Coca-Cola, Newell, Clorox: Three Distinct Roadmaps for the CPG AI Journey
Every CPG's AI journey is wildly different. Some businesses take on a measured, exploratory approach — dipping their toes into various use cases before committing to scalability. Others jump into the deep end, looking for end-to-end implementations that can then be leveraged across various functions.
Several major companies, such as The Coca-Cola Co., Newell Brands and The Clorox Co., shed light on their progress with AI so far at the recent Morgan Stanley Global Consumer and Retail Conference.
The Coca-Cola Co.
James Quincey, CEO of Coca-Cola, said that while the company has seen improvements on the innovation side with AI, it's difficult to know whether it has created something at scale without giving it time.
So far, he has seen results, particularly in marketing, using AI for its Christmas ad, which allowed the company to make promotional assets quicker and cheaper — and with increased customization capabilities.
AI allows for greater segmentation, targeting and adaptation of its core marketing areas, he said in statements shared from the event.
Additionally, he is seeing a positive impact on Coca-Cola's selling system, in which generative AI has automated outdated practices that previously required salespeople to turn up to mom-and-pop stores to make an order.
Now, with 30 million store visits per week, the company can use AI to send suggested orders based on what successful retailers are doing, and it can directly connect stores to the consumer system to increase clarity over sales opportunities across different markets.
"We know there's upside on the marketing side and we know the sales system, enabled by AI, produces higher revenue," he said. "Connecting the two will take us to a different place. And then internally, the AI, the analytics and engines, and the agentic stuff is going to get us stuff faster and cheaper."
The company still has some work to do internally to ensure these capabilities are implemented smoothly, Quincey said.
"As I tell people, if you just put it on top of a bad process, you're just going to get to a bad place faster and cheaper. You're not going to get to a better place," he said. "A part of what needs to happen is you need to fix some of the internal processes so that when you speed them up, you actually get a better result."
Newell Brands
Newell has approached artificial intelligence with an exploration mindset, focusing on a capability-based business model. As such, the company proactively approaches leading tech companies and volunteers to be a beta tester, helping to co-develop AI capabilities in various areas.
This began about a year and a half ago as part of the company's turnaround strategy, according to president and CEO Christopher Peterson.
"We got pretty aggressive at going after artificial intelligence. We started looking at use cases, and about nine months ago, we moved aggressively into agentic AI," he said.
So far, Newell has fully implemented over 100 AI use cases across the company, and reports significant productivity gains and reductions in operational complexity. This includes rolling out AI tools enabled by CoPilot 365 and ChatGPT to all employees and providing AI training across the board.
Additionally, Newell has sought to create deeper consumer understanding through a consumer insights function that is fully AI-enabled. This includes building digital personas and doing consumer testing against them, and using AI to create digital assets within the product development lifecycle.
The company has also introduced the technology into its brand management operations, the supply chain and customer service.
"We're looking at difficult multifunctional processes across the company that can be reimagined and redefined … think of things like planning that go across a lot of the organization that can be automated with artificial intelligence," said Peterson.
As a result, Newell has increased its digital marketing assets this year by 500%, with fewer people, and has taken its customer service response time from three hours to 15 minutes, increasing productivity by 300% to 400%.
The Clorox Co.
For Clorox, investment in AI has been about getting a strong data foundation in place to then layer on new capabilities across marketing and the supply chain. It's a pillar-based approach that the company began four years ago with the goal of rebuilding the data infrastructure and creating a suite of technology and marketing personalization.
"We created a pretty sophisticated database to collect information from consumers, as well as a database to manage a lot of content. Some of those investments, like marketing personalization, have already yielded a lot of benefits," said EVP and CFO Luc Bellet.
Sixty percent of the company's marketing efforts are now personalized with the help of generative AI. This is also a result of AI's ability to analyze a lot of data from a variety of sources, including social media and consumer feedback.
The technology has helped Clorox identify patterns and unmet consumer needs or potential business improvements.
Also: How Clorox adapts to consumer trend shifts with advanced analytics
"Over the last few years, you kind of moved from doing one national campaign day to maybe targeting 10 to 20 different customer groups," said Bellet. "And now you can leverage the same data and the same process, and because you have the infrastructure, you are able to just do hyper-personalization. We think that in a couple of years, we'll be able to really do one-to-one marketing."
Clorox's investment in AI is also laying the groundwork for the company's ERP transformation. While the company just finished its implementation, it expects to see the benefits from optimizations from 2026 to 2028.
"As you can imagine, having an ERP that was 20 or 25 years old created a lot of operational inefficiencies. You had a lot of silo processes," said Bellet. "Now you have the ability to see data in real time across the supply chain."
AI will create opportunities from an automation standpoint and help optimize processes from plant scheduling to waste management to logistic optimization and inventory management, he added.
