AI may be revolutionizing retail from the inside, but on the outside, many consumers are asking — “What’s in it for me?”
Why AI in Retail: A new global report by SAP Emarsys highlights a stark disconnect between how brands are implementing AI and how shoppers actually experience it. Drawing on insights from over 1,250 marketers and 10,000 consumers across the US, UK, UAE, Taiwan, and Germany, the study uncovers a concerning trend: while businesses invest heavily in AI, many consumers remain unconvinced of its value in enhancing their retail experience: consumers are not feeling the benefits of AI-fueled personalization.
Marketers Love AI. Consumers Aren’t Impressed.
The numbers speak volumes. While 64% of marketers say AI is central to their personalization strategy, only 33% of consumers believe brands are delivering tailored experiences. Even more alarming: just 29% of shoppers feel they receive fair value in exchange for the personal data they provide.
So, what’s going wrong?
According to SAP Emarsys, the issue isn’t consumer resistance — it’s technological fragmentation.
The Root Problem: Broken Infrastructure and “Dark Data”
Behind the scenes, many marketers are working with incomplete, unstructured, or siloed data. Over half of surveyed marketers admit they struggle to act on customer insights in real time. Without unified systems, even the best AI tools are hamstrung, unable to deliver the seamless, personalized experiences consumers now expect.
“Brands are dealing with fragmented systems,” explains Sara Richter, CMO of SAP Emarsys.
“More than half of Australian marketers are swimming in dark data — inaccessible, unstructured info — all while facing rising pressure to perform.”
The result? Impersonal campaigns. Irrelevant messages. And growing consumer skepticism.
Why Consumers Are Losing Trust
The report identifies two main drivers behind the growing trust gap:
1. Opaque Data Practices
More than one in four consumers say they have little to no trust in how brands use their personal data. Consent often feels like a checkbox exercise rather than a meaningful, transparent agreement. People want to know: How is my data being used — and what do I get in return?
2. A Weak Value Exchange
Shoppers are handing over emails, purchase histories, and browsing behaviors — but are getting generic or irrelevant content in return. The “value exchange” feels lopsided. Instead of feeling recognized, many customers feel surveilled.
Unless brands can visibly demonstrate how AI-driven personalization improves the shopper experience, consumers may tune out — or worse, walk away.
The Good News: Some Brands Are Getting It Right
Not all is doom and gloom. The report highlights Gibson Guitars as a standout example of what SAP Emarsys calls “engagement era” brands — companies using AI not just for automation, but for connection.
“We’re not just selling t-shirts,” says Sterling Doak, Head of Marketing at Gibson.
“We’re selling guitars. AI helps us personalize with purpose — without losing the soul of the brand.”
With the help of SAP Emarsys, Gibson achieved:
- Over 50% growth in email revenue
- Twice the customer engagement
- More than 40% of total revenue now driven by AI-powered automations
What sets Gibson apart? According to Richter, it’s not just the tech — it’s the transparency. “These brands show customers how their data enhances their experience,” she says. “And they do it with integrity, not gimmicks.”
Retail’s Next Move: Rebuild Trust, One Data Point at a Time
As AI continues to evolve, SAP Emarsys urges brands to rethink how they collect, manage, and activate customer data. The goal isn’t to do more with AI — it’s to do better.
Here’s where retailers should focus:
First-Party Data Transparency
Let customers see exactly what you collect, why you collect it, and how it benefits them. A clear explanation builds long-term loyalty.
Cross-Channel Consistency
Whether a shopper engages via email, app, or in-store, they should feel understood. AI must unify the experience — not fracture it.
Meaningful Value Exchange
Reward customers for their data. This could mean tailored offers, faster service, or more relevant product recommendations. Show them the ROI of sharing their info.
Final Thoughts: The Future of AI in Retail Depends on Trust
Consumers aren’t opposed to AI. In fact, most welcome smarter shopping experiences. But when AI feels robotic, irrelevant, or intrusive, brands lose more than just sales — they lose trust.
To make AI work in retail, businesses must close the gap between intention and experience. That means better infrastructure, honest communication, and personalized value that feels human — not just automated.
Because in the race to innovate, brands that win will be the ones that remember the human on the other side of the algorithm.
