AI Enables Trust, Efficiency, and Innovation in Marketing at the American Diabetes Association

Michelle Ober:

Hi, my name is Michelle Ober and I lead new business at Wongdoody, a wholly owned subsidiary of Infosys. And today we are coming to you from the ANA Masters of Marketing Conference in Orlando, Florida. And I'm really excited to be here with Simone. Simone, do you mind introducing yourself?

Simone Grapini-Goodman:

Yeah, happy to. Simone Grapini-Goodman, and I am the chief marketing and digital officer for the American Diabetes Association. Really good to be here.

Michelle Ober:

Awesome. Thank you so much for joining us.

So today, really excited to dive a little bit into some of what we've heard this week at the conference and then learn a little bit more about what you're doing at the American Diabetes Association relative to all the change and rapid transformation that's happening in our space right now.

Simone Grapini-Goodman:

Right.

Michelle Ober:

So I've got a handful of questions for you. And the first is really around governance. When it comes to AI-led transformation, there's so much that's happening so fast. And I'd love to hear a little bit about how you and your team are evolving your internal or external governance structures to really effectively scale AI across your different teams, different geographies, regions. Love to hear a little bit more about that.

Simone Grapini-Goodman:

I think for most companies, including ours, governance started with a discussion with legal. So we operate in a heavily regulated industry, healthcare. So it is very important that we continue to have the trust of the people that we serve as well. So just like any other technology, we wanted to make sure that we have in place governance structures to make sure that however we use AI, it is reliable and it is authentic.

So we started with a conversation around legal, but then we quickly realized that we also need to have a conversation about the change management impact. So there is the sense of nervousness around how the workforce is feeling about AI, right? About job displacement and that's a very real thing. So yes, we started with legal, but then we realized we need to bring human capital at the table and try to figure out what is the training that needs to take place. How are we going to talk about this with the workforce as well?

The human element, the way I think about it too, is more about enhancing what we do versus replacing what we do. But that's not necessarily the trending conversation that is being heard by our employees. So from a governance perspective, yes, we're starting from a very practical perspective. But we're also taking into account the impact that it has on the people that do the work for the people that we serve.

Michelle Ober:

Right. Absolutely. And sort of bringing them along on that journey with you.

Simone Grapini-Goodman:

Yes, exactly.

Michelle Ober:

So they feel like it's happening with them and not happening to them.

Simone Grapini-Goodman:

To them. Exactly.

Michelle Ober:

Exactly.

Simone Grapini-Goodman:

Yeah.

Michelle Ober:

Yeah. That's really interesting. And building on that, specifically when we talk about you and your team within your organization, how are you adopting your marketing talent strategy to account for all that transformation that's happening? So obviously governance is one layer of it. But to your point, when you think about the work that your team is able to do and the type of thinking and skillsets that's needed to really leverage AI and maximize the investment, what are you rolling out when it comes to talent strategy?

Simone Grapini-Goodman:

So interestingly enough, compared to other functional areas within our organization, marketing has been ahead of the curve when it comes to AI. When you think about AI usage within media, when you think about the personalization, the scalability of propagmatic media, we've been ahead of the curve.

So I found that in that regard, I needed to talk to my team about what is the story we want to tell first, right? We have been doing this for years now, right? How are we going to tell that story? We have so many use cases. We're using it from an agentic perspective for customer service. We're using it for personalization. We're using it for creative versioning, right? We're using it in our publishing division as well.

There's so many other use cases. So it started with, "Hey, remember, we have been doing this. Let's just catalog all the different use cases and then talk about impact." And the impact can be at times efficiency. But the impact can also be savings because you're not necessarily using creative share services to do this work if you have an AI capability to handle the actual versioning.

So number one, I reminded them that this is not necessarily completely new. Number two, I think that when ChatGPT just came into the public domain the way it did, I think was it 2022, perhaps fall of 2022? I think that's when it became democratized and everybody else realized, wow, it can do that.

So in terms of talent management and talent dialogues with my team, I think I quickly realized that we needed some self-imposed guardrails. So right now, when you actually think about AI usage in advertising, there isn't any trade organization that has said, "Whenever we use any type of AI content, you must disclose it." So then we determined, or I let my team know that because we do the work that we do in our community. And I think that not just in healthcare, but in any other industry really, I think that authenticity and trust are so important that if you are going to use AI, you really should be self-disclosing it. Right. So we made the decision earlier on to partner with legal and make sure that whenever we do use AI in our creative, we have language, we have disclaimers that actually mention that.

Michelle Ober:

Smart that you started that partnership early.

Simone Grapini-Goodman:

Right, right. So remind them we have been doing it. So what is the story that we want to tell? Remind them that now that it is so much more accessible, we need to figure out how we communicate that externally too.

And I think the third thing that I'm doing from a talent perspective is to just continue to emphasize and nurture the idea of experimentation, right? So when you're in marketing, you learn, you should be learning all the time by testing. So this is just like anything else that we have been doing. We need to make sure that we learn, we experiment, and failure's not a failure. Failure is a learning.

Michelle Ober:

Right, exactly.

Simone Grapini-Goodman:

So I think those are the three most important things I could do for my team.

Michelle Ober:

I love that. And I think this week we've heard a lot about the importance of maintaining experimentation with intent and making sure that we're communicating the value of that. And if we're going to fail, fail fast. And if we're going to test, make sure that we're learning and we're really applying and reinvesting what we learn back into everything that we're working on. So I love the way you summarize that.

And one of the things that you hit on in the earlier part of your response was making sure that we have a common understanding of what the value of some of the AI tooling that you're investing in is. And so one of the things that's come up time and again this week throughout the conference is how we are communicating the value of some of these marketing investments and metrics to the wider business. Because within marketing, we have one way of talking about it, but then when we look more broadly, I would love to hear your thoughts on how you're communicating some of the value to the business. Whether we're talking about your CEO, CFO, other financial planning conversations that you're having, because that seems to be a really hot topic right now.

Simone Grapini-Goodman:

It is a very hot topic. And one of the speakers at one point mentioned AI is everywhere except in the P&L.

Michelle Ober:

Yes.

Simone Grapini-Goodman:

Yeah. And I thought, okay, but it sort of is. It sort of is. So here's how I am able to communicate it. It's not a binary, but it's just a two-faceted part, right? So the first one is about cost savings and efficiencies.

Michelle Ober:

Right.

Simone Grapini-Goodman:

So I have not been able to, because I have not needed to grow the size of my creative staff because we have been able to take advantage of AI tools. So in that case, it can be the stories about cost obviation, right? You're not necessarily adding FTEs because the FTEs that you have are able to be ever more productive. And that is tangible. That is something that the CFO is able to understand. And we have a lot of metrics around, like you said, the number of projects that come through. This is the velocity with which they move through the system and the headcount has stayed the same. So it's not that we need fewer people, it's that the same number of people are actually being able to turn around work a lot faster and at the expected level of quality, so that we don't get AI slop in and out.

The other way we have been able to talk to my partners within C-suite about it, and I think that that's more like been like 20% of the dialogue, 80% of it has been more about cost savings. The 20% of it has been about growth and revenue. When we run these experiments, these AI driven experiments on the programmatic side of the house, and we have AI-based adjustments for, in our case, for like the donation ask array, right? Or we have AI-based targeted depending on somebody's profile and it's all de-identified data.

Then we're able to say, okay, in this version, wherever we employed AI, we're actually able to get a donation that's maybe 30% higher than if we weren't employing AI. So that's the story that's still developing. And I think that that's a story where most businesses have an opportunity to do more with. So it's not just efficiency, but also it's a growth factor.

Michelle Ober:

Definitely. And on that note, I think you brought up a really interesting point in how we're positioning the value of AI internally. And I'm curious if within your organization and marketing specifically, with the introduction of AI tools, if you have shifted the way that you're measuring marketing effectiveness. Because we have all these new tools coming into the suite and all of these new ways of working. So are there new ways that you're challenging your team to think about what success looks like?

Simone Grapini-Goodman:

Yeah, I have not yet. I have not yet, right? But I have some hopes. So one of the hopes that I have is that when we move from a world where we use analytics of what happened to being able to predict what might happen. So we can use more synthetic level data for our analysis or even a variety of modeling that will allow us to figure out what is the right channel mix and what might happen if we go in this market with this message versus another market with this message. So I'm not there yet because I don't think any of us have figured it out, right? But I think that it's important to at least have a-

Michelle Ober:

North Star.

Simone Grapini-Goodman:

Have a North Star and have a hypothesis around how it might help you. So it all starts with, well, what is your use case, right? No matter what, with any technology, AI included too, it's like, are you doing it because everybody's doing it and it's trending? Or are you doing it because you're trying to solve something in the business?

Michelle Ober:

Are there any recent implementations of AI into your marketing workflow in terms of automation or other sorts of tasks that you've seen really drive efficiency in the way that you're working?

Simone Grapini-Goodman:

From a creative perspective, absolutely, right? Because you're able to come up with so many versions in a matter of minutes. And at the American Diabetes Association, we serve so many constituents, right? So that's been of great help too. And then just we also publish scholarly content. So think about clinical research around diabetes and obesity. And being able to review incoming research. So just being able to get through that copy review in a much faster manner has been very helpful. So my publishing group is very happy ... Happy with that so far.

Michelle Ober:

Are you seeing any new things emerge in terms of business effectiveness as opposed to just marketing effectiveness when it comes to these new AI forward ways of working? So are you able to measure new things? Or are you thinking about what business success means in a different way as a result of the ways that you're working now?

Simone Grapini-Goodman:

I wanted to say yes. I think it's a very good question because it gives me the opportunity to put myself in the seat of my peers as well and understand how might that be helpful to them too. We're able to do, I think, things faster. So when I think about not only putting marketing messages that matter out there, but also for instance, advocacy messages, right? The current administration has been changing a lot of policies when it comes to healthcare. So if we want to be out there being the voice of the people for a change or against a change, whatever's in the best interest of people living with diabetes. I think that being able to test those messages with synthetic data, synthetic focus groups before we're out in the market is extremely important. It's huge time and money saving as well too.

Michelle Ober:

Absolutely.

Simone Grapini-Goodman:

Yeah. So definitely can think of applications that affect the overall business outside marketing.

Michelle Ober:

Are you evolving the way that your marketing organization functions based on the introduction of all these new AI workflows and tools?

Simone Grapini-Goodman:

No, I haven't yet. I think it's too early. I think right now when it comes to any good sort of change management process, we're doing a lot of listening and we're talking to people a lot to understand. So we're in the discovery phase, right? So I haven't made any changes to the team.

I have, generally, when I think about any big undertaking, there's this 5D process that I follow. It's the discover, define, decide, develop, and deploy.

Michelle Ober:

Yep.

Simone Grapini-Goodman:

I like-

Michelle Ober:

Love that.

Simone Grapini-Goodman:

... alliteration a lot, right? So we're more in the discovery phase and a little bit of define, right? So discovery, just really understanding use cases and where AI can help and honestly where it could restrict us too. Where it could restrict us because it's overly agreeable as we know, right? It wants to please you. It wants to continue to offer you more and more information. So we have to mind those things too. So in the discovery phase, it's not only what we should be excited about based on business cases, but also what we should be wary of based on how AI functions.

Michelle Ober:

Such a good point.

Simone Grapini-Goodman:

Yeah. And it's not just the fact that it just agrees and agrees and agrees. But it's also the fact that it's only as good as the data that it is trained on. So if you have garbage data, the AI is going to give you information that's not reliable, that's poor, and you can't put that out there. So I'm not ready to make any significant changes to the team. I think it's premature. Once I get into the discover ... Past the discover phase into the definition of what we want to do and what we don't want to do, then we can get into the decision phase. And obviously, any changes in the organization should have a very strong change management strategy as well.

Michelle Ober:

We've heard it in a few different iterations, but CMO now a lot of the time is actually really being asked to be instead of chief marketing officer, a change management officer or a chief transformation officer I heard today. And I am wondering from your perspective, as you think about the change management in your team and all the introduction of these new workflows and ways of working, have you tried or seen anything from a change management perspective that you think has worked really well in making your team feel empowered in the way that we're working? Or anything that hasn't worked well?

Simone Grapini-Goodman:

Yeah, that's a very good question. And the additional M, I would say, change management officer and change multipurpose ... Chief multipurpose officer.

Michelle Ober:

So true.

Simone Grapini-Goodman:

Right? Because I just feel like marketing is required to wear many hats and a new one every single day.

Yeah, so in terms of what has worked versus what has not worked, I think what I've seen work sort of aligns more with my leadership style too. I'm pretty democratic when it comes to decision making. I think that truly listening to understand, how are people feeling about it and why they're feeling about it the way that they are. I just saw right before I walked in here, Burnett Brown was talking about the fact that she thinks that everything that's going on these days, just socially, economically, plus AI on top of it, is really creating a significant mental health crisis amongst workers.

So those type of stories resonate with me. I know that it's not just the job obsolescence part of it that people are actually worried about, but even for people that are not necessarily worried about that, there is still a fear of, will I be fine? My job's not going away, but will I be able to keep up? Will I be able to still perform? Will I be able to learn at this point in my career where I am?

Michelle Ober:

Right, right.

Simone Grapini-Goodman:

Yeah. So I think bringing people along, I mean, it can be a basic answer, but it's one that's tried and true.

Michelle Ober:

Definitely.

Simone Grapini-Goodman:

Just bring them along and see how they feel. And then make sure that there is also a roadmap too. Sometimes is ... That's why I love the 5D and show them this is your destination.

Michelle Ober:

It's a destination.

Simone Grapini-Goodman:

This is where we are, right? And in order to ... And here's where we're going to be. And maybe we don't know where we're going to be, right? The large language models are changing right now, so we may not necessarily have a timeline. But I think that what we have is sort of like how we're going to go through it together. And that the why is important to people and then the how is very important to people as well.

Michelle Ober:

Well, thank you so much for the time and the discussion. It was really great to be here with you. And this was really helpful for me and hopefully for everybody watching.

Simone Grapini-Goodman:

Oh, good. Thank you. I appreciate it.