WEF Transforming Consumer Industries in the Age of AI 2025 · Page 11

1.2	 AI adoption-in-action use cases 
Within consumer industries, the environment 
is highly dynamic as companies explore the 
possibilities of AI technologies. However, each 
company is on its own unique journey of AI-driven 
transformation. Many are actively identifying 
opportunities to demonstrate proof points for 
positive business impact, including return on 
investment (ROI). Others are raising the bar on 
innovation, enhancing consumer engagement 
through hyper-personalization and improving 
customer service operations. In the retail sector, 
some are uncovering high-potential new revenue 
streams. The following are just a few examples of 
adoption in action:
Navigating the early stages of AI adoption 
Many companies struggle with fragmentation in 
their AI efforts, launching numerous uncoordinated 
initiatives without aligning them with a strategic 
vision. To overcome that challenge, some have 
established an AI task force or AI leadership office, 
responsible for mapping the AI transformation 
journey, identifying priority applications, creating 
employee training frameworks and ensuring 
responsible adoption. Mexican retailer Coppel 
developed an AI capability framework to kickstart 
its transformation journey. The framework helps 
executives identify use cases to prioritize in 
areas including supply chain management, retail 
operations, customer service and credit risk 
assessment. By mapping the impact of 185 AI 
technologies and tools against 160 retail and 
financial services sub-domains, the company 
continuously evaluates the pace of AI evolution  
and its domain impact. This analysis is then 
transformed into AI application agendas that  
inform business decisions, identify synergies  
and ensure a structured, long-term approach  
to AI implementation.
Research and development 
Combined technologies and unique partnerships 
are already demonstrating significant potential 
for value delivery – making innovation faster and 
better. GenAI is accelerating the time to market 
for early adopters in consumer goods by 25-50% 
within the R&D functions. For instance, Unilever 
is revolutionizing its research and development 
(R&D) by collaborating with Microsoft to transform 
material discovery, ingredient formulation and 
product development while drastically reducing 
timelines and unlocking new possibilities for 
consumer goods innovation. Microsoft’s Azure 
Quantum Elements is accelerating the scientific 
discovery process by combining advancements 
in high-performance computing, AI and, in the 
future, quantum computing. This allows Unilever 
scientists to analyse vast numbers of molecules, 
optimize ingredient ratios, predict outcomes using 
simulations rather than physical manufacturing and 
enable cost-effective innovation.11
Nestlé is revolutionizing product innovation with 
a proprietary genAI-based tool that presents a 
range of concepts in a little over a minute, drawing 
on information from more than 20 Nestlé US 
brands and real-time market trends. The tool has 
accelerated Nestlé’s product ideation process from 
six months to six weeks.12
Marketing
Some businesses are also using “synthetic 
consumers” (digital twins) to test new propositions 
and accelerate time to market. Meanwhile, beauty 
company L’Oréal is among those businesses 
using AI to develop and deliver new customer 
experiences. L’Oréal is using advanced science, 
data, AI and genAI to connect more personally with 
customers and deliver innovations