The AI Advantage: How Top Communicators are Leading the Shift

AI is transforming corporate communications—but how can CCOs take the lead? In this episode of The New CCO, top communications leaders Megan Noel (Golin), Mike Marinello (J.P. Morgan Payments), and Dan Gaynor (Signal AI) cut through the hype to reveal real-world AI strategies. From change management to reputation tracking, they explore how AI can be a strategic advantage—not just another tool. Tune in for expert insights on how communicators can drive AI adoption, future-proof their strategies, and lead transformation inside their organizations.

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Transcript

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POD - The AI Advantage: How Top Communicators Are Leading the Shift

[00:00:00] Eliot Mizrachi: AI is rapidly transforming every industry, including communications.

But what does that really mean for CCOs?

This episode of the New CCO goes beyond the AI buzz to bring you the perspectives of top communications leaders who are already shaping its future. On this episode, we're joined by three experts leading AI driven transformation in corporate strategy and communications.

Megan Noel, Global President of Corporate Affairs at Golin, Mike Marinello, Managing Director, Head of Global Communications at J. P. Morgan Payments. and Dan Gaynor, Head of Strategy and Insights at Signal AI. They'll share the AI conversation that's really taking place inside companies today, and how AI can turn communicator skills into real superpowers, becoming a true strategic advantage for your organization.

Let's start by backing up, though, and looking at the bigger picture to help see through the hype. Mike Marinello has seen the evolution of major technological shifts throughout his career. Here's how he frames AI in the context of past industry transformations.

I'm Eliot Mizrachi, and this is the New CCO.

[00:01:15] Michael Marinello: We've been doing this since the beginning of automation and the industrial revolution, so, To me, I'm less awed and, and impressed by any of this in a good way. Not skeptically, but understanding history and understanding that transformation is inevitable and that things can only either make your job better or they can make your job evolve or they can make it go away and you have to reskill yourself.

But that is just human, that's just the course of human history. And I think the thing that I My approach has been, and continues to be, the breathlessness around these types of things is not productive. it's how do you systematically and logically approach it. I remember when I was, I had my own consultancy, and I was working with Ray Day, who was the CCO at IBM at the time.

I mean, I was helping him rebuild the entire comms organization there, and redefine how they do comms in general, both structurally, their agency partners, etc. And I remember being in a meeting with then, um, you know, head of cloud and cognitive software, Arvind Krishna, who's now the CEO. And he said, Stop talking about your AI strategy.

This is 2019. He said, you have a strategy and then you figure out how to deploy AI to be more successful. But if you start with what's my AI strategy, then you're lost because you're putting the thing before the outcome and the impact. And so that's basically been my approach, right? It's look, learn, listen, understand, right?

I was at Bloomberg when, when Sean Edwards, who's the CTO deployed machine learning so that reporters no longer had to ridiculously and wrotely report. every single and rewrite every single earnings report, right? They were able to do something for the reporters. And this was back in 2015, 2016, I don't remember the exact date.

But that was great. And no reporter was like, Oh my God, my job's going away, at least there. My, the reporter was, this is going to make my job easier. it was, Okay, now what can I do better, more impactively and more efficiently because I'm using this versus I'm going to lose my job, right?

[00:03:18] Megan Noel: I've heard this phrase a lot, and I'm sure it's probably overplayed by now. A. I. Isn't going to take your job, but someone that knows a I will, and I fully believe that the same way that Social media didn't take people's jobs.

pick up on a big point that you just said is that about the understanding it because if you don't actually understand your deployment before you understand it, that's where I think you start to see companies organizations get in trouble, and this goes back to the responsible use and the trust in the platform that you really have to understand how you're going to apply it and then do it in the right way.

Otherwise, It could come back reputationally and operationally for a company in a negative fashion.

[00:04:02] Michael Marinello: and those are the hurdles that we'll have to overcome, both as professionals and, and societal if you want to take it larger, before any of this becomes, you know, anything, right? But, and then by also, and Eliot, you know, great point, and Megan, you alluded to it too, Like the robots are, are here, but are they coming? You know? And I think that's what everybody just has to, you know, get their head around,

[00:04:24] Eliot Mizrachi: Yeah, let me, let me actually probe on that because, you know, a few years ago, you know, you attend these conferences and comms and, you know, blockchain was like, this is the most transformative thing to ever happen. And then a couple of years after that, it was the metaverse, you know, and now it's AI, but with AI, the consensus or a lot of what I hear is.

Like, this is the thing. It's as transformative as the advent of the internet to begin with. And while I hear you about the kind of systematic, practical, continuous evolution point. How, like how much potential is there for companies in AI and, and how can they think about that systematically?

[00:05:01] Michael Marinello: Well, I, I think, I'll, I'll, I'll think more from a practitioner's standpoint, but I think you're right. It is a,

it's a huge, jump, right? technologically, right? It is the advent of the, like, the internet. And, you know, so back in the day when I was working in the U. S. Senate as a press secretary, I witnessed the advent of the 24 7 news cycle.

Right? Changed everyone's lives, both as practitioners, you know, societally, and news people forever, right? Saw it happen right before me, right before my eyes, right out of college. you know, we were joking when we were having a conversation the other day about how I can't imagine being a press secretary and having to type on a typewriter, right?

We had word processing and we had all sorts of things that, but just imagine, right, the evolution there. So these are massively transformative technologies and AI is definitely Probably the most that we've seen in our lifetime. So I don't want to underplay it. but I think it's the deployment and understanding of it and the explanation of what it can do that will accelerate or hinder it.

And I'll just say, Eliot, you started, you know, you mentioned big data. Like, big data was so overstated that no one actually figured out what it meant. It And it's no longer a term because it didn't make sense, right? And it got out, everyone got out there too fast to talk about it. No one understood what it was.

And now it's, now it's a punchline. Big data is now a punchline. But everyone was, oh, big data, it's the next big thing. Well, guess what? Data is, but big data maybe not.

[00:06:25] Eliot Mizrachi: well Dan, I feel like that is as good a place as any to bring you in. what do you think it is that is most misunderstood about AI by organizations?

[00:06:33] Dan Gaynor: Well, we're on the new CCO podcast. So presumably a lot of the listeners here are like all of us, comms practitioners. And if I had one message, one key takeaway as somebody who has founded and sold an AI company and works at an AI company and figures out ways to make AI tangible, the lesson is you can do it too.

And I think what I've seen over and over again from big tech to pharmaceuticals to aerospace to automotive is that communicators on a global scale working hand in hand with AI can now make it more tangibly apply to their function than almost any other function in the business. That whether it's operations or sales or marketing, A.

I. enables communicators to go toe to toe with their peers across the organization to develop clear strategies with more demonstrable R. O. Y. so that they can actually for the first time ever prove their impact. Beyond just seeding messages in the market or landing great media pieces, but instead creating entire categories, creating new messaging strands that others will follow.

And most importantly, consistently over time differentiating from their peers by constantly propagating the best proof points from within their organization. That A. I. Would advise you are going to resonate best in the market ahead of time. So the ability to look around the corner to operate more predictively and most importantly, to prove the value of this long misunderstood function, I think, is the coolest thing about it.

And what's fun for me in, um Joining forces with a, with a much more substantial AI company than the one that I found it is just how fungible and flexible and malleable the technology can be in combination with a great communicator, whether that's architecting the pillars of your corporate narrative and tracking those over time with AI.

And today. With all these low code and no code tools out there, not just Chat GPT or Claude or Google notebook LM, you should be able to create not only better content, but truly a measurement program that assesses your strategy before it goes to market and assesses ways to optimize it once it's in the market.

[00:08:51] Eliot Mizrachi: That's really interesting. I'd love it if you can elaborate there because so much of the conversation in the comm space tends to be around the tactical application. Like it will help me write things and I can brainstorm and you know, all that stuff. But you're talking about what CCOs are really interested in.

How is this a strategic force multiplier?

[00:09:08] Dan Gaynor: I mean,

communicators who are naturally storytellers are going to be attracted to generative AI because it can write a press release. It can edit a document. It can suggest better words, you name it. no surprise, right? But it's not the only family of AI. I would encourage you to explore the company that I'm focused on.

Signal AI is using discriminative AI, which means that it's succeeding around labeling and tagging. So did a climate change storyline appear in this article? Or did Pfizer appear in this social media post, but if you go very, very specific and break down your ability to assess strategy down to like individual business units or subtopics within a big picture storyline, like instead of climate change, is it about clean energy?

And within clean energy, is it about renewables? And with renewables, is it about carbon capture? The more specific you can train the AI to understand what your core priorities are, the more specific the insight you get. And as any storyteller knows, the more specific you are, the more differentiated the message.

In this world where there's this giant sea of sameness, What's most exciting for me is to enable communicators to scan across a really broad array of peers, a huge depth of topics from media spanning like Asia to Europe to North America, and then to figure out where they are truly differentiated from their peers, both in terms of the investments they're making and the initiatives they're undertaking.

And if you do that consistently. You stand apart from the pack. More importantly, on an internal basis, when sales walks in with their revenue numbers and marketing walks in with the amount of people that saw the billboard and operations talks about cost cutting, the communicator for the first time ever can walk in and say, here is our proprietary reputation analysis, and we can track improvement on a day by day, week by week, month by month, quarter by quarter basis.

We can actually show. Concentrated improvement over time that really levels the playing field and earns communicators a seat in terms of steering the ship.

[00:11:14] Eliot Mizrachi: Megan, I see nodding.

[00:11:16] Megan Noel: I, I will just echo that and double down on the fact that. Communicators are very similar to the CEO in that we're probably the only two functions that are looking across all of our audiences, all of our stakeholders, and sort of seeing what their views are on our organization or company. And so that unique vantage point is something, Dan, as you said, no one at other organization has except for the CEO.

And with that, AI can be a superpower in terms of not only ID perceptions, reputation challenges and opportunities with each of these different stakeholders, but then saying, how do we act on it in a very personalized way? At scale to be able to either change perceptions, deepen perceptions, shift ideas, et cetera, to ensure that all of our stakeholders are receiving and believing the messages that we want out there.

And that's truly the superpower. We were sort of always able to do it, but it was either very manual. Reflection back, or we weren't able to do the personalization at scale. AI is changing the game for us to give us those tools to go toe to toe in a very different value prop than we would have had. Just a couple of years ago.

How do we, um, start to think about our jobs? differently. I started my career faxing press releases. Well certainly I'm not doing that now and it's been kind of fun mid career to have a total democratization of learning and learn alongside my juniors at the same time. Of of how A. I. Is going to change our job in the future, and I think every organization is going through that.

You don't have those opportunities often in a career to be learning the same thing all at the same time. And I think each organization has to look at their business model and then make those decisions. Um, themselves, but going along that entire journey is, is critical.

I keep hearing that AI is going to be a big topic. It should be, but it's now in the prove it phase. And I think that that's where the change management and the, the rubber meets the road on the, how we start to integrate it into organizations, not if and when.

Yeah, really interesting. We will put a link to the definition of facts in the show notes. Uh, for the younger people who might not know what that is,

Yeah, so I, I think that I'll go on a couple of places. One, I think using AI right in the strategy part, when we were working with a client on their reputation and what their overall positioning was, we were doing a bunch of research and AI helped us, ID, hey, this is what the market is saying, what you are, W what you, what your perception is.

And frankly, it wasn't what they wanted. And so we were able to then do research and, campaign activation, measure it six months later and put the same sort of set of data in AI and show a, a complete change in. what the market was picking up in terms of their perception, making that that AI is not biased.

It's pulling through anything that they're getting,what's out there in the ethosphere. Another example I'll use on internal. And this goes to scaling. when I was at PWC, 75, 000 people were a part of our employee base. They're not monolithic, right? They are sort of unique and have their own audience and employee personas.

We used AI to supercharge how we do internal newsletters. So instead of all 75, 000 people getting the same newsletter, we actually were able to do 75, 000 different newsletters powered by AI and technology. So Megan got her own newsletter on information that mattered to her. If Mike and Dan were at the organization, they would get their own and it was all done By technology and A.

I. That empowered that custom newsletter. So it can be applied in so many different ways from strategy to execution to be able to bring to life.

[00:15:54] Michael Marinello: And I would just add, like, I think what Megan is hitting on is so critical, it's the strategic deployment, right, of AI for the purposes that the firm, the individual, the role needs. Um, because someone shared with me the other day, and I looked it up and then I read it, but Wired came out with a piece that was able to, that they were able to show that 80 percent of long form thought leadership content on LinkedIn was driven by AI.

Okay, so that's a wrong deployment, because if you're a thought leader, then that's not your thought. If you're letting AI drive it, and if it's that long, and it's not from you, then what's the point, right? So, again, it's the strategic use, and the appropriate use, and the use that has the most value, is where AI is going to make the most difference.

But when you do it because You know, you're using it because you don't understand it or you're not quite sure, you're using it before you understand the value of it. That's where. You know, all of a sudden, by God, I found myself in the naysayer role here. I didn't, that's not, I didn't carve that out for myself, but I guess that's where we're going.

But I'm not, I'm not trying to be a naysayer. I'm actually just using, I understand the power and the awesomeness of it. And I want to be practical about its deployment. And so when I see things like this link, you know, this study about LinkedIn thought leadership posts, it also gives me pause. And as an individual practitioner about what I do, but then also about the deployment of the technology in general.

[00:17:23] Dan Gaynor: Yeah. You know, Mike, it, it strikes me. It's like, you need to have your ducks in a row. You need to know what you stand for. When we talk about a strategic use case, the first requirement is knowing what your strategy is. And there is this gigantic sea of sameness. I think we can all admit across the fortune 500.

I mean, how many healthcare companies are putting patients first, quote unquote, how many companies out there on their journey to net zero by 2035 or 2050, as if a regular consumer gives an F. Whether you get there in five years or 15 years, every company wants to be a great place to work, even though they're rushing you to return to the office at three p. m. on a Friday these days. And so what I think is so essential if you want to deploy a I correctly into Megan's point when I say deploy, get people actually using it. It starts first and foremost, which, which within with what your corporate narrative pillars are, what are the component topics that assemble those narrative pillars and what are the authentic real tangible proof points that propagate every one of those subtopics within each of those pillars, which in composite represent us as a whole company, you know, just to give you a few examples of how I've seen this done well again, going back to the point of knowing what our strategy is.

We're working with a big four consulting firm. Because they want to have a proprietary approach to trust. So when they do audits and Megan, I think gets this well, they want to not just look at your financials. They want to look at the external risk landscape, like supply chain or human rights concerns, and make sure that you are in fact a trusted company across the global ecosystem.

AI can help you do that. We work with Takeda. We did a panel, of course, as Eliot knows that at the Page society conference, they're interested in campaigning just on their particular distinctive positioning themes. It's not innovation writ large, it's their own particular definition of it. So whether it's, you know, cell therapy, manufacturing or M and A and oncology.

They have to train all of their topics, particular to their business.

[00:19:22] Megan Noel: I want to double down to what Dan said. I think this is another opportunity for comms professionals as we're looking at reputation, um, employee engagement, change management, all things that we're responsible for. If you are not involved in setting the policy and the framework around your company's AI posture, push yourself in.

Comms should have a huge role in helping shape that because that does come down to trust, that does come down to reputation with all of your stakeholders, and those decisions that are getting made on operations business real use cases are so critical, but equally, if done in the wrong way. Can have reputational challenges that then the comms organization is dealing with from, um, a trust with your stakeholder standpoint.

So, I just think that's another place where I'm counseling clients on and was a part of when I was in house of helping play that role of, of coming with that hat on the way policy or a legal team would come with their respective hats on.

[00:20:29] Michael Marinello: And Dan, you and I have talked about this, you know, like anyone can build a great technology platform internally or externally, but it's the, it's the human application deployment and an ability to apply it. That is a difference maker, right? And we've talked about that before in all sorts of scenarios, right?

And I think that's maybe that's what you're talking about, right? It's like, you know, it's. Build it, but then there's always going to be that, how does the human element come into play, and how is it then deployed, again, used, and strategically sort of executed on to make it as valuable as possible.

[00:21:04] Dan Gaynor: I couldn't agree more. I mean, listen, uh, if you're listening to this episode, And you're working with any of the myriad tens of thousands of AI vendors out there for anything, whether it's comms or HR or finance. I would ask one operative question of them, which is how can I make this platform my own?

How can I make this thing my own?

How can I customize it to my needs, my operating structure, my team dynamic. And in the comms context, what that means is like, can I train my own topics? Can I train my company as an entity or is it some sort of preset thing in the system that I can't touch because maybe I have a definition of what my company is in the marketplace and can I train the metrics because I might have a different understanding of what sentiment looks like.

Can I pick my own sources, my own data inputs, all of these things are essential to adoption because to Megan and Mike's point, the more customized it gets, the more owned it feels. By the rest of the team. And we've seen over and over and fortune five hundreds to small companies. It's not enough to buy the new fancy gizmo.

It's essential that it's built into how we operate on a day to day basis. And if AI is just another tool for you to do your job exactly as status quo, but then prove you were doing a good job, that is not reaching the Zenith of utility. If instead, AI becomes your daily newspaper, your editor, your feedback mechanism, and a way to foster collaboration, convene multiple functions together at the same table, then it's deployed correctly.

So, you don't have to be a coder to use AI well. I certainly, as a practitioner, Can barely use Excel, let alone built my own system. So if I can do it, I'm sure many of the people out there all far smarter than me can. The question is, can we customize it and can we give our team the chance

to tailor it to their needs?

[00:22:54] Eliot Mizrachi: Well, clearly there is more expertise among the three of you than we can fit into a single podcast episode, uh, which is a wonderful thing, but, uh, but I thought I might just give you all a chance, uh, just to share a final thought, a piece of advice or a learning that you've had that you think is not obvious.

Something that, you know, you haven't heard talked about, but you think would really be. Uh, important for listeners to understand. Megan, let's start with you.

[00:23:18] Megan Noel: Yeah, this is something I haven't heard before, but I think it continues to be important to all practitioners and it's lean in, lean into this as an opportunity To really shape our profession and what's next of it. Um, we continue to talk about this as a transformational piece of technology and way we operate.

This is our chance to reshape our profession and be a part of that change. And by us leaning into it, we have the opportunity, especially as those that are sitting in the senior most seat. to have an outsized role in playing and dictating what's next in our profession. And for that, I'm bullish because that means that I get to shape a next generation's entire experience for how we get to show up to the business community.

And that is super exciting.

[00:24:12] Eliot Mizrachi: Yeah. What would your advice be, Megan? So I think a lot of CCOs would say, I want to lean into AI, but the organization, uh, is, you know, risk averse and, you know, just. We'd rather be slow and get it right than, than fast. What's your advice to organizations who are that predisposed to that mindset, but still want to capitalize on all the benefits?

[00:24:32] Megan Noel: Continue to listen and learn to those organizations that are leaning in. There is a lot of organizations that are equally risk adverse or highly regulated or both that are still figuring out a way to make this work. equally, it can also be a competitive advantage. So I think the more that. You bring outside perspectives in and success stories from either like minded companies or adjacent industries.

I think it will help with the buy in to the internal structure. And then secondly, is like any good. C. C. O. Know that you're gonna have to tailor the business case to the different, entities that which you are trying to convince. So a different business case for legal, a different business case for finance, a different business case for H.

R. We are the masters of customization and personalization. So if there is any profession that can do that, that's us. But, I wouldn't be dismayed by me. Transcribed by that type of reaction, I would continue to, use outside voices and bring them in.

[00:25:36] Eliot Mizrachi: Interesting that you're recommending a form of stakeholder management. Very communicator. Uh, Mike,

[00:25:43] Michael Marinello: I, you know, I'll just be like sort of succinct and, you know, it's be curious, not complacent. because complacency leads to what Dan said, which it it just has utility that is just, you know, status quo versus, transformative. And, you know, even Einstein said he had no special talents, but it's only, only his passion for curiosity.

And I think like curiosity is, is the key. And so with AI or anything else, it's be curious, not complacent. And that's, you know, that will lead to success,

[00:26:10] Eliot Mizrachi: dan.

thoughts specific to you in general, to the conversation,

[00:26:14] Dan Gaynor: I think I come away with three thoughts here. the first is on talent. I would encourage folks to think about diversity over familiarity. One of the things that I've seen in starting an AI company and scaling a division within one AI allowed us to hire from non traditional backgrounds and scale the skills gap.

In a much faster way. I'm super proud that we've hired former bench scientists doing cancer research and analysts who were previously looking at the brains of fruit flies, let alone former political fundraisers and anti smoking campaigners.

The second point is offense over defense. I think AI being a bit more predictive, a bit more informative with regard to scanning all the topics across the landscape to match breadth and depth in a way that surveys simply can't should allow you to take bolder bets, should allow you to have messaging that is a bit more aggressive and distinctive and current than the corporate rigmarole.

That's been approved by the general council six times. And the last one is to think about using AI for strategy over content. Use it for strategy creation, which we should stand for versus our peers for strategy measurement. Isn't this thing actually working and for strategy optimization, how can we continuously make ourselves fresher in the minds of a very fickle consumer and stakeholder audience?

[00:27:43] Eliot Mizrachi: AI is redefining the role of communicators, but those who embrace it strategically will lead the way. The insights shared by Megan, Mike, and Dan offer a roadmap for how CCOs can harness AI for real impact. Ensuring our profession stays at the forefront of business transformation.

If you found this conversation valuable, subscribe to the new CCO so you don't miss upcoming episodes. And if you're looking for a deeper dive into AI in action, subscribe to get our upcoming new CCO Brief.

Megan Noel breaks down how PwC implemented AI at scale Thanks for listening to this episode of the new CCO. I'm Eliot Mizrachi, We'll see you next time.