Key takeaways

• AI is reshaping the consumer experience first, through trust and authenticity: As AI creates “things out of nothing,” brands must prove what’s real and why they deserve consumer confidence
• Personal agents are becoming the new gatekeepers of commerce: Brands must rethink discovery, trial and differentiation when a consumer’s agent filters options
• Retailers risk becoming “fulfilment centres” if agents run shopping on autopilot: The winners will still create moments of delight and high-margin value, without breaking trust
• The era of pilots is ending: Scaling depends on ruthless clarity on value. “Let’s stop with the science projects”
• Execution capacity and change absorption are the constraint: Many organizations can’t pursue top-line and bottom-line AI transformations simultaneously
• Data control may shift toward consumers: “Data wallet” models could change the economics of personalization and targeted marketing

Retail and CPG have always been industries of fast feedback loops: shoppers decide in seconds, supply chains respond in days and brands rise, or fall, on trust built over years. As AI accelerates, that time compression is intensifying.

In a conversation focused on the consumer impact of AI at HCLTech’s pavilion at the World Economic Forum in Davos, Kristina Rogers, Global Chief Growth Officer – Retail/CPG/Luxury at HCLTech, laid out what she sees as the next set of fault lines: authenticity in a world of synthetic content, new “agent-to-agent” barriers between brands and consumers, and the reality that scaling AI is now a strategy-and-change challenge, not a technology one.

From selling services to solving industry problems

Rogers described her mandate in Retail and CPG as shifting from a sales-driven planning cycle to an industry strategy built around client needs and measurable outcomes.

“As the velocity of change accelerates, addressing client challenges has become a primary driver when compared with positioning products and services,” she said, pointing to a vertical-first approach that starts with business strategy and then determines how capabilities fit. At HCLTech, she sees the opportunity to bring that structure to Retail, CPG and Luxury with distinct strategies that align delivery and talent behind them.

She also emphasized the upside if the operating model can connect deep technical capability with industry strategy and relationship leadership: “If you can think about the marrying of the tech talent it’s a pretty powerful [combination].”

The consumer impact of AI: Authenticity and the “agent barrier”

Rogers framed AI’s consumer impact as two shifts happening at once: what consumers trust, and who (or what) brands are selling to.

1. Trust gets harder when AI can manufacture reality

“AI can create a lot of things…things out of nothing. So, do we trust what’s out there? How do know what’s authentic?” she said.

That matters in Retail and CPG because consumers don’t just buy products; they buy reassurance. Rogers argued that the brands that win will double down on the fundamentals that make them worth choosing: “One thing that brands need to be is authentic and create value for consumers so that they trust them and …bring them into their lives.”

2. Agents are becoming the new interface to shopping

The more disruptive change may be the new intermediary: consumers increasingly delegate tasks, including shopping, health and gifting, to AI agents. That creates a new problem for brands and retailers: are they speaking to the consumer or the consumer’s agent?

“Are they communicating with my agent? Are they communicating with me?” asked Rogers. If an agent is configured with strong guardrails, it becomes harder for brands to drive trials and higher-margin discovery.

She summarized the risk: “Does a retailer have a risk of falling into just being a fulfilment centre, rather than being able to delight me with a new experience or cross-sell something with a higher margin?”

Grocery illustrates the “autopilot” dynamic. “Grocery shopping’s a great example. It is on autopilot in many ways.” If more categories follow this pattern, retailers will need new permission-based ways to spark discovery without violating consumer preferences.

Personalization vs privacy: Who owns the data economy?

“I think it’s a struggle,” said Rogers. Retailers want richer personalization, but consumers are increasingly wary of what’s being collected, inferred and sold.

She pointed to emerging models that could shift power toward individuals moving data toward a “data wallet” that consumers can use intentionally: “giving me a personal data wallet that I can spend as I want to…when I want to have things personalized.”

If these models scale, they could reshape how retailers and platforms fund personalization, and how much consent becomes a real economic lever for consumers.

Different markets, different comfort levels

Rogers contrasted earlier consumer research across regions, especially around willingness to adopt deeply embedded technology.

In China, she observed “a real recognition and willingness to adopt all sorts of technologies,” including “transhumanism, or biohacking [and] embedding chips [in many different environments.”

Western markets, she said, have historically had more “hesitancy around government intrusion...privacy and trust and data issues.” But she sees convergence as benefits become clearer and younger cohorts normalize data-sharing: “Gen Z has arrived…they’re much more open…and they don’t care as much because they’ve grown up on it all.”

For global retailers and CPG companies, this translates into a practical design challenge: personalization, consent and transparency will need to be tuned by market, and often by generation.

Scaling AI in Retail and CPG: Value clarity, execution capacity brand trust

Rogers laid out three ways to move from experimentation to impact, echoing a theme that emerged from discussions during the 2026 World Economic Forum:

1. Define the value first

“Let’s stop with the science projects.” The first decision is whether AI is being deployed for top-line growth, such as sales, experience or share, or bottom-line efficiency, including supply chain, procurement and productivity.

2. Don’t underestimate change absorption

She warned that “there’s only so much capacity for change and absorption…in the workforce,” and that many organizations don’t know their own readiness, requiring a “big change management plan.”

3. Treat trust as a value lever

“Are you building trust or eroding trust? Are you adding value or destroying value to the brand?” she asked. In Retail and CPG, where substitution is easy, AI-driven experiences that feel manipulative, opaque or inauthentic can quickly backfire.

FAQs

What’s the biggest consumer impact of AI in Retail and CPG?
A shift in who makes shopping decisions (humans vs personal agents) and what consumers trust (authenticity in a world of synthetic content).

Why do personal AI agents matter for retailers?
Agents can filter offers, reduce impulsive discovery and turn shopping into replenishment “autopilot,” making it harder to drive trial and higher-margin cross-sell.

How can retailers avoid becoming “just fulfilment”?
By creating permission-based discovery, differentiated experiences and trust signals that make consumers want engagement, not just low-friction transactions.

How do brands balance personalization with privacy?
By increasing transparency, limiting unnecessary data use and preparing for a future where consumers may control, and monetize, more of their own data via data wallet models.

What’s the biggest blocker to scaling AI in Retail and CPG?
Not the tech. It's organizational change capacity, operating model redesign and clarity on where AI is meant to drive value.

Do cultural differences affect AI adoption?
Yes. Comfort with surveillance, privacy expectations and generational attitudes vary widely by region, influencing what kinds of AI-driven experiences consumers will accept.