Nestlé is embedding AI into its marketing and sales operations, reshaping how teams plan campaigns and manage workflows. The company is rebuilding the infrastructure beneath its marketing systems to support artificial intelligence.
Over the past 12 months, Nestlé has taken steps to arrange its global teams to make use of AI in routine, revenue-related tasks and inventive production. The change offers a case study in how large brands are approaching AI in marketing and e-commerce.
An AI foundation for marketing operations
Nestlé recently accomplished the primary phase of a worldwide upgrade to SAP S/4HANA Cloud Private Edition, its core system for handling operations in finance, sales, and more. The rollout covered greater than 50,000 users in 112 countries, and the broader deployment is predicted to complete over the following two years.
The upgrade gives teams a single, shared data platform that may serve AI tools. The new system embeds SAP’s AI copilot directly into core business systems, which might help employees pull insights and automate routine tasks in ways in which were harder to do before.
This can change what’s possible in a digital-first marketing and sales context. According to Nestlé’s IT leadership, the upgrade should help the corporate construct platforms to support digital marketing and sales activities that span geographies and channels.
In other words, the work is about making the info and workflows behind marketing and commerce ready for AI-driven abilities, like automated evaluation and execution.
AI-driven content and digital twins
One of the more tangible marketing tech advances at Nestlé lies in content creation. In 2025, Nestlé rolled out an AI-powered content service that uses digital twins (detailed digital 3D models of real products) to generate product visuals for e-commerce and digital media.
Digital twins are created using tools like NVIDIA Omniverse and OpenUSD, which let the corporate’s teams construct virtual replicas of physical products. A product twin will be adapted in some ways: packaging variants, localised images, backgrounds or lighting that match campaign needs, without physical photography.
Nestlé says the service supports brands like Purina, Nescafé Dolce Gusto, and Nespresso by giving marketing teams the flexibility to provide images faster and at lower cost.
Instead of planning dozens of separate photoshoots, teams can produce and adapt assets in a digital environment that reflects the actual product. That can speed up campaigns and let marketing teams act closer to the moment when trends or seasonal events arise.
At first glance, ERP upgrades and digital twins might sound like internal tech talk. But the implications stretch into how brands plan and deliver marketing content.
Here’s how:
1. Faster content production
With models that will be reused and adapted, teams don’t need to start out from scratch for each campaign or variation, useful if brands sell in lots of markets and wish tailored visuals for local audiences.
2. Lower costs over time
Traditional creative work: photoshoots, retouching, editing for format variants, will be expensive and slow. Digital twins convert that work into a reusable asset. Teams can produce visuals in several sizes or contexts without repeating costly production stages.
3. Data-ready marketing workflows
The company’s SAP upgrade was vital as data driving campaigns and customer interactions sits on a standard platform. That makes it easier to use AI in functions that matter to marketing, from customer behaviour evaluation to inventory insights that inform promotional timing.
4. Automation for routine work
Tools like SAP’s AI copilot might help employees finish routine tasks faster. In marketing or sales operations, that might mean less time spent pulling reports or updating campaign plans by hand, and more time focused on strategy or creative decisions.
What marketing leaders can learn from Nestlé’s AI strategy
Nestlé’s moves show what large brands are doing to make AI useful beyond pilot projects: fix the info foundation first, then construct tools that integrate into on a regular basis work. For marketing leaders evaluating AI investment, this offers two lessons:
- Start with shared data and workflows that support multiple teams. AI can only be useful if everyone seems to be accessing a consistent source of truth.
- Think about content as a platform asset. Digital twins make creative reuse easier.
What Nestlé is making marketing operations more predictable and versatile; an approach that many large brands may soon must match in the event that they want AI to do greater than solve narrow tasks.
(Photo by inma santiago)
See also: Walmart expands Scintilla In-Store to link store data and marketing
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