The Power of Patience: Gap Inc.’s Second Mover Advantage

In Fortune 500 boardrooms, executives feel pressure to act on AI. They consider options such as launching a chatbot, launching a pilot program or announcing an AI initiative. The urgency has become the norm in recent years, but it has also become a problem.

The data reveal a sobering story. According to Gartner, at least 30% of AI projects are eventually abandoned, potentially representing millions in wasted investment and demoralized teams. Nonetheless, the gold rush is still on, and executives continue rushing forward with their AI use and integration.  

But what if the smartest move is to wait?

While others rushed to launch beta chatbots and unfinished prediction models, Gap Inc. tackled the challenge by pausing, observing and planning. This led to a masterclass on the second-mover advantage. On Oct. 9, 2025, the 56-year-old retailer announced a significant partnership with Google Cloud. By using a second-mover strategy, Gap didn’t catch up. They jumped ahead of early adopters who are now weighed down by technical debt.

The High Cost of Haste

To understand why patience is important, we have to look at the wreckage of the “AI Gold Rush.” Many companies rushed to be first and used tech that didn’t solve real problems. More often than not, those AI projects fail to deliver on their promises.

The second-mover advantage is real. Today’s AI users enjoy advanced tools, reliable platforms and effective best practices that weren’t around two years ago. Companies such as Gap Inc. skipped the expensive trial-and-error phase that trapped their predecessors.

Despite this, the psychological pressure is real. Surveys have shown that executives worry about missing out on AI and resulting job security. But as Gap’s case proves, patience isn’t passivity—it’s strategy.

Anatomy of a Strategic Pause

For 18 months, Gap Inc. conducted a thorough market analysis. Competitors faced issues with untrustworthy vendors. They were also managing customer service bots that often provided incorrect information. This “active waiting” process enabled Gap to craft a mature strategy from day one. During this evaluation period, Gap’s leadership systematically assessed not just technology reliability but organizational readiness—identifying that early adopters lacked the data infrastructure and workforce alignment necessary for successful AI implementation. By March 2025, Gap had already established an internal AI unit to explore specific use cases and establish governance frameworks before selecting external partners, ensuring they could evaluate vendors from a position of internal strength.

CTO Sven Gerjets was clear: He didn’t want AI to replace his workforce; he wanted it to amplify them. Gap skipped the experimental phase by waiting for the technology to stabilize. They launched enterprise-grade solutions with Google’s Gemini, Vertex AI and BigQuery. Rather than deploying fragmented point solutions that early adopters struggled to integrate, Gap opted for a unified AI-powered platform approach that spans from silicon to models to platform to applications—a comprehensive stack that Google Cloud positioned as uniquely capable of delivering retail transformation. Gerjets emphasized a “ruthless” vetting process for technology adoption, rejecting what he called the poor “signal-to-noise ratio” of low-quality tools flooding the market, noting that “not every shiny object belongs in the tech stack.” This selectivity meant Gap would only integrate solutions that solved genuine business problems rather than pursuing AI adoption for its own sake.

Execution: Where Patience Pays Off

Gap’s slow adoption of technology was strategic. This approach paid off in three key areas where many early movers failed:

1. Product innovation: Early AI fashion tools suggested designs that manufacturers couldn’t produce. Gap’s mature implementation uses Google’s Gemini to analyze large amounts of sales data and trend reports. This helps designers predict hits while still allowing for human creativity. At the operational level, Gap’s AI tools now accelerate design, planning, and pricing processes by leveraging BigQuery—Google’s enterprise data warehouse—to process massive datasets containing historical sales patterns, trend data, and market intelligence. This unified platform approach, powered by Vertex AI’s machine-learning infrastructure, enables Gap’s designers to test concepts against real market conditions before manufacturing, creating a feedback loop between AI insights and human creativity that moves ideas from concept to shelf more efficiently.

2. Customer experience: Gap was deliberately slow to adopt new technology and completely avoided the era of frustrating chatbots. Their hyper-personalization engine provides significant support and makes shopping feel intuitive, not intrusive. Operationally, Gap is deploying Gemini-powered tools to deliver hyper-personalized shopping recommendations, smarter product suggestions, and seamless engagement across channels. Additionally, Gap is leveraging Google Ads AI to optimize ad placements and campaign performance, improving its omnichannel capabilities and ensuring customer data flows intelligently across touchpoints—from online browsing to in-store experiences to mobile interactions. This dual approach allows recommendations to feel contextual and relevant rather than invasive, driving stronger storytelling and greater relevance for consumers while deepening customer loyalty at scale.

3. Employee empowerment: Early AI adopters faced significant pushback from workers who feared replacement. Gap framed AI as a “co-pilot,” securing the buy-in necessary for rapid scaling. Specifically, Gap has redesigned workflows from the ground up to position AI as a true partner in decision-making and execution, putting AI tools directly in the hands of every employee across the organization rather than deploying AI as a separate system. By embedding Gemini’s generative capabilities directly into daily processes, Gap is freeing teams to focus on creativity, culture, and customer connection while keeping the company’s “human-centered DNA at the core of innovation.” This embedded approach fundamentally changes how agents and teams operate, making the company more agile, responsive, and forward-thinking while addressing the core concern that plagued earlier adopters: employee resistance based on job security fears.

The Science Behind the Strategy

Gap’s success isn’t an anomaly. Research from Warwick Business School shows that these kinds of strategies can help companies save money and might even lead them to outpace the more rushed leaders. The second-mover phenomenon works like this: The first mover goes first and discovers hidden traps and pitfalls. This, in turn, can allow a follower to move forward with greater knowledge and resulting confidence.

The power of patience lies in this information asymmetry. The second mover knows what works and what doesn’t before they spend a dime. In a landscape as volatile as AI, knowing what not to build is as valuable as knowing what to build.

Lessons for Leaders

Patience isn’t risk aversion. It’s risk mitigation. Gap’s journey offers three clear lessons for leaders navigating technology adoption:

1. Define the problem, not the tech: Gap started with a goal of, “We need to reimagine retail,” rather than, “We need AI.” This prevented wasteful technology purchases and led to thoughtful problem-solving.

2. Let the market mature: By being patient, Gap avoided the “vendor churn” that hit early adopters. They partnered with Google Cloud only after testing its AI tools in real-world settings and evaluating its complete AI-optimized stack—spanning from silicon to models to platform to apps and agents—which Google Cloud positioned as uniquely capable of delivering retail transformation. This comprehensive evaluation process prevented Gap from accumulating redundant or unreliable tools that would create technical debt.

3. Embrace strategic timing: Being a late adopter can be a strength and part of a diligent strategy. Use this time to prepare your data and culture.

The Tortoise Wins Again

In a world addicted to speed, Gap Inc. reminds us that strategic timing can beat hasty execution.

By choosing patience over panic, they transformed potential irrelevance into market leadership. Instead of worrying about surviving the AI revolution, Gap Inc. mastered it by arriving prepared.

For the anxious executive watching competitors sprint ahead: You haven’t missed the boat. The smart money waits for seaworthy vessels, not the first one to leave port.