The Agentic Shift: Why Retail’s AI Focus is Moving From Efficiency to Agility in 2026

The retail industry is already steeped in the nonstop buzz of artificial intelligence. While hype is high, action is lagging. The time is now to accelerate or be left at the bus stop.

Yet the question remains: Is there a real return on investment in AI? A recent Google study, ROI of AI, found that 53 percent of executives reporting increased revenue cite 6 percent to 10 percent revenue growth from generative AI. This growth is rooted in the fundamental promise of AI: better shopping experiences lead directly to topline growth while driving better cost structures that innovation has always delivered. However, the collective focus on cost efficiency and the tendency to launch multiyear “big bang” projects have often led to slow execution, fueling the perception that AI is just "a little bit better."

In 2026, the industry will see a dramatic and necessary structural shift that will demonstrate the profound and positive impact that's occurring. The question will no longer be, "Where can we apply AI to save money?" but rather, "How do we deploy AI agents to drive the existential transformation required?"

Retailers thriving in the next economic cycle will be those that master the art of continuous, prescriptive deployment, evolving AI from a passive tool into an active, intelligent resource embedded across every consumer and operational touchpoint. This is the mechanism that accelerates the AI flywheel.

It’s all about embracing an existential operating model. Here's my outlook on the three key trends that will define the next-generation retail enterprise in 2026.

Retailers Must Embrace the AI-Native Operating Model

The competitive reality in a razor-thin margin environment is that the 5 percent to 10 percent cost reduction and revenue uplift AI already delivers isn't incremental, it's existential. Ignoring this transformation is more of a guaranteed path to irrelevance than a mere competitive disadvantage.

In 2026, the industry will be polarized into two clear categories: the "digital-first" incumbents and the "AI-native" innovators. Digital-first retailers will have retrofitted AI into their existing, siloed systems, treating it as a new feature to optimize a website or supply chain node. AI-native retailers, by contrast, will have fundamentally rebuilt their operating model around the premise that every decision, every workflow, and every customer interaction starts with an autonomous AI agent.

This is a cultural and architectural transformation. Moving to an AI-native model means dismantling monolithic, legacy data silos and embracing fluid, real-time data flow. It requires business leaders to stop asking if AI can solve a problem and start asking how the problem should be defined for AI to help solve it. This transition isn't optional; it's the price of admission for the next generation of retail. 

Empowering Retail Teams From Prediction to Strategic Execution

The need to deliver improved experiences and support topline growth means retailers need to find ways to execute more effectively and efficiently across the organization. This is where AI moves from saving money to helping teams do more with less.

For years, retail AI has provided powerful predictive intelligence, such as forecasting demand, modeling customer behavior, and suggesting markdown necessity. The retail employee then uses this data to make a decision. In 2026, AI's role will evolve from passive prediction to active, prescriptive decision-making that can directly execute actions.

The true breakthrough is the shift from suggesting an action to enabling direct execution with employee oversight.

Consider dynamic pricing. Today, an algorithm might suggest a price adjustment. By this time next year, advanced pricing systems will receive a strategic objective (e.g., "maintain a 15 percent margin on this product while maximizing sell-through over seven days") and execute thousands of micro-adjustments per hour across all channels without manual tactical intervention, all while observing a prescribed risk threshold.

The same principle will apply to inventory management. In addition to predicting a spike in demand, AI will automatically initiate the store-to-store transfer of stock, update the fulfillment system, and notify the local logistics provider. The goal isn't to eliminate the human, but to increase their effectiveness and scope.

The role of the employee moves from making every tactical decision to setting the strategic boundary conditions — the "what" and "why." The advanced AI systems handle the "how." This freedom from repetitive, tactical micro-management allows strategic thinkers to focus on truly novel ideas and high-value customer initiatives that drive business expansion.

Elevating the Store Associate From Operator to Experience Creator

The most profound impact of autonomous agents will be felt on the store floor. We've long talked about AI freeing up associates, but the reality has been complex. Associates still face a tremendous cognitive burden, dealing with complicated processes like nuanced returns, cross-channel exchanges, loyalty program exceptions, and compliance requirements.

In 2026, AI agents will support store associates, reducing procedural complexity to foster a more empathetic, high-touch shopping environment. Imagine an associate handling a complex return involving a split payment and a loyalty voucher. Instead of juggling three different systems and policies, the associate simply interacts with a single, unified AI interface, which instantly processes the complexity and offers the associate a single, compliant resolution that can be executed with a single tap.

This offloads the procedural complexity, allowing the store associate to focus entirely on the core functions that AI cannot replicate, including empathy, creative problem-solving, and building genuine human connections. The AI-enabled store will transform the role of the associate from a mechanical operator into a true "experience creator" — a valuable function that cannot be outsourced and is essential for driving lifetime customer value and topline growth.

AI Agents Represent a New Core Operating Model

The competitive battleground in 2026 will be defined by an existential transformation in the speed at which retailers can rebuild their core operating models around AI agents. Retailers must shift their mindset, budget and talent away from pursuing incremental gains and toward cultivating an internal culture of continuous, survival-driven transformation — the critical investment required to accelerate the AI flywheel.

Paul Tepfenhart is the global director of retail at Google.