As retail heads into 2026, tech trends including artificial intelligence agents, data modernization and workforce transformation are reshaping how stores operate and how customers engage.
However, many retail organizations must adapt their experience and data strategies to support outcome-driven engagement, with federated architectures and governance frameworks for AI use cases requiring real-time, contextual data.
Rise of Agentic AI and Autonomous Agents
Research firm Gartner reports 15% of IT leaders are already considering, piloting or deploying autonomous AI agents. Retailers are using agentic AI to drive inventory optimization, shelf management, checkout automation and predictive customer experiences.
According to IDC research, retailers face expanding security and compliance demands as 50% of CIOs diversify risk strategies and struggle with regulatory complexity.
“Unfortunately, retailers are woefully unprepared for the shift to autonomous agentic AI, especially at the retail store level,” says Ananda Chakravarty, vice president of research for IDC Retail Insights.
However, there is a lack of clarity and lack of mature standards concerning how agentic AI will interface with such systems, as many retail data sets are not yet modernized.
“Many retailers are relying on their partner and vendor networks to support necessary changes until some level of maturity in this space is evident,” Chakravarty says.
WATCH: Artificial intelligence will drive efficiency for retailers in 2026.
Outcome-Driven Consumer Experiences
Gartner says retailers are shifting toward outcome-driven experiences as consumers increasingly expect seamless, low-effort interactions — from curated services to everyday problem-solving.
To meet those expectations, companies are leaning on unified customer data platforms and predictive analytics to anticipate needs and deliver highly personalized product bundles and services.
Margot Juros, research director for IDC Retail Insights, says that to leverage the full benefits of AI initiatives, a critical first step for retailers is to develop a data modernization strategy to develop a unified, accessible data foundation, such as centralized data warehouse or lake house, that enable seamless automated access to data from across operations.
“Modernized infrastructure strategies utilizing cloud, edge technologies and advanced networking support the need for real-time data access and processing essential for many AI applications, such as personalized interactions or real-time promotions,” she says.
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Data, Analytics and AI Governance
IDC projects that by 2027, 80% of agentic AI use cases will require real-time, contextual data access — pushing retailers toward federated data architectures for greater agility and compliance.
Juros notes that cloud-based platforms facilitate unified, accessible data and secure automated data movement, while edge computing enables faster analysis of data generated throughout operations while ensuring data security.
The flexibility of hybrid cloud and edge models support optimized data and AI strategies that allow users to select which solutions run in the cloud or on-prem.
With this setup, retailers can choose applications that have low-latency or data residency/compliance requirements, such as point-of-sale transactions or loss prevention solutions, to keep on edge, while retaining unified control and management of data and workloads across cloud and edge environments.
Security, Compliance and Technical Debt
Security, compliance and technical debt are becoming top priorities in retail. IDC forecasts that by 2026, most CIOs will diversify security strategies to counter new supply chain and GenAI risks, and 40% will focus on technical debt cleanup to speed innovation and stay competitive.
“A key step to better battle growing security risks across operations is to enable a seamless, unified view of data in real time from across all systems and operations,” Juros says.
She says modernized data and infrastructure technologies enable retailers to gain a unified view of what is happening, with greater visibility and control across systems and faster access to real-time AI intelligence to proactively identify potential risks or problems on the spot.
SEE MORE: Retailers are facing new and evolving security risks.
Workforce Transformation and Skills Gap
Workforce transformation will become a defining factor in retail, with IDC projecting that by 2028, half of major retailers will deploy advanced tools to close the digital and AI skills gap.
“The retail workforce will require autonomy and trust-building as a key factor in discovering and delivering advantages through AI, GenAI and even agentic AI as we undergo the next version of retail engagement,” Chakravarty says.
He says that what is still unclear is the actual digital and AI skills needed to successfully navigate retail roles as a store associate, store manager or corporate retailer.
“It makes more sense to bring people on board who can learn and adapt quickly and arm them with trust than to manage the tech and force employees to conform,” Chakravarty says.
