Retail and consumer packaged goods (CPG) companies have made great strides in adopting AI. They’re using it to make demand forecasting more accurate and consumer experiences more personalized, and they’re streamlining supply chains and factory operations in new ways by reinventing operating models and ways of working.
On paper, the industry is all-in — but there is a foundational challenge.
Research for an NTT DATA report, Cloud-led innovation in the era of AI: The new rules for driving value with cloud, shows that almost all retail and CPG organizations (98%) say that AI has increased the need to invest in cloud, which has become the execution layer of the AI operating model — the place where data is integrated, decisions are made and actions are triggered across the business.
Yet, despite the near-universal recognition of the importance of cloud investment, relatively few organizations have built the cloud foundation needed to scale AI effectively. Only 22% of retail and CPG organizations consider themselves truly cloud-evolved — the most advanced when it comes to cloud adoption and impact — and just 49% are satisfied with their progress in cloud-driven innovation.
Where retail and CPG AI strategies get stuck
Retail and CPG AI strategies are stalling in that gap between ambition and capability. Yes, the AI use cases now in play are meaningful advances. But when they exist as isolated improvements rather than as part of a coordinated system, business leaders are left underwhelmed by the results.
We’ve moved from agents to agencies that reshape processes, but to unlock AI’s full potential, we need to redefine processes end to end throughout the value chain, across departments and even across companies.
Successful retail and CPG operations are powered by an orchestrated, end-to-end value chain. Shifting demand should immediately influence supply decisions. Supply constraints should determine what’s promoted and how orders are fulfilled. Operational throughput should inform how working capital is allocated.
AI makes this level of orchestration possible, enabling these companies to deliver the right product, through the right channel, with the right promotion, in the right place and at the right time.
However, none of this happens without a strong cloud foundation. Limited cloud-native capabilities are as much a barrier to AI success as fragmented data and the constraints of legacy enterprise resource planning and supply chain platforms.
There’s also a mismatch between intent and investment. While AI demand is accelerating, cloud investment has remained relatively flat for nearly 9 in 10 retail and CPG organizations, and just as many acknowledge that their current cloud investment levels put cloud-native, AI and modernization initiatives at risk.
Find the real value in orchestration
It’s no surprise that, in our research, retail and CPG organizations cite modernization as one of the biggest barriers to innovation. However, this is where the conversation about cloud and AI needs to change. Too often, cloud is framed as nothing but a modernization exercise — migrating systems, upgrading infrastructure or deploying new tools. But in retail and CPG companies, the real value lies in orchestration: the ability to connect demand, supply, operations, customer and consumer experience into a single, responsive system.
Cloud and AI become the enablers of visibility and coordination across the value chain, and this changes the nature of the opportunity. It’s not simply about using AI to promote products in a more targeted way or to automate isolated processes. It’s also about understanding what to sell, where to sell it, how to fulfill orders and how each decision affects cost, service levels and working capital throughout the business.
When all of this data is connected, retail and CPG companies can move beyond local optimization and start maximizing value at a system level.
What cloud leaders are doing differently
Globally, a small group of organizations across industries is already taking the lead. Identified as cloud leaders in our research, they’re building their IT environments to support AI from the ground up.
Because they treat cloud as the strategic execution layer for AI, greater AI readiness is their number-one cloud objective — 75% are planning significant increases in cloud investment, compared with just 43% of all other organizations.
These cloud leaders do a few things differently:
- They see data as a shared asset rather than something owned by individual functions, and invest in data management and governance.
- They shift their focus from optimizing silos to orchestrating the entire value chain — connecting demand signals directly to supply decisions, linking operational capacity to customer and consumer promises, and keeping insights flowing across the organization in real time.
- They invest in platform-led architectures that bring together data, applications and processes into a coherent whole.
Crucially, they don’t treat cloud and AI as separate initiatives. They develop them in tandem, recognizing that neither can scale without the other.
Scaling also comes with new security and governance responsibilities. Our research shows that all retail and CPG organizations expect private and sovereign cloud adoption to grow in the next two years, with sovereign cloud projected to rise by 61% in that time.
There are no shortcuts to value
One of the clearest insights from our research is also the simplest: There are no shortcuts. If you keep treating AI as something added on to existing systems without investing in the cloud foundation, you’ll see limited returns.
So, what should your organization do to stand out?
Stop treating cloud as infrastructure and AI as an add-on. Rebuild the foundation, connect the systems and design for AI from the start. Your next competitive advantage won’t come from AI alone but from how well your business is wired to use it.
WHAT TO DO NEXT
Read more about NTT DATA’s retail and CPG services to see how we use our technology and expertise to deliver seamless, personalized and sustainable shopping experiences.