Subscribe
Share
Share
Embed
Business is an unlikely hero: a force for good working to solve society's most pressing challenges, while boosting bottom line. This is social purpose at work. And it's a dynamic journey. Purpose 360 is a masterclass in unlocking the power of social purpose to ignite business and social impact. Host Carol Cone brings decades of social impact expertise and a 360-degree view of integrating social purpose into an organization into unfiltered conversations that illuminate today's big challenges and bigger ideas.
This transcript is produced using transcription software and reviewed for quality. Despite our best efforts, some passages may be incomplete or contain errors due to audio quality or software limitations.
Carol Cone:
I'm Carol Cone, and welcome to Purpose 360, the podcast that unlocks the power of purpose to ignite business and social impact. Today, we're tackling one of the biggest questions facing purpose-driven leaders: as AI transforms the way we work, what ensures it strengthens, not weakens, the values, indeed the humanity, that defines our organizations? Many leaders view AI primarily through the lens of efficiency, productivity, and innovation. Those benefits, of course, are real, but AI also raises larger questions, like what values guide its use, who benefits from its deployment, and how do we ensure technology serves people rather than the other way around? Technology, no matter how advanced, cannot become a substitute for human judgment, moral responsibility, or human flourishing. And as AI expands its capabilities, organizations need a stronger compass, not a weaker one. Simply put, and what we've been discussing for years, is that purpose provides that compass, because without a clear purpose, AI can accelerate the wrong priorities just as easily as the right ones.
Joining me today are two remarkable thought leaders and longtime collaborators: Kristian Merenda, one of my partners at Carol Cone ON PURPOSE and co-author of our new purpose and AI guide, and Balaji Ganapathy, a frequent contributor to Purpose 360. He's founder and CEO of Social Positive and former Chief Social Responsibility Officer at Tata Consultancy Services.
Together, we'll explore why purpose should be the operating system for AI, not something forgotten but something primary, how leaders can avoid purpose drift, what it takes to build an AI-ready culture, and why the future belongs to organizations that combine technological innovation with human judgment. If you're wondering how to lead responsibly, how to use your purpose as a guide for your AI journey, and competitively, this conversation is for you. So let's get started.
Welcome to the show, Kristian and Balaji.
Balaji Ganapathy:
Thank you, Carol, and Kristian. It's a real pleasure. I've always admired Carol Cone ON PURPOSE and what you've been building for years, and especially the opportunity to unpack the purpose AI guide that you've given to the community. I think it's exactly what the sector needs right now. So happy to be here.
As Carol said, I'm Balaji Ganapathy, CEO and founder of Social Positive, an AI-native social impact intelligence and advisory firm. In my previous life, I was a practitioner and chief social responsibility officer at TCS, where I led social impact across fifty-five countries, investing about a hundred million dollars each year and reaching about thirty million people through our work. Pleasure to be here.
Carol Cone:
Thank you, Balaji. Kristian, we've worked together for so many years. Tell a little bit about your background, and then why you penned this very important guide.
Kristian Merenda:
Thank you, Carol and Balaji. It's such an honor to be here with the both of you today.
One of the great privileges of my life has been working with you, Carol, on and off as your collaborator for the past 25 years. We started by transforming Cone One, building out nonprofit citizenship, consumer brand citizenship, and corporate citizenship capabilities, all the predecessors to the purpose strategy that we champion today. Through publishing, industry collaborations, speaking, and teaching, we helped define those for the sector. We wrote new research, a handful of UN and Harvard Business School case studies, and our first book together, Breakthrough Nonprofit Branding. Spoiler alert: the sequel is due out this fall.
Then at Edelman, when our paths crossed again, we helped take that concept of purpose global, teaching their staff around the world and steering their research, including the Trust Barometer. And now, with our merry band back together at CCOP and our Purpose Collaborative, we're driving change once again, always as co-creators with our incredible clients, leading the charge with purpose and AI.
Carol Cone:
That is amazing. So you can see, listeners, that we have two extraordinary professionals here, and they have one very common characteristic besides being lovely people: they are curious. They are curious, they are leaders, and they are teachers. And that's why today I've brought them to talk about purpose and AI. As we all know, AI is transforming how we work, but purpose must guide why we work. A lot of people talk about AI as technology and purpose as the humanity. So today we're going to talk about how they can work in harmony with each other. Kristian, how do you define purpose?
Kristian Merenda:
When it comes to purpose, I define it the same way we do at CCOP: purpose is an organization's reason for being beyond profits, grounded in humanity. For a company, it's their why beyond profits. It's always aligned with meaningful benefit for those it affects, like colleagues, customers, and community. And for a person, it's their why. Mine is to leave everything better than I found it.
Balaji Ganapathy:
Beautiful answer. I'll double-click on that. I think purpose is an organization's answer to the question, why do you exist, when nobody is watching, when there is no great press release, no annual report, no recognition. What you live with in the organization, what is the operating system of the organization, that is what, to me, is purpose. Everything else, including AI, is an add-on.
Carol Cone:
Love that. That is really, really wonderful. So if purpose stands for why an organization exists, is it more important than ever in this age of AI?
Kristian Merenda:
I think it is, because the two forces aren't mutually exclusive. Purpose helps define the focus and the filters for AI. It helps organizations say what they stand for and understand why they should organize around it. And AI, when countered with a purpose governance layer paired with humans in or above the loop, has the potential to unlock incredible advancements for those who deploy it well. AI is certainly proving to be a game-changing factor, leveraging insights from large data sets that would have been unimaginable even ten years ago.
Together, they're incredibly powerful. Separately, purpose is always going to be a terrific driving force, but without purpose as a driving force for AI, it can definitely steer off the road.
Balaji Ganapathy:
I like that framing. Purpose tells you what is worth doing. AI helps you do it at scale. The tension comes not between them, but when you deploy one without the other. AI without purpose is speed without direction. You don't want to get in a car and go nowhere, you want to have a destination. But conversely, purpose without AI, especially in today's age, is conviction without reach. You know what's the right thing to do and why you exist, but are you able to fulfill that in the best way possible using the resources available?
Carol Cone:
So I want to start building the case, because prior to the big AI boom, we still did not have every company embracing purpose. We had the prescient leaders, then we had a middle stage where some had stated it, many had stated it, but not that many had really activated it. So how can we, as practitioners, and everyone listening, make the case to senior management, to the C-suite, who are all thinking about how they're investing, how they're scaling, and how they're educating? How do we convince them that purpose is more important than ever before?
Balaji Ganapathy:
It's an easy case to make, because the fundamental question you want to ask is: what is the value that you want to create in the world, and how do you want to bring it to life? The value you want to create in the world comes through understanding your purpose and living your purpose. How you bring it to life comes through the tools and the systems that you use. So it's a question of being really purposeful about going to the root of why you exist, how you want to bring it to life, and then applying AI on top of it.
You hit the nail on the head, Carol. The way most companies are going about it is the reverse. Boards and executives get excited, they want to introduce AI, and they make it available to the organization, then mandate it. It becomes a compliance model of, here's AI, use it, as opposed to recognizing that this isn't a technology implementation, it's a culture implementation, because you're asking people to shift how they think and operate. You have to give them the space to experiment, to fail, and then to learn. That's the biggest takeaway. The companies that aren't set up to do that are just firing people and treating it as an efficiency play instead of an innovation play. They're going to come back to the drawing board and redo this.
Carol Cone:
Kristian, can you build on that?
Kristian Merenda:
One of the pieces that Balaji's speaking to, when it comes to purpose and its embedding, has to do with employees. There's a counterintuitive part to thinking about AI and transformation with employees: the potential risk and opportunity in your AI transformation is present with every employee. The person who could sink your AI program, due to fear or hesitancy, may be the same one who can help it succeed. Which one you get depends on how your AI transformation treats them and how purpose is embedded.
I like to think of it as an equation: employee fear, plus AI and purpose abandonment, equals quiet resistance. And that quiet resistance kills AI programs from the inside, because the tools sit unused. It's understandable and easy to relate to, because there's a growing group operating from a position of fear: fear of the unknown, for those who haven't touched the tools and have only met AI through layoff headlines, or fear of the known, for the heaviest users who can see exactly which tasks the machine already does but haven't been told what's left for them.
Both fears have the same medicine: purpose and participation. Giving employees an invitation to play a determining role in what gets automated and what stays human about their jobs with AI is the way to be employee-centric. Whether they test the tools before rollout or own pieces of the program once it's live, it means the business treats people as co-creators rather than cogs.
Carol Cone:
I know that in the purpose guide you wrote, Kristian, you talk about humanity, values, and ethics. I'd love both of you to chat about what this conversation could sound like in the C-suite, because my fear is that there's so much cacophony about being at the head of the pack, being first, having enough data centers to power all the electricity, that it's drowning out the ethics, the values, the purpose, the humanity. So how can we have this conversation?
Balaji Ganapathy:
Boards don't respond to frameworks, they respond to data, real evidence, and stories. The data shows that the half-life of a company in the S&P 500 or the Fortune 500 is about 14 years today. It was about 50 years in the 1950s. So if you want to be on the board of a company that exists beyond 2035 or 2040, the question isn't whether you need to be purposeful, that's a given. You need to understand what long-term value creation means, and that comes from doing what you say.
I don't subscribe to the view that values are written on the walls of a company. To me, values are what you do on a day-to-day basis, the behaviors your employees and leaders exhibit. The question about values and ethics comes down to what you practice today, because AI is only going to amplify that. If you're making decisions based on short-term returns instead of staying alive and thriving and creating both shareholder and stakeholder returns in the long term, then that's what your company is going to practice. AI is going to accelerate whatever decision or behavior you exhibit. So understand what value you're actually living today. If you're not living what you say in your headlines and your charts, and it's something different, that's what's going to manifest, and AI is going to accelerate it at a pace you've never seen before. So fix internally what you're measuring.
The story part I mentioned, Carol: one of the greatest changes I saw in my ten years or so in social impact leadership at TCS was when we brought real beneficiaries of our programs into the boardroom to present, because it shifted from an obligation to an aspiration. Until then, it was an obligation, a responsibility to do the right thing. But when you see who you're empowering, it stops being something you do to something that enables them, and the aspiration is how you make that happen. It's the same with AI: purpose gives you the aspiration, and AI gives you the accelerant.
Kristian Merenda:
I love that. And when you said "amplify," Balaji, it reminds me of my favorite analogy for this: thinking of AI like an amplifier on a guitar. It doesn't change the note you play, it makes whatever you play a whole lot louder. If the note is clean, the amp makes it sound great. But if the note's off, the amp makes the wrong note drown out the room.
Organizations work exactly the same way. If your purpose and values are clear and you actually live them day to day, AI makes you more effective at exactly what you're good at, freeing up time for human-centric activities like building relationships, creative problem-solving, and reaching new audiences. And if there are say-do gaps, AI makes those louder too. A system is only as good as the purpose that's driving it.
Carol Cone:
We've talked about the power of purpose to truly humanize and guide the organization. Kristian, in the guide, you talk about purpose drift. What is purpose drift, and what's the risk if a company starts drifting? What happens to their culture and their AI transformation, or lack thereof?
Kristian Merenda:
The first thing I should mention is why we made the guide, and then I'll talk about purpose drift. When organizations are rolling out AI, they need help answering the right questions and assembling the human talent and information they need to train the models, so that if they're learning from great use cases, they can maximize its potential. The guide helps leaders avoid purpose drift and ask how their organizations are adopting the technology. They should ask themselves: are they leading with tech first or people first? Is the pull toward efficiency starting to crowd out the most important human part of the work? And are they beginning with the end in mind, with purpose, values, and strategic priorities as the driving forces?
Most companies are going to end up with roughly the same tools from the same handful of vendors, which means general AI technology use is quickly becoming a commodity. What's needed is the discipline to deploy it in a way that differentiates. That's what the guide is all about.
Purpose drift has to do with the strategy, operations, decisions, and eventually the money pulling away from an organization's reason for being, due to poor AI deployment. People often picture drift as some off-brand marketing copy or messaging gone wrong. We can think of bad copy as the smoke, but the real focus should be on the fire, which is the strategy and operations run amok due to the drift. It's hard to spot while it's happening. Nobody wakes up and decides to abandon their purpose and strategy. It happens when a tool gets adopted for speed, and then that tool starts making calls that should stay in the realm of human judgment and taste, like which customers get served first, which insurance claims get flagged for review, which job candidates get screened out, and where the savings from that efficiency actually go. Each case is small, but every one is a values decision. Those improperly delegated values decisions can have compounding negative effects, resulting in an organization optimizing for something other than its reason for being, at the expense of the communities and customers its purpose was built around.
Carol Cone:
Balaji, can you talk about adoption? Have you seen purpose drift, and how it can impact the power and scaling of AI?
Balaji Ganapathy:
Absolutely. I think the real harm in where AI adoption can show up in purpose drift is what I call performative purpose. Many organizations, early movers, have figured out how to use AI to generate beautiful narratives and reports that sound very compelling but aren't grounded in real measurement or actual change happening in the real world. And there's already a backlash growing from that.
The challenge is that if you're delegating your humanity, your aim for what you want to see change in the world, to an AI, over time the language gets more and more polished, but the outcomes remain unchanged. That makes it difficult, over time, to tell your stakeholders that you're actually doing what you say you're doing. So while the negative part will be there in the short term, purpose drift and AI polishing, AI washing, what's going to happen is the capabilities of AI will also show up in how people are doing versus what they're saying.
I love how Kristian put it in terms of what the drift will cost. The cost of the drift is that it won't feel like a crisis, it'll feel like you're being efficient. That's the biggest fallacy, because you'll feel like there are productivity gains, some efficiency, some money coming your way, but actually you're eroding the fundamental basis of what made your organization work and create value in reality, and you're basically delegating all of that to AI. So who's then going to represent your organization's intent to the world?
That part of purpose drift is going to start showing up very quickly, because people think of AI as a tool and then give it everything: write this report for me, take this decision for me, tell me if I'm doing well, be my therapist, be my friend. Recognizing that isn't the real value of AI, but rather making you smarter, making you better, making you do your job at a higher level, bringing more ideas and innovation to the table and creating that culture within the organization, that's where you can save yourself from purpose drift. Unfortunately, a lot of organizations are going down that first path. Very few are going down the second.
Carol Cone:
Do you have any suggestions about how you can shape the culture using purpose, to make it acceptable, and honestly, fun? I'm always surprised by what comes out of my interactions with AI. But I'd love any cultural suggestions.
Balaji Ganapathy:
You don't create an AI culture by training people to use tools. As I said, this isn't a technology play, it's a culture play. You create the culture by giving people permission to experiment and the safety to fail.
There are three things we do at Social Positive. First, as a CEO, I use AI for everything, from research to preparing for today's call to writing, analysis, and strategy, and I make sure everyone knows it, every partner, everyone in my leadership training cohort, everyone in our network of partners. That signals that it's not mandated, it's something you're inviting people into.
Second, you have to share what works and what fails. Carol, you and I were talking the other day about how bad prompts give you bad returns, AI is only as good as what you put into it, what you ask it. A safe space has to be created for that transparency, so people understand better what it's powerful for and what its limitations are. The problem is a lot of people are asking AI itself how to use it, which is fine, but it's biased. So we have to create a culture where people mentor each other, especially young people reverse-mentoring other generations who may not be as savvy with technology, and older, brilliant people who are at the forefront of using these technologies and have the wisdom to ask the right question.
The third thing is you shouldn't ask, can AI do this. That's the wrong question. The question should be, should we use AI for this? And is it serving Social Positive? We ask: does it serve the practitioners? Does it serve the communities? Does it serve the beneficiaries we're building it for? Even though we're AI-native, that's the question we start with, because it's a culture question, not a technology question.
Kristian Merenda:
It might be helpful for your listeners to know that at CCOP, we map this journey toward culture with three phases: contact, connect, and cultivate. Contact is building awareness and honest communication, meeting the fear that employees may have, providing psychological safety. Connect is where co-creation happens, through town halls, design sprints, matching people's skills and values to the work they want to do. And in cultivate, we sustain it with story sharing, ambassador programs, and continuous listening, so the programs adjust as people do.
In our own research with the Harris Poll, we identified employees we call believers, who represent about one in five, who are genuinely connected to the organization's purpose, and found that they're likely to defend it to critics 96% of the time. When AI is connected through a purpose governance layer aligned with the company's strategy, that pays off, because AI adoption inherits all of that when it's designed with people instead of done to them.
A case in point is Bank of America, who's doing a great job of this through their Academy. It's upskilling more than 200,000 people, pairing technical AI skills with human ones, like judgment and adaptability, and mapping exactly where human oversight must remain, so every employee can see where their judgment still matters. That's a bank answering the "what's left for me" question at scale.
Carol Cone:
One of the things you do, and it's pretty simple, but I really like it: you call it a "ride-along." We're a smaller organization, but I'm encouraging everyone to just try, try, try. To Balaji's point, you encourage your colleagues, at no matter what level, to bring you a real situation, show you what they're trying to do, and you'll ride along with them as their partner.
Can you share a few predictions, not ten years down the road, but the next year or so, since AI is moving so fast, about how purpose and AI are going to work together versus grow apart?
Kristian Merenda:
My favorite is in the guide: the prediction that the role of leadership will expand to include moral and technological stewardship. For most of the last century, a CEO could delegate technology to the CTO and values to the HR department. That division of labor is changing, because technology now makes value judgments continuously. Every automated decision has someone who needs to own those judgments, and you can't outsource stewardship of a system that speaks and acts in your name a million times a day. So the next great leadership skill isn't technical fluency, it's the ability to answer, on behalf of the whole organization, what all this power is for.
Carol Cone:
That's a great one.
Balaji Ganapathy:
It was a great one.
Carol Cone:
What is all this power for?
Balaji Ganapathy:
Yeah, and all your predictions are very interesting. I think a lot of it will be proven very soon. A couple I want to add: first, I think in the next year or two, organizations that invested in purpose before AI will outperform those who adopted AI before purpose. I'm putting myself out there saying this, but I think it'll happen at that pace, because AI is unforgiving. Your consumers and your market are going to give you the signal very fast, because previously you could get away with it since your time to market was two or three years. But at the pace things are moving now, unless you're invested in purpose, you won't outperform anyone who is adopting AI, and I'm not talking about a small margin, but a significant one.
The issue isn't the technology. Purpose-driven organizations have cleaner data, higher employee trust, deeper stakeholder relationships, and a governance culture that makes AI adoption smoother.
Kristian Merenda:
One additional prediction I'd love to share is that the traditional instinct in many boardrooms, treating responsible AI as a cost center, will shift, because research now says the opposite: those who use AI responsibly are the ones making money from it, while those skipping the governance are losing money and trust.
There are a couple of recent studies I think are really helpful for making this argument with boards. First, Ernst & Young's responsible AI pulse survey found that companies with real AI governance, meaning live monitoring and oversight committees, are the ones actually reporting revenue growth and cost savings from AI, the two returns everybody's chasing. And 99% of the companies they studied have lost money to an AI incident, over four million dollars on average. So those losses aren't hypothetical.
Then PwC's AI performance study, published in April, looked at over 1,200 large companies and found that just 20% of them are capturing about 75% of all the financial value generated by AI. And those leaders are nearly twice as likely to have a responsible AI framework in place. So the governance isn't slowing them down, it's what lets them run the technology harder than everyone else.
And finally, Just Capital's spring 2026 polling covered the trust side. It showed that only 37% right now are disclosing responsible AI principles, and most people want to see that happen. So those deploying at full speed while telling their stakeholders almost nothing, despite consumers wanting transparency, are doing it at their peril. That silence may be one of the cheapest problems in corporate America to fix today. I think it's a trend we'll see soon.
Balaji Ganapathy:
You have nothing to hide behind. Even if you report annually, everybody will have visibility. They'll be able to see in real time whether your investments are actually doing the work they should. Transparency will change how, I hope, the $2.3 trillion social impact ecosystem operates globally.
My prediction, maybe not next year but in the next two to three years, is that AI will not replace any practitioner in this space. It will replace the isolation that practitioners feel. There are millions of nonprofit and social impact organizations and people around the world, and a lot of them are small or mid-sized, where you're one of the few doing this work. AI deployed with purpose gives these practitioners a research team, an analyst, and a thought partner. So to me, that won't be a threat, that'll be a liberation.
Carol Cone:
So I always love to give the last comments to my guests. This has been a fascinating conversation.
Kristian Merenda:
One thing I love to say, because it's something we haven't touched on, is how fast the ground underneath this whole conversation is moving. Everything we've discussed today assumes AI as we know it, running in data centers down the street, and both of those realities are about to change. There are real data centers in orbit now. A startup called Starcloud put a serious AI chip on a satellite last fall and became the first company to train an AI model in space. Google and SpaceX are right behind them, and the computation part is about to jump as well.
The technologies will keep changing: generative AI today, agents next year, quantum and compute in orbit tomorrow. What doesn't change is the question we ask every organization: do you know what you stand for? Purpose can help answer that, and it will absolutely transfer to help lead every new platform along the way. It's not a panacea, there's much we don't know, but I think being prepared and leading with purpose is the best way to capitalize on this evolution we're living through.
Carol Cone:
Profound, Balaji.
Balaji Ganapathy:
My pet peeve nowadays is that one thing we don't address is who's building AI, who's building these tools, and for whom. The last point I want to share is that most AI tools, especially in the social sector, are built by technologists for technologists. The assumption is that there's data literacy, that people know how to interpret the outputs. The design starts with what AI can do, not with what we actually need, what practitioners need, what the space needs.
So my provocation to end this conversation is: what if we started the other way? What if we, the people, build AI for social impact? What if we, the practitioners, took that upon ourselves? What if it was built by the sector, for the sector? That's the ethos behind everything we do at Social Positive, whether it's the solutions, the products, the intelligence: it's shaped by the practitioners, not by AILLM and SLOP [AUDIO UNCLEAR - Anne, please verify against source audio].
Kristian and Carol, this guide you put together is a gift to the sector, and thank you again for creating the space where these conversations can happen. Kristian, I want to build off what you said: purpose is not a solo journey. It never was. And with folks like you in this space, it's going to be a journey we'll enjoy together.
Carol Cone:
That is so wonderful. Thank you for saying it, and thank you so much for the conversation.
Balaji Ganapathy:
Thank you.
Kristian Merenda:
Thank you, Carol and Balaji.
Carol Cone:
This podcast was brought to you by some amazing people, and I'd love to thank them: Anne Hundertmark and Kristin Kenney at Carol Cone ON PURPOSE, and Pete Wright and Andy Nelson, our crack production team at TruStory FM. And you, our listener, please rate and rank us, because we really want to be as high as possible among the top business podcasts available, so we can continue exploring together the importance and activation of authentic purpose. Thanks so much for listening.