What major trends are impacting the CPG sector today? In their conversation for The Bridge, Artefact’s Arvand Modarresi, Managing Partner & Global Lead for Consumer Brands, and Alexis Poujade, Partner and Lead for Consumer Brands, discuss four key post-Covid topics:
- Growing profitability pressure and the need to prove ROI
- Managing business volatility through data
- The risk of disintermediation in an AI‑driven commerce landscape
- Reinventing business processes with generative AI and agents
Since joining Artefact, Arvand Modarresi has led global CPG data and AI transformation programs, supporting leading brands in reinventing their marketing, commercial, and operational strategies to drive profitability and agility. Arvand holds an MSc in Management and Economics and brings extensive expertise in consumer brands strategy.
Alexis Poujade has 20 years of experience combining strategy, marketing, data, digital & AI for prestige brands and managing direct and transversal teams across Europe, North America, Asia, and Africa. He holds an MBA from ESSEC Business School and specializes in ROI optimization for marketing and sales.
From profitability pressures to intelligent decision-making
One of the most significant shifts in the CPG sector since the pandemic is the end of the “easy growth” period. For several years, many brands were able to absorb cost inflation through price increases and strong demand. That dynamic has now changed. “Today, everything related to data and AI must demonstrate ROI,” explains Arvand. “There is intense pressure on profitability.”
As a result, companies are increasingly relying on advanced analytics to support commercial and marketing decisions. Tools such as Marketing Mix Modeling (MMM), which once required significant technical investment, are now widely deployed across organizations.
Alexis notes that organizations have also reached a higher level of maturity in how they approach performance measurement. “ROI is now often driven by CFOs,” he says. “Marketing, sales, and other teams must now respond with very robust analytical answers.”
Revenue Growth Management (RGM) is a clear example of this shift. Rather than applying uniform price increases, companies are now using sophisticated algorithms to optimize prices across products, categories, and distribution channels. These tools allow brands to simulate scenarios, refine promotional strategies, and negotiate with retailers using precise data rather than intuition.
Using data to navigate a volatile market
Beyond profitability, volatility has become a defining challenge for global consumer brands. Economic conditions differ widely across regions, with markets such as China, the United States, and Europe evolving along very different trajectories. To adapt, companies need real‑time visibility into market dynamics and consumer behavior.
“Companies want to truly understand what is happening in the market in real time,” Arvand says. “They want their finger on the pulse of the consumer.”
Traditionally, brands relied heavily on syndicated data from panel providers such as Nielsen or Kantar. While these sources remain valuable, many companies are now complementing them with more granular data obtained directly from retailers. Access to this information allows brands to analyze product performance at a much more detailed level, monitor customer migration patterns, and better understand purchasing behavior.
This evolution is also strengthening collaboration between brands and retailers. Shared data and analytics enable richer joint business plans, where commercial decisions such as promotions, assortments, and pricing strategies are based on precise insights rather than assumptions.
Disintermediation: Threat or opportunity?
The relationship between brands, retailers, and consumers has always been complex. Retailers have historically played a dominant role in controlling access to consumers, shaping how products are discovered and purchased. Today, however, a new intermediary is entering the ecosystem: conversational AI.
“With LLMs and conversational tools, there is a risk that brands lose direct access to the consumer,” Arvand warns.
AI assistants and conversational search engines are increasingly guiding consumers through the product discovery process. Instead of browsing retailer websites or brand pages, users may rely on AI tools to recommend products, compare options, or answer complex questions.
However, this shift could also create new opportunities for brands. Because conversational queries often occur earlier in the decision journey, they open new spaces where brands can influence consumer choices before the final purchase stage. “In prompt‑based search, the playing field is reshuffled,” Alexis explains. “Many questions arise very early in the funnel, and that can actually benefit brands.”
In this context, collaboration between brands and retailers becomes even more important. By combining insights and aligning strategies, both parties can create more differentiated customer experiences and remain relevant in an AI‑mediated commerce environment.
Generative AI is transforming CPG marketing and operations
Generative AI is enabling new forms of consumer engagement. AI‑powered tools can guide shoppers in choosing products, whether through personalized recommendations, image recognition, or conversational interfaces. For example, multimodal AI solutions allow consumers to upload images and find products that match the style or environment they are looking for.
GenAI is also accelerating innovation cycles. Marketing campaigns, product concepts, and creative assets can now be generated and tested much faster than before. AI can even simulate consumer reactions using synthetic personas, allowing teams to validate ideas earlier in the development process.
Finally, AI is improving operational efficiency across organizations. Many support functions, such as finance, HR, and marketing operations, can be partially automated through AI agents. This allows companies to redirect resources toward innovation and strategic initiatives.
Arvand describes an extreme but increasingly discussed scenario within the industry: “The fantasy is hyper‑focused brands with ten or fifteen employees, fully automated through AI agents, competing with giants.” While this vision remains theoretical, it illustrates how dramatically AI could reshape the competitive landscape.
Will AI level the playing field or widen the gap?
A key question for the future of the CPG industry is whether AI will reinforce the dominance of major, long-standing companies or enable smaller competitors to flourish.
Historically, large consumer brands had two major advantages: access to massive datasets and the financial resources needed to invest in advanced technology. Today, generative AI is lowering some of these barriers. “Data and capital used to give big brands a huge advantage,” Arvand says. “But with AI agents, many processes can now be redesigned from scratch.”
This opens the door for smaller, digitally native brands to scale much faster. In sectors such as beauty, new entrants have already demonstrated how quickly brands can grow through strong digital strategies and social media engagement.
At the same time, investors are increasingly using data and AI to identify promising emerging brands. By analyzing social signals, consumer engagement, and online performance indicators, AI models can help detect high‑potential companies much earlier in their development.
Conclusion: A new competitive landscape for CPG
Data and AI are no longer experimental capabilities in the CPG sector. They are becoming central to how brands manage pricing, marketing performance, commercial negotiations, and product innovation.
At the same time, the competitive environment is becoming more fluid. Conversational commerce, generative AI, and agent‑based automation are reshaping how consumers discover products and how organizations operate.
For consumer brands, the challenge is not simply adopting AI tools. It is learning how to redesign processes, strengthen collaboration across the ecosystem, and turn data into faster and better decisions. In a sector historically defined by scale and brand power, AI is introducing a new competitive dimension: agility. Companies that succeed will be those able to combine advanced analytics with deep consumer understanding while transforming their operating models for an AI‑driven future.
Watch the original interview in French:
