Newell Brands is investing in artificial intelligence not as a future bet, but as a present reality. At the center of that effort is our AI transformation program, a company-wide initiative built to accelerate AI adoption and embed new ways of working across every function.
Leading that effort on the ground are Navigators and Voyagers: experienced practitioners embedded within their functions who drive adoption, model new behaviors and connect AI tools to real business problems. Navigators are senior leaders guiding their teams through the transformation. Voyagers are earlier-career professionals who are equally active in building momentum from the ground up. Each Navigator is paired with a Voyager, creating a two-way channel for ideas to flow in both directions.
We spoke with two Navigator-Voyager pairs – one from Sales and one from Customer Service – about what they've built, what they've learned and what comes next.
How did you become a Navigator or Voyager, and what has surprised you most about how your team's relationship with AI has evolved?
Navigator, Sales — AI adoption was already becoming central to how my team does its work, from category analysis and reporting to customer-facing tools, so stepping into the Navigator role was a natural next step. What's surprised me most is the speed of the shift from skepticism to dependency. At the beginning of 2026, AI adoption in the Sales organization was around 45%. Today it's 97%. But the bigger surprise wasn't the adoption number; it was watching the questions change. We went from "why would I use this?" to "how did I ever do this without it?" Team members are now the ones bringing me new use cases instead of the other way around.
Voyager, Sales — I became a Voyager by asking to be part of the conversation and being an early adopter. Before moving into the Sales organization, I spent several years in IT working on business intelligence tools and transformation initiatives, so AI felt like a natural intersection of those experiences. What's surprised me most is that everyone's entry point is different. Some people start with writing, others with research, data analysis, image creation or automation. There isn't a single path. The other surprise has been how quickly AI has changed the conversation. People who never wanted to talk about technology are now some of the most engaged participants in AI discussions. It's empowering people in a way I haven't seen before because they can immediately connect it to their own work.
Navigator, Customer Service — Customer Service was already running on Salesforce, and that platform was surfacing AI applications faster than most functions at Newell were positioned to absorb. We were pulling in support from IT, Data Science and Business Intelligence just to keep pace, and the appetite for doing more was real. When the AI program took shape, the Navigator role was a natural fit. We were already in motion; this was a way to keep that momentum organized and visible across the organization. What surprised me most was how far ahead Newell was compared to many industry peers. When we engaged with others in our space, we found that the AI work we had in flight was moving at a faster pace than many comparable organizations, and these were real-world solutions delivering real value. We were legitimately early in the right places, and that early momentum has been inspiring.
Voyager, Customer Service — AI was already a major focus area for my team. For several years, we've been exploring how AI can transform Customer Service, and since my team is responsible for the technology our agents use every day, we've had a front-row seat to that evolution. We've built a strong collaboration with Salesforce and are working toward a digital-first customer experience supported by an AI-assisted employee experience. What has surprised me most is how quickly the conversation has shifted from curiosity about AI to finding practical ways to use it every day.
Walk us through a specific project or use case your team has tackled — what problem were you solving, and what was the outcome?
Navigator, Sales — We built an AI-enabled "Run of Show" tool to strengthen how our teams present product innovation to retail customers. The problem was that our Innovation Showcases were often built brand by brand, and the opening story would jump straight into product features without grounding it in the customer's specific category strategy. That gap had real commercial consequences — delayed commitments because the connection between the innovation and the retailer's business wasn't clear enough.
The tool synthesizes category overviews, customer data, commercial plans and growth stories to generate two outputs: a complete Run of Show document with a category-first narrative, talk tracks and timing built in, and a gap-summary report that flags what's still missing before the presentation is ready. It's become a forcing function for quality and consistency. Today, 75% of our Innovation Showcases pass an activation-plan readiness review before they go in front of a customer — up significantly from our baseline — and commitment rates on complete showcases have improved event over event.
Voyager, Sales — One of my favorite examples is a simple one. A colleague was working with a dataset containing thousands of rows that required detailed, cell-level analysis and recommendations. Using Claude, we created a short prompt that performed the analysis in minutes and were able to validate the results and move forward with confidence. The entire exercise took about an hour. Without AI, the work likely would have taken several days. Beyond the time savings, it was a powerful example of helping someone rethink what's possible and start looking at their everyday work through a different lens.
Navigator, Customer Service — The use case with the most structural impact has been our work on eliminating what we call the "swivel chair" problem. Our customer service representatives were constantly toggling between Salesforce and SAP to handle a single customer interaction — case notes in one system, order data in the other, with no clean handoff between them. It was costing us speed and accuracy. We've been building toward a model where an AI agent bridges those two systems, pulling order data directly into the service console, summarizing emails and writing case notes, so our teams can stay in one workspace while the AI handles the system navigation. We're making meaningful progress and the direction is clear.
Voyager, Customer Service — One of our biggest focus areas has been creating a digital-first customer experience. We wanted customers to find answers faster while enabling our service teams to spend more time on complex issues. Through our Communities platform, we combine self-service capabilities with AI-powered solutions to reduce friction for both customers and employees. The result has been increased self-service adoption, faster access to information and less manual work for our teams. What I'm most proud of is that we approached it as an experience improvement initiative rather than a technology project. That framing made all the difference in how the team engaged with it.
What advice would you give to someone at Newell who's just starting to explore AI in their work?
Navigator, Sales — Start with your most annoying, repetitive task, not a big strategic project. And don't wait for a perfect prompt. Iterate in the open with it like you would with a smart new colleague and thinking partner.
Voyager, Sales — Just start. Every Newell employee has access to Microsoft 365 Copilot, and the best way to learn is by asking a question or trying a task you're already doing today. Create quick briefs by pulling together information from meetings, emails and shared documents. Find files you know exist but can't locate. Rewrite emails or simplify complex concepts for different audiences. Or use AI to critique your own work: ask what you did well, what doesn't make sense, or what a best-in-class version of this concept would include. You don't need a big project to get started. The small wins add up quickly.
Navigator, Customer Service — Start with something you already know well. Don't pick your most complicated problem, pick the task or workflow you find tedious and repetitive, where you know what good output looks like so you can actually evaluate what the AI gives you. That first win matters. It resets how you see the tool. And don't treat the first output as final. The people getting the most value are the ones who use it as a starting point and then push it. Build on your workflow expertise.
Voyager, Customer Service — Start by looking at your process end to end and making sure it's clearly documented. AI is most effective when you understand the work you're trying to improve. Once you have visibility into the process, look for repetitive tasks, manual handoffs, information searches or activities that consume disproportionate time. Those are often the best opportunities. Focus on solving a business problem first rather than leading with the technology. AI works best when it's paired with strong processes and human expertise. The better you understand your work, the easier it is to identify where AI can make it faster, simpler and more effective.
Where do you think AI will have the biggest impact in your function over the next year or two?
Navigator, Sales — The shift is from AI as a personal productivity tool to AI embedded in how we run core commercial processes: the moments that matter with our retail customers, like line reviews, assortment and category planning, and joint business planning. We're moving from "I used AI to help me build this" to workflows where AI is a structural part of how the work gets done, with clear ties to revenue, distribution and margin outcomes rather than time savings alone.
Voyager, Sales — The biggest impact will be in analytics and insight generation, information processing and the repetitive work that consumes more time than it should. For years, we've all said, "There has to be a better way." Now there is. More importantly, I hope AI helps create real capacity. The Commercial organization has experienced significant change: new systems, new processes, new leaders, evolving ways of working. My hope is that AI handles more of the low-value, repetitive and manual work so our teams can spend more time on strategic priorities, developing new skills and driving growth.
Navigator, Customer Service — Two areas. The first is case resolution speed; when AI can query order data, suggest next actions and handle routine tasks without the representative leaving their workspace, the impact on service efficiency is significant. The second is knowledge management. Right now, institutional knowledge is buried in individual experience and informal practice. AI gives us a way to surface that at scale: the right information, the right precedent, at the right moment. We expect to see a compounding effect of speed and knowledge that creates real capacity to focus on the customer experience.
Voyager, Customer Service — We're only scratching the surface of what's possible today. I'm most excited about humans and AI agents working together across the entire Customer Service process. While much of the attention is on customer cases and email interactions, I see significant potential in operational activities like monitoring orders, identifying exceptions, coordinating across functions and surfacing insights. I'm also excited about the future of our Communities platform and how AI can make it more intelligent, personalized and proactive. The biggest impact won't come from replacing human work, but from augmenting it. The combination of knowledgeable employees and intelligent AI agents has the potential to create a better experience for both our customers and our teams while allowing us to focus our time where it adds the most value.