Why your organization needs both AI moonshots and mundane wins

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How to balance big swings and safe bets to build the most powerful AI portfolio for your business.

Enterprises are on track to pour $307 billion into AI in 2025—more than $35 million dollars every hour. Yet most of that cash will never see daylight: an S&P Global survey found that 42 percent of companies scrapped most of their AI projects this year. The problem isn’t funding or ambition; it is a failure to see that the moonshots need to be balanced by sure things, the stretch goals by easy wins.

AI’s true transformative power emerges not from any single initiative but when leaders orchestrate a portfolio of projects that runs the gamut from the revolutionary to the routine. The organizations that will thrive in this new era are those that pursue both the audacious bets that can redefine their industry and the mundane victories that provide the resources to fund the journey. These modern alchemists understand that transformation requires both vision and groundwork, both aspiration and application. And they know that going all in on a single idea offers an almost guaranteed path to failure.

THE INNOVATION PORTFOLIO

Just as financial portfolios balance risk and return across diverse investments, organizations approaching AI need to develop what we call an “innovation portfolio”—a carefully curated collection of AI initiatives that offer multiple paths to transformation while effectively managing risk. This portfolio approach responds to a fundamental truth about innovation: long-term success requires a pipeline of projects that vary in their size, scope, risk, and transformative power.

The portfolio and financial management approach allows organizations to maintain a comprehensive view of potential AI projects and to systematically manage their development. Think of it as the difference between a chess grandmaster who sees the entire board versus a novice fixated on individual pieces.

The portfolio approach enables leaders to understand how different AI initiatives interact, where synergies might emerge, and how risks in one area might be balanced by stability in another. Crucially, it also lets leaders orchestrate a combination of big and small bets, long- and short-term plans, that fit the business’s needs and resources. Some projects will deliver value immediately while others represent longer-term bets on emerging capabilities that might fundamentally reshape entire industries. By maintaining a portfolio that encompasses both time horizons and risk profiles, organizations create the conditions for sustainable innovation rather than sporadic breakthroughs.

THE CEO AS CHIEF AI ORCHESTRATOR

The transformative power of AI is so great that it demands a fundamental change in the role of the CEO. In this new landscape, AI strategy cannot be delegated to the CTO alone. The CEO must become the chief orchestrator of the AI portfolio, balancing competing priorities while maintaining strategic coherence.

While a foundational AI tech literacy is essential for making informed decisions, this doesn’t mean that CEOs need to understand the technical minutiae at a highly granular level. Instead, they must excel in three critical areas:

Vision Setting: The CEO must articulate how AI aligns with organizational purpose. When employees grasp AI’s significance beyond its ability to deliver financial gains, adoption accelerates and resistance diminishes.

Resource Allocation: Making tough decisions about which AI initiatives receive funding and attention is vital. This demands the courage and authority to discontinue promising projects that don’t align with strategic priorities.

Cultural Transformation: Most critically, CEOs must embody the shift in mindset that AI requires—embracing uncertainty, celebrating intelligent failures, and demonstrating continuous learning. When the CEO publicly shares their AI learning journey, including their mistakes, it empowers organizational experimentation.

THE MACRO-MICRO BALANCE

A successful AI portfolio should operate on two levels simultaneously. At the macro level, you’re asking profound questions: How might artificial general intelligence reshape entire industries? What happens when AI agents take over most knowledge work? How should a company be reconfigured to make the most of a hybrid human-AI workforce. These aren’t philosophical musings—they’re strategic imperatives that guide long-term positioning.

But here’s where organizations often stumble: they become so intoxicated by grand visions that they neglect the micro-level victories that are necessary to fuel the journey. At the same time as planning for whole-of-organization transformation, you also need to ask what your company can do this quarter. Can you use an algorithm to optimize delivery routes? Is there a commercially available chatbot you can use to process customer inquiries? The mundane funds the miraculous.

STRATEGIC PRIORITY MAPPING

Not all AI initiatives deserve equal resources. Comprehensive frameworks for harnessing AI’s potential and managing its risks, such as the OPEN and CARE frameworks, provide systematic tools for evaluating capacities and needs. For instance, the OPEN framework’s FIRST assessment provides a tool for rapid viability screening

Feasibility: Can current technology deliver your vision? Don’t confuse science fiction with strategic planning.

Investment: What’s the true cost—not just dollars, but organizational attention and cultural capital?

Risk/Reward: Map the potential downside as well as the upside. Remember, though, that the biggest risk might be doing nothing.

Strategic Priority: How closely does this idea align with our core purpose? An AI initiative that is at odds with your organization’s identity and goals is doomed regardless of its technical merit.

Time Frame: Can you sustain investment long enough to see returns? Many AI projects fail not because they were wrong, but because they are too early.

THE CONTINUOUS EVOLUTION MODEL

Static strategies die in dynamic environments. Your AI portfolio needs built-in adaptation mechanisms:

Regular Rebalancing: Quarterly reviews of project mix. Are you maintaining appropriate risk levels? Have new capabilities opened fresh opportunities?

Learning Loops: Every experiment feeds strategic understanding. Failed projects often teach more than successful ones.

Cultural Evolution: Organizations must embrace perpetual beta. Yesterday’s mindset won’t create tomorrow’s success.

FROM THEORY TO PRACTICE

A financial services firm might simultaneously pursue:

• A moonshot project using AI to predict market movements with unprecedented accuracy

• A medium-risk initiative automating compliance reporting

• Several low-risk projects improving customer service chatbots

Each initiative serves distinct portfolio purposes. The moonshot could transform the business model entirely. Compliance automation delivers clear ROI within 18 months. Chatbot improvements show immediate returns while building AI capabilities.

The CEO’s role is to ensure that each initiative receives appropriate resources while maintaining portfolio balance—not picking favorites, but orchestrating the symphony.

THE TRANSCENDENCE FACTOR

Ultimately, successful AI portfolios recognize a profound truth: AI isn’t just about efficiency or cost reduction—it’s about transcending current limitations entirely. But transcendence requires groundwork.

Like alchemists purifying base materials before transformation, your AI journey begins with the mundane—cleaning data, upskilling teams, running small experiments. These pedestrian activities build toward something greater: a point at which AI doesn’t just improve existing business operations but enables entirely new possibilities that were previously unimaginable.

WHO WILL WIN?

The organizations that will thrive in the age of AI won’t be those that bet everything on a single strategy. The winners will be those who build diversified portfolios that balance transformational ambitions with incremental improvements, macro visions with micro victories, human wisdom with machine capabilities.

For CEOs, this balancing act isn’t optional. Leaders who treat AI as just another type of new technology have already lost. Those who recognize its power to fundamentally transform both companies and markets are the ones who will write the next chapter in business history.

[Photo: Sergey Nivens/Adobe Stock]

Original article @ Fast Company

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