Human-Centered AI Development Strategies for CPG Leaders - with Shaje Ganny of Procter & Gamble

**Daniel Faggella** (0:12)
Welcome everyone to the Emerge AI in Business Podcast. Today's guest is Shaje Ganny, author, guest lecturer, TEDx speaker, and digital transformation director at Procter & Gamble. Shaje joins Emerge's Matthew DeMello on today's episode to outline how CPG leaders can scale AI responsibly by grounding adoption in clear business value and human-centered operational design. He explains why enterprise pilots often fail to translate into real deployment, and how leaders can evaluate AI through its impact on the company, the consumer, and the surrounding workforce community. Just a quick note for our audience that the views expressed by Shaje Ganny on today's program do not reflect that of Procter & Gamble or its leadership. Emerge works with a select group of AI vendors to reach Fortune 500 decision makers through research, media and direct access.
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Now, the conversation with Shaje.

**Matthew DeMello** (1:32)
Shaje, welcome to the program, it's a great pleasure having you.

**Shaje Ganny** (1:35)
Matthew, I am overjoyed, thank you for having me.

**Matthew DeMello** (1:37)
And always very, very excited to have guests fresh from Davos on the program to talk about exactly what they were talking about in Davos. It's like we got a little mini Davos conference right here on the show, of which I'm very, very grateful. For what we're talking about today, we've had a lot of folks come on the show, talk about AI infrastructure. A lot of them have been in very regulated industries, legacy tech stacks. The new term in this group is Frankenstacks. But I don't think we've heard enough from industries that may not be as tech-adjacent or as traditionally human-centric as CPG, as retail, as manufacturing. I think these are very interesting spaces, especially to talk about human-centric AI development. Just to start out in very basic categories of large and small organizations, what in your view makes scaling AI in larger enterprises fundamentally different from piloting AI in smaller, less regulated organizations?

**Shaje Ganny** (2:33)
Wow, what a great question to start off with, Matthew. So first, that was just amazing, and what it is is, so this was only my second time, but second time was so much better than the first time. They've already booked my accommodation for the third time, and it is a fantastic place for people to meet and talk about what actually matters and move things from conversation to action. But I wanted to say something, I reacted immediately to something you said, CPG is not perhaps as tech-adjacent or as tech-connected.

**Matthew DeMello** (3:06)
And that's changing fast. Go ahead, tear it apart.

**Shaje Ganny** (3:09)
Not only, you will be surprised how technologically advanced CPG companies are, and I'm not just talking about all of us, because we have to be. The manufacturing process of any CPG, especially a large-scale CPG company, has to be tech-first, because when you produce at large scale, every second matters and the cost matters, because this is not a large-scale business. So anywhere, anyplace, you can leverage technology to get just that little bit of advantage, you do. And technology has been used in our industry forever. It's just that in today's world, Gen. AI has become this new buzzword. But AI has been around since the 60s, right? Or even before.

**Matthew DeMello** (3:58)
Yeah, absolutely.

**Shaje Ganny** (3:59)
And machine learning, automation, RPA, that's always been around. So large scales or large enterprises have been very comfortable with piloting and learning with AI. So they have experienced that the small ones might actually not have. They actually already have an advantage. They have done this, they've been around, especially if they've been around for a while. The Unilevers of the world, the P&G's of the world, the records of the world, they've been around for quite some time. And they have gone through their own digital transformation, where they've introduced stacks of technology from the manufacturing floor to the planning floor. And they're used to bringing new technology. The difference with AI is that AI is bringing this whole element of FOMO, which is bringing the element, well, if I don't do something, then I'm going to get left behind. And which, from my point of view, is based on lack of understanding on what AI can or cannot do, hype versus reality. And this is causing some companies to jump into trying something in AI and forgetting the lessons they've learned over the past 50, 60, 100, or 185 years.
And that's why mistakes are happening. So between large scale enterprises and small scale enterprises, I think that one difference is experience.
And the second difference is the large scales, they have a lot more to lose by getting something wrong. So large scales are generally tend to be a lot more apprehensive on going, moving from pilot to execution very quickly. I think I have experience, and I know quite a few, and it goes and it takes a little bit of time. Now, some of them will move faster than the others, but they will pilot, learn, and then scale slowly. Yeah.