are more responsive, inclusive, and resilient – ensuring workers are prepared for what’s next. Some of the most salient takeaways from the discussion appear below:

Key takeaways

Build workforce systems around capabilities, not credentials. A skills-first labor market only works if the underlying data infrastructure can recognize how people actually build skills through work, not just through degrees. When systems continue to privilege credential proxies over demonstrated capability, they miss large pools of qualified talent and reinforce inequities that workforce initiatives are meant to solve.

Pair predictive tools with better upstream data. Forecasting tools are only as strong as the signals they rely on. If workforce data continues to over-index on traditional credentials or lagging indicators, even sophisticated models will reproduce old blind spots; the real opportunity is to feed these systems richer, skills-based, real-world signals that surface emerging pathways earlier.

Invest in verified outcomes data, not just self-reported program metrics. Too much workforce decision-making still depends on incomplete or anecdotal outcome data. Expanding access to administrative wage data and other verified sources can help providers understand which programs are actually driving employment and earnings gains, and make more strategic decisions about what to scale, refine, or retire.

Use labor market data to map mobility, not just demand. It is not enough to know which jobs are growing. More useful systems help workers and practitioners understand how people can move from one role to the next based on shared skills, adjacent occupations, and realistic transition pathways, especially in a labor market where workers will increasingly need to pivot across sectors over time.

Treat durable human skills as core infrastructure. As AI and automation continue to reshape tasks, foundational capabilities like problem-solving, judgment, adaptability, collaboration, and communication are becoming more valuable. Technical requirements will keep evolving, but these underlying skills are what allow workers to remain resilient and mobile across changing tools, roles, and industries.

Redesign learning environments for experiential learning, not just memorization. Traditional teaching methodologies are increasingly challenged in a labor market where workers are expected to interpret information, make decisions, and adapt in real time. Experiential learning where people must apply knowledge, navigate ambiguity, and solve real problems better prepares learners for a world in which execution is increasingly automated and judgment is the differentiator.

Center the learner’s lived experience when designing workforce pathways. Workforce systems often default to employer demand signals and institutional priorities, but durable pathways require equal attention to how individuals actually make decisions. People choose careers based on identity, values, belonging, perceived risk, and developmental stage so the strongest systems help learners navigate options rather than simply presenting them.

Avoid replacing one rigid pathway with another. As enthusiasm grows around alternatives to four-year degrees, there is a risk of steering lower-income learners into workforce tracks while more privileged peers retain access to broader optionality. The goal is not to substitute “college for some, training for others,” but to build multiple high-quality pathways that preserve dignity, mobility, and long-term choice across backgrounds.Reframe middle-skill and nontraditional career paths as real engines of mobility. Many high-demand roles outside the traditional college track now offer strong wages, lower debt burden, and meaningful advancement potential, yet outdated perceptions still diminish their value. Shifting both rhetoric and practice to put career and college readiness on more equal footing is essential if workforce systems are going to reflect today’s economic realities.

Cisco | Skills-to-jobs at scale

Cisco | Skills-to-jobs at scale

How Cisco Networking Academy is transforming the lives of learners

The idea for Cisco Networking Academy was born in 1997. Cisco employees returned to an under-resourced school where they had donated state-of-the-art networking equipment. They were excited to see how students and educators were being empowered by the technology. Instead, they found the equipment sitting unused. The lesson learned that day was that technology alone is not enough; without the knowledge and skills to use it, even the best equipment’s potential will go untapped. 

Cisco recognized that for networking technology to truly expand and thrive, there needed to be a workforce capable of installing, configuring, and maintaining those networks. There was a critical skills gap: educators and students lacked the training to leverage the new technology, and there was no established pathway to build that expertise at scale.

Beyond just technical skills, Cisco also saw an opportunity to transform lives by providing inclusive access to technology education. Cisco sought to use its own technology and vast networking expertise to create clear pathways for both new learners and those reskilling or upskilling, ensuring they become prepared for the jobs of today and tomorrow. Thus, Networking Academy was launched.

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Responsible Use of AI for Social Impact

Responsible Use of AI for Social Impact

AI is rapidly reshaping how the social impact sector delivers on its mission. Yet as adoption accelerates, many organizations lack the governance needed to manage risk and fully realize AI’s potential.

Developed by NationSwell in collaboration with IBM, Responsible Use of AI for Social Impact is a practical playbook designed to help organizations of all sizes adopt AI ethically, safely, and effectively. Drawing on insights from leaders across the field, the guide offers real-world frameworks, case studies, and actionable steps to move from experimentation to responsible application.

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Impact Next: An interview with One Mind’s Kathy Pike

Posted on by Brianna Provenzano

At a moment of inequality and division, who is advancing the vanguard of economic and social progress to bolster under-served communities? Whose work is fostering the inclusive growth that ensures every individual thrives? Who will set the ambitious standards that mobilize whole industries, challenging their peers to reach new altitudes of social impact?

In 2026, Impact Next — an editorial flagship series from NationSwell — will spotlight the standard-bearing corporate social responsibility and impact leaders, entrepreneurs, experts, and philanthropists whose catalytic work has the potential to shape the landscape of progress amid urgent need for social and economic action.

For this installment, NationSwell interviewed Kathy Pike, President and CEO of One Mind. Here’s what she had to say:

Ray Hutchison, Vice President of Community Engagement, NationSwell: What brought you to the field that you’re in now? Was there an early moment or a formative experience that helped shape how you arrived at this role, or your leadership?

Dr. Kathy Pike, President and CEO of One Mind: Before I became CEO of One Mind, I spent 35 years as an academic, as a professor at Columbia University in the Department of Psychiatry and the School of Public Health. Academia is a kind of priesthood, and moving from a full-time faculty role into leading a nonprofit is not a transition most academics make. So something had to shift for me, and it really came down to a couple of moments.

About ten years ago, I was invited by a large multinational company in New York to give a talk on mental health and well-being. I went in for an in-person prep meeting, and they told me there was one condition: I couldn’t say “mental health” or “mental illness.” Those terms were considered too alienating, too stigmatizing. They wanted the talk framed entirely around stress, coping, and resilience.

That stayed with me. The discomfort around even naming mental health felt incredibly restrictive, and I remember giving those kinds of talks and feeling like progress was painfully slow.

Then, a few years ago, after COVID, I was invited back to that same company to give a similar talk. When I walked in, there was a large sign on the door that read something like: “Feeling anxious? Depressed? Want to talk? I’m a mental health ambassador.”

That was a crystallizing moment for me. It was clear we had entered a genuinely new era, one where people were paying real attention to mental health and well-being. And with that shift came a huge opportunity to bridge what we know from rigorous science with what is actually happening in workplaces and communities.

I have always been deeply committed to translational science, to the question of how we take what we know and get it into the hands of people who can use it. That moment made it clear to me that the bridge between science and practice needed to be stronger, and that I wanted to lean fully into building it. When the opportunity came to join One Mind, it felt like exactly the right place to focus that work, to help ensure that what reaches people is grounded in strong science and actually makes a difference in their lives.

Hutchison, NationSwell: What is the “North Star” of your leadership style, and how has it changed over time? What is it about the way that you lead in the space that makes you an effective leader?

Pike, OneMind: Early in my leadership career, I was very focused on building a team that could deliver the work with excellence. I approached leadership in a very task-oriented way. When I thought about hiring or bringing people onto a team, it was largely about finding the right people to get the job done.

And that’s still essential. The work does need to get done, and it needs to be done well. But over time, my thinking about leadership has evolved, and I now see leadership as much more about leading with people. It’s about understanding who individuals are so that they can do the work they’re best suited for. The work they approach with energy and passion, and that allows them to operate at their highest level.

So the question becomes: How do you create the right match between the work that needs to be done and the person who’s doing it? Because when someone is working in an area where they feel alive, engaged, and capable of excellence, they’re simply going to do better work. It’s a subtle shift; the goal of delivering the work doesn’t change, but it changes how I think about leadership, especially when something isn’t working. It changes the questions I ask and the adjustments I consider.

More recently, when we think about building teams, I’ve come to see it less like assembling pieces of a pre-made puzzle and more like building with Legos. You may have an idea of what you’re trying to build, but people bring different strengths and perspectives, and the organization becomes stronger when you build around those differences. When people feel fulfilled and are working in areas they care about and feel strong in, the quality of the work improves as well.

Hutchison, NationSwell: What are some of the programs, signature initiatives, or some facets of the work that you’re doing at One Mind that feel particularly cut-through?

Pike, OneMind: I knew I wanted to lead an organization focused on translating science into practice, and One Mind felt like the right fit for a couple of reasons. For one thing, there’s a deep commitment to grounding the organization in science, which aligns closely with how I believe the mental health field needs to move forward. But there’s also a more personal reason: My paternal uncle was diagnosed with schizophrenia when he was around 20 years old, before I was born. As a child, I used to visit him with my father on Sundays at Rockland State Psychiatric Hospital, where he lived as a ward of the state for most of his adult life. But more than living there, he languished there. It wasn’t because people didn’t care. There were many deeply committed professionals working at the hospital, but the treatments and the understanding of serious mental illness at the time were very limited. I remember riding home after those visits thinking, we have to be able to do better than this. I’m sure that experience shaped my path toward becoming a clinical psychologist, and ultimately joining One Mind.

One Mind was founded by Shari and Garen Staglin after their son, Brandon, was diagnosed with schizophrenia. In contrast to my uncle’s experience, Brandon is thriving today. He serves as our Chief Advocacy and Engagement Officer, and the opportunity to work alongside him was an important part of my decision to join the organization. In a certain poetic way, it feels like being able to say, we’re doing better now, Uncle Henry. 

Of course, a diagnosis like schizophrenia is not unlike other serious health conditions where you can do everything right and still face difficult outcomes, but we can do far more now than we once could to help people thrive. One Mind’s commitment to integrating people with lived experience in all our programming under Brandon’s leadership, is enormously valuable and meaningful and ensures that the priorities and perspectives of those we aim to serve shape what we do.

What excites me every day is the way our work pushes the field forward across three core pillars: The One Mind Rising Star Academy supports researchers pursuing bold, breakthrough ideas in neuroscience to better understand the brain and develop new interventions; the One Mind Accelerator brings investment, technology, and innovation into mental health to build scalable, sustainable solutions; and One Mind at Work takes those insights into workplaces, helping organizations rethink how work itself supports mental health and well-being.

Across all three, the goal is the same: to demonstrate that better is possible, and to help make that future real.

Hutchison, NationSwell: What are the trends that you’re currently seeing that are giving you hope?

Pike, One Mind: Mental health is definitely having a moment. For a long time, nobody wanted to talk about it. Now everyone does. The advances in science and technology, the innovation, and the level of investment coming into this space fill me with genuine hope and make me deeply optimistic about what lies ahead.

But I’ll be honest about what keeps me up at night. All of this attention may not translate into real impact. There’s a real risk that good intentions don’t actually achieve their aims, and if that happens, the naysayers will say: we invested in mental health, we funded research, we built workplace programs, and nothing changed. They’ll throw up their hands and walk away. That concerns me deeply, because I believe we have a genuine opportunity right now, and I don’t want to see us squander it.

Here’s the challenge: too much of the work in mental health is underdosed. Think about strep throat. A doctor prescribes a very specific antibiotic at a very specific dose for a very specific number of days, because that is what produces results. In mental health, we have evidence-based strategies that similarly require a certain level of frequency and intensity to work. But too often we are asked to make do with less. It’s like telling a doctor to cut the prescription in half and then wondering why the patient isn’t getting better.

At One Mind, we think about this constantly. Good intentions are not enough. We are committed to translating science into programs that are designed and scaled for real impact.

And here is what I keep coming back to: we are living in a moment of extraordinary possibility. The science is stronger than it has ever been. The cultural openness is wider than it has ever been. The investment is growing. If we do this right, if we stay grounded in evidence and committed to reaching the people who need it most, I believe mental health will lead the way to a broader and more expansive understanding of what it means to be healthy. Not just mentally healthy, but fully, wholly healthy. That future is within reach, and that is what drives me every single day.

Hutchison, NationSwell: How are you thinking about AI in this moment? Is there a future where it’s a force for good? And if so, what does that look like? How do we get there?

Pike, One Mind: It’s not a future where AI becomes a force for good; it’s already here. AI is power, and it is potential. In many ways, it’s like water or money: what matters is how you use it.

In mental health and well-being, AI offers tremendous opportunity. Population-level data show that the burden of untreated mental health conditions is enormous, one of the leading causes of disability worldwide. And the vast majority of people with these conditions, whether in high-income countries like the United States or in lower-income countries and communities in the US, are not receiving treatment.

There are many reasons for that. Stigma remains a barrier, access to care is limited, and AI can help address both. It can expand access to information and support in ways that feel more private for people who are hesitant to seek care openly; it can help standardize aspects of care and reduce administrative burdens, like documentation and record-keeping, that take time away from clinicians. In those ways, AI has the potential to dramatically increase access and improve how mental health care is delivered.

But there is also real risk. We’ve already seen cases where people turn to tools like ChatGPT or other AI systems for mental health support, even though those systems aren’t trained to manage clinical risk. There have been tragic outcomes, which underscores how important it is to approach this thoughtfully.

We are addressing the issue of AI and mental health across all our programs. What is ethical use of AI for our One Mind Rising Star Award researchers? How can we responsibly support companies that are creating AI-enabled interventions in our One Mind Accelerator? How do we bring best practices to this new world of work for the companies we work with through One Mind at Work. Workplaces are all grappling with what AI means for their industries and their workforces. Jobs will change. Some roles may disappear, and new ones will emerge. All of us will be working differently in the years ahead.

So from my perspective, AI brings enormous opportunity and enormous risk. Our future will be shaped by the choices we make now. We need to be intentional about building AI in ways that advance our shared aspirations: improving the human condition and strengthening people’s health and well-being. And if we see risks emerging, we have a responsibility to act in ways that reduce harm and optimize good outcomes.

When there is choice, there is risk. But there is also the possibility of getting it right.

Hutchison, NationSwell: What are some peer leaders out there that you admire, particularly leaders in roles at other organizations, or companies, or nonprofits whose work you hold in high esteem? Is there anybody else out there that we should be pointing a finger in the direction of as another great example of a human being or an organization?

Pike, OneMind:  One organization that serves as a North Star for me is the Kennedy Forum, founded by Patrick J. Kennedy. I believe Patrick is the most important and effective national spokesperson on mental health today when it comes to advocacy, parity, and advancing solutions that matter for society as a whole. The organization’s CEO, Rebecca Bagley, is also an incredibly thoughtful, strategic, and compassionate leader who is helping carry that mission forward.

Patrick’s leadership was especially top of mind for me recently. This past Monday, he convened a major gathering at the National Press Club that brought together mental health leaders and policymakers. The event opened with an interview featuring his cousin, Secretary Robert F. Kennedy Jr.

Patrick and Secretary Kennedy have very little in common politically, and Patrick acknowledged that directly. As he closed his opening remarks, he said many people were probably wondering how he could stand on that stage and introduce someone whose political views he often disagrees with. But he explained that he was there because the Secretary will help shape the national agenda on mental health and addiction. And those issues matter to everyone. Patrick spoke about how both of them understand, through their own family experiences, what mental illness and addiction can do to individuals and families. He said, essentially, that they may sit in different political camps, but on this issue they share a mission.

For me, that moment captured something powerful. Patrick doesn’t just say that mental health is bipartisan, he treats it as a universal issue and leads accordingly. He’s willing to partner with people he may disagree with in other arenas because the mission matters more. One of my mentors used to say, “Keep your eye on the prize.” That’s exactly what Patrick is doing.

Because of that leadership, he and Rebecca and their team have helped drive real progress, including the Action for Progress on Mental Health and Substance Use — a framework that, if fully implemented, could have tremendous benefits for people across the country. I have enormous respect and admiration for Patrick’s ability to lead with that kind of focus and commitment.

Hutchison, NationSwell: What is the North Star of your leadership?

Pike, OneMind: I think about the North Star of my leadership as a three-legged stool of values: dignity, purpose, and joy.

As I make decisions about where to spend my energy, whether in my leadership, my social life, or my philanthropic work, those three values are the ones that guide me. I want to feel a sense of dignity, purpose, and joy in the way I engage in the world. If something lacks those things, if it doesn’t feel purposeful, if it doesn’t bring joy, or if there’s an indignity in it for myself or for others, then I know it’s not where I belong.

We live in a world with a frenetic energy that can pull people away from what they care about most. It’s easy to become disconnected, to drift from your center without even noticing it’s happened. But when we are intentional about keeping our values close, we actually have tremendous power to shape the world around us. It shows up in the decisions we make every single day, the small ones as much as the large ones.

So for me, dignity, purpose, and joy are not abstract ideals. They are the stars I use to navigate my leadership and to choose the work that is worthy of my time and energy.

Q1 2026 Social Impact Trends

Q1 2026 Social Impact Trends

TREND REPORT
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NationSwell’s quarterly trend spotter provides impact professionals with visibility into the most noteworthy, timely, and material shifts in the field. For Q1 of 2026, our report explores the following six trends:

  1. Minneapolis ICE raids spark employee activism and minimalist business response
  2. OBBBA precipitating shifts in philanthropy, new corporate approaches
  3. Nonprofit anxiety around operational risks runs deep amidst legal and financial pressure
  4. AI adoption outpacing workforce readiness
  5. ESG notches a legal victory while confronting growing antitrust warnings
  6. Sustainability compliance remains a moving target for companies
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Q4 2025 Social Impact Trends

Q4 2025 Social Impact Trends

TREND REPORT
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NationSwell’s quarterly trend spotter provides impact professionals with visibility into the most noteworthy, timely, and material shifts in the field. For Q4 of 2025, our report explores the following six trends:

  1. Food security draws mainstream attention amid government shutdown
  2. AI-driven layoffs hit tech and service industries, but overall employment impact remains modest
  3. Philanthropies and nonprofits are investing more in AI, but governance needs to catch up
  4. Political leaders continuing pressure on corporate leadership and civil society
  5. Sustainability efforts continue, but more quietly and with less accountability
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Five Minutes with… IBM’s Sara Link

Posted on by Brianna Provenzano

As artificial intelligence reshapes how institutions operate, many nonprofits and public-sector leaders are grappling with a pressing question: How can AI be deployed responsibly and equitably in service of the public good? 

At IBM, that question isn’t theoretical — it’s central to how the company designs, governs, and advances its AI strategy across sectors. In a new resource developed in collaboration with NationSwell, Responsible Use of AI for Social Impact, IBM outlines a practical roadmap for responsible AI adoption that moves beyond high-level principles and into actionable guidance for organizations navigating capacity constraints, ethical considerations, and rapidly evolving technology. The report emphasizes AI literacy; governance as an enabler instead of a blocker; and a clear focus on augmenting, rather than replacing, human capability. 

For this installment of Five Minutes with…., NationSwell spoke with Sara Link — IBM’s Global Head of Employee Impact — about what it takes to operationalize trustworthy AI at scale and why government and social sector leaders must be equipped not just with tools, but with the systems and confidence to use them well.

We asked Sara how IBM is reframing responsible AI from a compliance exercise into a performance advantage, what meaningful AI literacy actually looks like inside an organization, and what wild success for ethical AI adoption could look like five years from now. 

Here’s what she had to say:

NationSwell: What do you see as most distinctive about IBM’s approach to responsible AI, particularly for nonprofits and social impact organizations that face capacity constraints?

Sara Link, Global Head of Impact at IBM: It’s encouraging to see so many responsible AI principles circulating right now; that level of focus and intentionality is important. At IBM, our approach centers on making AI practical, understandable, and genuinely useful in everyday work. Our belief is that AI should help people do their jobs better — not replace them, overwhelm them, or create confusion.

One of the key insights in the report is that responsible AI has to be realistic for organizations with limited time, staff, and capacity. Nonprofits don’t have extra resources or margin for error, and in many cases they don’t have deep technical expertise in-house. So responsible AI can’t just live in a policy document — it has to be built in a way that reflects those constraints. That means designing tools and governance structures that are usable, accessible, and practical from the start, so organizations can adopt them confidently and integrate them into their daily work.

NationSwell: Augmenting rather than replacing human capability is central to IBM’s view of AI. Can you share an example of what that looks like in practice, either at IBM or with partners?

Link, IBM: In practice, we think about AI as something that helps bring work to life — whether that’s surfacing information, spotting patterns, or saving time on repetitive tasks. But at the end of the day, people still make the final decisions, especially when judgment, fairness, or context matter.

At IBM, for example, internal tools like AskHR or AskCSR help employees find answers more quickly and efficiently. They streamline the process, but they don’t replace accountability. People are still responsible for what happens next. The goal is to enable better, more informed decisions — not to obscure or complicate them.

NationSwell: The report emphasizes foundational AI literacy. What does “good” AI literacy look like inside an organization, and how does that translate into better outcomes?

Link, IBM: Good AI literacy means people aren’t afraid of the tools, but they also don’t blindly trust them. It shows up when leaders and staff understand what AI can support and where human judgment still needs to step in.

You can hear it in the kinds of questions people feel comfortable asking: Does this actually make sense? Should we double-check this before acting on it? For example, in a nonprofit using AI to screen applications or triage services, literacy shows up when staff know how to review AI recommendations, recognize when something doesn’t feel right, and understand that the final decision rests with them.

That kind of literacy leads to better mission outcomes. It reduces errors, helps guard against bias, and builds trust with the communities being served rather than simply automating decisions without oversight.

NationSwell: How does the report reframe responsible AI governance as an enabler rather than a blocker? What is one practical first step an organization can take?

Link, IBM: When you lay out clear rules, it actually becomes easier to move forward. Clarity helps people understand what’s acceptable and what’s not. Without that clarity, uncertainty can cause hesitation or lead organizations to avoid using AI altogether. One of the strongest findings in the report is that governance doesn’t slow adoption; it accelerates it by removing ambiguity.

A practical first step is to build a simple pause point into an existing workflow — a moment where a human reviews and signs off before an AI-driven decision affects someone. It doesn’t have to be complicated. It can be as straightforward as asking: Does this outcome make sense? Would I be comfortable explaining this decision to the person it impacts?

Over time, those small, repeatable checks turn responsible AI from a written policy into a daily habit. And that’s what enables organizations to scale AI safely and confidently.

NationSwell: If you could change one thing about how funders currently approach AI in the social sector, what would it be?

Link, IBM: First, it’s critical for funders to recognize the importance of investing in organizational capacity; that’s the foundation. I would encourage funders to focus not just on funding AI tools, but on supporting people’s ability to use AI well over time.

Investing in technology alone doesn’t create impact if organizations aren’t prepared to work with it. Right now, many nonprofits are expected to figure this out on their own. They may receive funding to pilot AI, but not necessarily the support for training, governance, or long-term learning that makes those tools effective and safe.

Through IBM’s AI for Impact program, which we launched in late 2024, we’ve brought nonprofits together to share how they’re using AI, what questions they have, and where they see opportunity. A recurring theme has been the need for funding that supports both the right tools and the training required to use them responsibly. And research from the IBM Institute for Business Value shows that skills are evolving rapidly — 57% of executives surveyed expect today’s skills to become outdated by 2030. That pressure is even more acute in the social sector, where resources are already stretched.

The funders making the biggest difference are supporting AI readiness, not just adoption — investing in training, shared standards, and giving teams time to learn and adapt, not just deliver. I’d also encourage funders to make their grantees aware of programs like AI for Impact. Many of these resources are free and can help organizations and their leaders build the knowledge and confidence they need to prepare for what’s ahead.

NationSwell: If responsible AI adoption truly takes root, what might wild success look like for the sector five years from now?

Link, IBM: The vision of success, to me, is that AI makes work easier and fairer — not more stressful or confusing. If we can eliminate that sense of overwhelm and instead empower people to use their skills more fully, that would be a meaningful outcome.

In that future, people would understand the tools they’re using and feel confident explaining the decisions those tools inform. AI would help nonprofits do more good without eroding trust or weakening human connection. Most importantly, technology would support organizations in serving communities better — not get in the way.

That’s what wild success looks like: better outcomes for communities, more efficient pathways to get there, and trust and connection preserved throughout the process.

NationSwell: What have you personally learned or found inspiring as you’ve helped lead this work around AI? How has this journey informed your broader leadership in the corporate impact space?

Link, IBM: For a long time, I’ve focused on capacity building for nonprofits and on how the corporate sector and funders can partner more closely with them, providing the right level of support so they can better serve their communities.

What’s been most inspiring lately is the openness I’ve seen when nonprofits come together — the willingness to share ideas, build relationships, and solve challenges collaboratively. There’s a real energy in the room when leaders from across sectors are learning from one another and exploring what’s possible.

I saw that firsthand at a recent conference after speaking on this topic: A healthcare employee approached me and shared that she and her colleagues had been experimenting with AI tools to solve internal challenges, and they were eager to bring leadership into the conversation to explore the potential more formally. She ended up connecting with another healthcare system that was further along, helping to broker a conversation between them.

That kind of openness — being curious about what’s out there and willing to imagine what could be possible — is what excites me most. It’s that spirit of shared learning and forward momentum that will ultimately drive meaningful change.

NationSwell: Is there anything else from the report — or from your leadership perspective — that you’d like to share?

Link, IBM: As someone who doesn’t necessarily have an engineering or a technical background, what’s been especially inspiring to me is realizing that you don’t need deep technical expertise to ask the right questions or to begin this journey of continuous learning. You don’t have to be an engineer to engage meaningfully with AI.

Personally, this experience has shown me how much further we can take our work by building our skills, staying curious, and asking thoughtful questions. When we approach AI as a tool for strengthening connections and building stronger partnerships — rather than something intimidating or purely technical — it becomes incredibly energizing. That mindset has been one of the most exciting parts of this journey for me.