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Retail research in 2023–2024 points to five connected changes: generative AI is moving from pilots into operating workflows; practical customer and commerce uses are leading adoption; personalization is shifting from “mass to micro”; loyalty, stores and omnichannel continuity are back at the center of growth plans; and contextual commerce is exposing the need for integrated systems, clear accountability and customer consent.
The five shifts at a glance
| Shift | What the evidence shows | What it means for retailers |
|---|---|---|
| AI enters operations | In a Google Cloud/NewtonX survey of 274 US retail decision makers, 81% felt urgency to adopt generative AI and 72% felt ready to deploy it in 2024. | Prioritize governed workflows with measurable outcomes instead of isolated demonstrations. |
| Use cases stay practical | Customer-service automation led the requested applications at 59%, followed by marketing and product-description support at 49%, creative assistance at 44%, conversational commerce at 40% and store-associate support at 38%. | Start where faster answers, better content or employee access to information can affect revenue or cost. |
| Personalization becomes “mass to micro” | Deloitte describes a move toward more relevant experiences for specific consumer groups. Half of retail executives prioritized AI-driven recommendations, but only five in ten were confident using AI effectively. | Personalization must be paired with transparency, privacy controls, reliable data and human oversight. |
| Loyalty and physical stores regain strategic weight | Deloitte’s 2024 executive survey ranked stronger loyalty programs (54%), digital commerce (44%), in-store experience (36%) and omnichannel experience (32%) as leading growth opportunities. | Growth plans increasingly connect membership economics, store service and digital journeys. |
| Contextual commerce raises integration and trust requirements | RRD respondents cited system-maintenance costs (44%) and integration complexity (35%) as major vendor-collaboration challenges. Consumer attitudes toward in-store cameras were mixed. | Location-aware, platform-integrated shopping is useful only when systems work together and consent is understandable. |
1. Generative AI is moving into retail operations
Google Cloud’s survey, commissioned from NewtonX and fielded from October 23 to November 14, 2023, covered US decision makers at organizations with at least 500 employees. The figures are a 2024 readiness snapshot, not a measure of every retailer or a guarantee that deployment will succeed.
Among those respondents, 81% felt urgency to adopt generative AI and 72% said they were ready to deploy it in 2024. That is a notable change from the experimentation phase described for 2023. Amy Eschliman, Google Cloud’s managing director for Retail Industry Solutions, said generative AI had shifted “from a barely known concept to an urgently needed answer for numerous business challenges.”
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2. The first AI deployments are close to customers and revenue
The same survey shows where retailers are directing attention:
- Customer-service automation: 59% selected it as a requested application. It was already the leading deployment path, with 25% piloting and 22% deploying customer-service automation.
- Marketing support and product descriptions: 49% selected this use case, reflecting the large volume of catalog and campaign copy retailers must produce.
- Creative assistance: 44% selected tools that help generate or adapt creative material.
- Conversational commerce: 40% selected shopping interactions conducted through natural-language interfaces.
- Store-associate knowledge and support: 38% selected applications that help employees find product, policy or operational information.
These are revenue-adjacent tasks: they can reduce service workload, shorten content production, improve product discovery or help an associate resolve a question while a shopper is present. They also carry distinct risks. A service bot can give an incorrect policy answer; generated descriptions can introduce compliance or accessibility problems; and an associate assistant can expose information that should remain restricted. A controlled launch should therefore include approved source content, confidence thresholds, escalation to a person and an audit trail.
3. Personalization is changing from “mass to micro”
Deloitte describes retail as moving “from mass to micro”: away from one broad message and toward experiences tailored to more specific consumer groups or situations. In its 2024 US retail outlook, half of retail executives prioritized AI-driven personalized recommendations.
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More granular relevance can improve discovery, timing and offer economics, but the data also show a capability and trust gap. Only five in ten retail executives said they were confident in using AI effectively. In Deloitte’s holiday consumer study, eight in ten consumers had little to no trust in retailers’ responsible use of AI.
A responsible personalization program should make the value exchange visible. Explain why a recommendation appears, provide controls for marketing preferences, limit sensitive inferences, test for discriminatory outcomes and give customers a practical way to correct data. Retailers should distinguish a useful recommendation based on current shopping activity from opaque profiling that follows a person across contexts without clear permission.
4. Loyalty, stores and omnichannel continuity are growth investments
Deloitte’s ranking of executive growth opportunities places loyalty first. Strengthening loyalty programs was selected by 54% of retail executives, followed by strengthening digital-commerce offerings at 44%, enhancing the in-store customer experience at 36% and enhancing the omnichannel experience at 32%.
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The ordering suggests that retailers are treating retention and continuity as operating capabilities rather than separate marketing projects. A loyalty account can connect a digital order, a store visit, a return and a service interaction, but only if identity, inventory, pricing and consent rules are consistent across systems.
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- Whether rewards increase profitable repeat behavior rather than simply discounting purchases that would have happened anyway.
- How quickly members receive usable benefits and whether redemption rules are understandable.
- Whether customers can see and control the data used for offers and recommendations.
- Whether store employees can recognize and serve members without creating a slower or less private checkout.
What an omnichannel experience requires
Customers should be able to move between channels without losing essential context: accurate store inventory, consistent product information, visible order status, and returns or support that do not force them to restart the conversation. Retailers should measure failure points such as canceled pickup orders, mismatched prices and transfers between digital and store service teams.
5. Contextual commerce depends on integration and consent
RRD defines contextual commerce as personalized, location-based and platform-integrated shopping aligned with a customer’s activity. Examples include a relevant offer near a store, assistance based on the product a shopper is viewing, or a transaction that continues smoothly between an app and a physical location.
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The infrastructure remains a major obstacle. RRD’s September 2023 industry survey included 536 respondents, with a retail subgroup of 102. Respondents identified high system-maintenance costs (44%), integration complexities (35%), slower market adaptability (35%) and demand for integrated solutions (33%) among vendor-collaboration challenges.
Consumer acceptance is not uniform. In RRD’s August 2023 study of 1,809 US adults, 33% said they were comfortable with in-store video cameras and 29% were indifferent. The study found pronounced discomfort among many baby boomers and financially stressed consumers. A camera or location signal may improve operations, but convenience does not remove the need for notice, purpose limitation, retention rules and a non-surveillance alternative where feasible.
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A safer rollout sequence
- Map the context: Specify the event that triggers an experience, such as a product view, store entry or service request.
- Minimize the data: Use the least identifying information needed and separate operational analytics from individual marketing where possible.
- State the benefit: Tell customers what they gain, how long data is retained and how to opt out.
- Connect systems deliberately: Test identity, inventory, pricing and consent synchronization before adding more channels.
- Measure trust as well as conversion: Track opt-outs, complaints, false matches, failed handoffs and demographic differences in outcomes.
Where Coresight’s 2024 outlook fits
Coresight Research’s January 2024 US retail report organizes its outlook around five forces and five trends. It includes proprietary data on inflation, retail theft, resale, retail-media advertising, interest rates and sustainability. The report is a paid 10-page publication, so its estimates and outlook should be read as publisher-authored analysis rather than a neutral forecast.
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Those forces help explain why the five shifts are happening together. Margin pressure increases interest in automation; changing consumer budgets raise the value of relevant offers and loyalty; theft and labor constraints increase the appeal of better store information; and sustainability and resale create additional data and merchandising requirements. None of these pressures makes a particular technology investment automatically worthwhile. The business case still depends on implementation cost, measurable service or sales improvement, and customer acceptance.
How to use these findings in a retail roadmap
- Choose one workflow with a measurable baseline. For example, service response time, product-content cycle time or associate search time.
- Prepare the data and controls before scaling. Define ownership, permitted sources, retention, review thresholds and escalation paths.
- Join channels only where the customer benefit is clear. A unified experience should remove friction, not simply increase tracking.
- Test with employees and customers. Look for incorrect answers, inaccessible content, unwanted personalization and confusing consent notices.
- Report financial and trust outcomes together. Conversion or cost savings without complaint, privacy and reliability measures can hide long-term damage.
These publisher studies describe executive priorities and reported attitudes from specific samples collected mainly in 2023 and published for 2024 planning. They show direction and tension—especially between relevance and trust—not proof that every retailer should adopt the same tools or that any one investment will produce a fixed return.
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