Bridging the AI Imagination Gap: Leading Beyond Incremental Gains

When I reflect on my entrepreneurial journey—including the experiences that led to successful acquisitions—I’m reminded of the many top leaders, Fortune 500 executives, and disruptive founders I’ve had the chance to interview and learn from. Their insights consistently point to one conclusion: the most transformative leaps occur when we use emerging technologies like AI not just to automate what already exists, but to reimagine what our businesses can become.

A 2025 BCG study (From Potential to Profit: Closing the AI Impact Gap) found that while the majority of large organizations now invest in AI, only a small fraction use it to fundamentally reshape their offerings or tap into entirely new markets. Most remain focused on incremental efforts that deliver small-scale efficiency gains. I call this the Imagination Gap: the difference between AI as a tool for short-term optimization and AI as a catalyst for rethinking the core of a company. Below, I’ll share approaches, examples, and first-hand lessons on how leaders can close that gap and unlock the larger promise of AI.

The Imagination Gap in AI

Many companies start by applying AI to speed up processes or automate repetitive tasks. These incremental moves can generate quick returns, which is why they’re popular. But according to the BCG report, too many teams stop there, leaving AI’s potential for bigger market opportunities on the table.

Netflix illustrates how AI can be a launchpad for broader change. Early on, their recommendation algorithms helped influence roughly 80% of viewer choices and saved an estimated one billion dollars each year by reducing churn. Those same data-driven insights eventually guided Netflix to invest in original programming—knowing exactly which stories and talent would resonate with audiences. Rather than remaining a simple streaming platform, Netflix evolved into a major force in content production and global entertainment.

Elevating AI to a Strategic Priority

McKinsey’s research on AI maturity found that only about 1 percent of companies truly integrate AI at a strategic level. Too often, organizations treat AI as a technical side initiative rather than a driver of overall vision.

Three Ways to Shift Mindset

• Immerse yourself and your teams: Leaders who get hands-on with AI—through site visits, pilot projects, or integrating new AI tools into daily life—tend to see possibilities beyond mere cost-cutting. Direct exposure reveals how AI can open doors to growth and new business models.

• Cross-functional collaboration: AI breakthroughs usually emerge where different perspectives overlap. Bringing data specialists, finance, and product leaders together under shared objectives sparks bolder ideas that are both feasible and market-ready.

• Metrics that reflect transformation: Moving beyond short-term efficiency metrics means evaluating how AI might unlock entirely new markets, enable subscription-based revenue, or create data monetization strategies. By measuring strategic impact, you shift AI from a side project to a true growth driver.

Transforming Business Models with AI:

This is where things get truly interesting. Several top executives I’ve learned from have gone beyond small wins to overhauling their very business models through AI.

• Rolls-Royce’s “Power by the Hour:” Rather than selling jet engines outright, Rolls-Royce used predictive analytics to measure uptime and bill airlines based on how long engines remained operational. AI turned a product transaction into a continuous service model.

• Ant Group’s data-driven ecosystem: Originating from a payment platform, Ant Group scaled AI-based fraud detection and credit scoring to serve millions of underbanked users. This pivot redefined how financial services could operate at high volume and low cost.

For leaders seeking inspiration, one of the best ways to spark associative thinking is to learn from other sectors, perhaps through platforms like FifthRow that highlight AI-driven breakthroughs across industries. Draw connections from these examples back to your own strategic challenges.

Strategic Decision-Making: AI as Your Real-Time Radar:

McKinsey’s How AI is Transforming Strategy Development (2023) shows that companies using AI to spot market shifts can take action faster, sometimes weeks before competitors see what’s happening. This is a huge shift from the traditional cadence of annual or even quarterly planning.

Proactive vs. Reactive

When teams receive near-real-time alerts on changing trends, customer sentiment, or competitor patents, they can pivot on product roadmaps or budget allocations almost immediately. Platforms like FifthRow offer AI agents that constantly research and monitor external signals, providing leaders with timely insights before issues—or opportunities—crystallize. The real transformation happens when these insights become part of daily or weekly decision cycles, rather than appearing in postmortem reviews.

Tesla offers a visible example in the way it constantly refines car software based on data feedback. Rather than annual model upgrades, each vehicle is updated continuously, reflecting a philosophy where strategy is never fully locked in.

Elevating Customer Experience Through Predictive Engagement

Many of the leaders I’ve talked to insist that AI’s greatest value is in delivering a step change in how companies interact with customers. In retail, Amazon attributes about 35 percent of its sales to recommendations, and Netflix harnesses personalization to drive viewer retention. The common theme is predicting what a customer might need, then serving it up before the customer even realizes it.

Proactive Service

In financial services, an AI model may detect a decline in a client’s monthly income early, suggesting a small loan or financial restructuring before the client hits an overdraft. In healthcare, AI triage bots analyze symptoms so that patients connect with a specialist far earlier. These are examples of how AI moves engagement from a passive, wait-and-see approach to an anticipatory model that delights users and solves problems preemptively.

Building a Culture of Experimentation and Immersion

A separate BCG analysis found that leading AI adopters typically concentrate on only a few high-potential initiatives at any given time. They pilot quickly, measure real outcomes, and then scale successes across the enterprise.

Key Elements of Such a Culture

• Clear executive sponsorship, so employees know that learning through trial is valuable.

• Cross-functional teams, not confined to a small group.

• Practical immersion, encouraging leaders and employees to experiment with AI-driven platforms and data sets.

• Emphasis on a fail-fast, scale-fast mindset. When pilots don’t work, capture the lessons; when they do, ramp up quickly.

Challenging Your Own Assumptions

If you don’t disrupt yourself, someone else will eventually do it for you. That’s been a recurring theme in my work with accomplished leaders who turned to AI for fundamental change rather than incremental gain.

Future-Back Planning: Visualize your industry 5 or 10 years out, fully infused with AI. Ask which parts of your current offering or strategy would still matter. Consider moves like cannibalizing existing lines with subscription, predictive models, or AI agents before a rival forces you into playing catch-up.

Cross-Industry Analogies: This is where platforms like FifthRow and broader industry networking can be a game-changer. By learning how AI revolutionizes industries such as healthcare or manufacturing, you can spot fresh possibilities for your own domain.

Practical Moves to Close the Imagination Gap

AI is reshaping industries at breakneck speed—sticking to safe, incremental projects won’t cut it. Now is the time to think bigger, move faster, and turn AI into a genuine growth engine. Consider these immediate steps:

• Audit Your AI Portfolio: Don’t let your AI agenda be a random assortment of automations. Pinpoint which projects merely trim costs versus those that can drive bold revenue streams or entirely new customer experiences. Prioritize investments that have the power to transform—not just streamline—your business.

• Form a High-Level AI Steering Group: Scattered pilots will linger in proof-of-concept limbo if no one owns them at the executive level. Create a cross-functional team of top leaders who can secure budgets, unify efforts, and swiftly push high-impact AI ideas into production.

• Get Data Ready and Governed: AI is only as strong as the data fueling it. If your data is siloed, inconsistent, or unverified, you’ll never reach the big wins. Centralize your data sources, set robust quality standards, and institute clear accountability. Better data is your ticket to more powerful AI.

• Learn by Doing: Nothing accelerates progress like rolling up your sleeves. Conduct internal labs, visit AI innovation centers, or work with real-life use cases that force your organization to experiment. Immersing teams in AI hands-on converts “maybe someday” talk into “we can do this now.”

• Look Beyond Your Vertical: Innovation often happens at the intersections. Study how other sectors leverage AI to open new markets or subscription models, and see if those insights can be adapted to your context. Associational leaps like these can spark breakthroughs you’d never spot by staying in your lane.

• Scale Trust and Responsibility: As AI deployments widen, data privacy and ethical frameworks aren’t optional—they’re imperative. Make sure your governance structures keep pace with your ambition. Earning trust early is crucial for sustained adoption and long-term competitive advantage.

Dream Bigger, Act Faster

AI can certainly optimize existing processes, but more importantly, it can serve as a platform for reimagining your entire organization. The true pitfall is not aiming too high, but settling for incremental steps while your competitors embrace bigger possibilities.

Whether you run a mature enterprise or a fast-scaling venture, closing the Imagination Gap means weaving AI into your company’s core vision. Learn by doing, challenge your own assumptions, study industry disrupters, and nurture a culture that doesn’t shy away from bold moves. By doing so, you position yourself to define—rather than follow—the next wave of disruption.

About the Author

Jason Hauer is CEO of HauerX Holdings and an Inc. 500 honoree. He partners with commercial AI tech and solutions companies to turn ambition into market leadership.