Navarro and Mehta left Greaves’ office with the grim realization: they needed a company-wide rollout plan, one that delivered immediate financial impact while also proving long-term viability.
They had to think bigger. Instead of focusing only on external sales, they would double down on internal efficiencies, targeting factory-wide AI optimization, procurement cost reductions, and predictive maintenance integration.
Within a week, Mehta and Navarro assembled a war room, bringing in leaders from operations, finance, IT, and sales. The tension in the air was palpable as they laid out their plan. “The board won’t wait for long-term gains,” Mehta stated. “We need results within months.”
Navarro added, her tone urgent but firm, “We’ll prioritize low-hanging fruit like energy cost reductions, quick-turn AI efficiency boosts, and supply chain streamlining. These need to be visible wins.”
Fred LaPlante, the COO, leaned back in his chair, arms crossed. “You think you can roll out AI across the company and make it profitable in six months? I’ve been in this business for 30 years. Nothing happens that fast.”
Navarro met his gaze head-on. “Then maybe it’s time we change how things happen.”
LaPlante snorted. “I’ll believe it when I see it.”
The scene in Twin Transformation is fictional, but one we’ve watched unfold many times in real life. That moment, along with many others, captures the recurring tension we’ve witnessed in boardrooms, strategy workshops, and transformation programs around the world.
Businesses today face simultaneous, urgent imperatives: harness the disruptive potential of artificial intelligence and respond meaningfully to growing pressures for sustainability. Too often, these are treated as separate mandates, led by separate teams, pulling in different directions. Our argument is simple: if companies want to thrive, not just survive, they must learn to integrate these forces. They must embrace a twin transformation.
We’ve written countless research papers, case studies, and articles over the years. But when it came to this topic, AI, and sustainability, we chose to tell a story. Why?
Because transformation isn’t linear. It’s unpredictable. It’s personal. It’s emotional. It plays out in corridor conversations, late-night strategy pivots, and hard-won consensus. A novel allowed us to surface the real human dynamics behind business change: the fear of being left behind, the allure of shiny tech, and the resistance to shifting power dynamics.
In Twin Transformation, we follow the executive team at ThermaDynamics, a legacy manufacturing firm under threat. Newly appointed Chief Sustainability Officer Elena Navarro joins forces with Chief AI Officer Vikram Mehta and CEO Thomas Greaves to pursue growth, drive operational efficiency, and lead AI-driven and sustainability-driven change, all while navigating internal resistance and market disruption. The situations are fictional, but the dilemmas are real. Every breakthrough and setback is drawn from patterns we’ve seen in our research, teaching, and advisory work.
“At the same time, the climate crisis is intensifying.”
In most companies today, AI and sustainability operate in different parts of the organization chart. One is often run by IT or a digital innovation lab; the other by a compliance or ESG team. These teams might sit on opposite ends of the building and rarely share a coffee, let alone a strategy. This structural separation reinforces siloed thinking: AI as a tool for automation and analytics, sustainability as a reporting or risk management exercise.
But the world is changing. AI is no longer experimental; it’s foundational, transforming everything from product design to operations to customer service. It’s reshaping competitive advantage, enabling faster decisions, leaner processes, the augmentation of human work, and entirely new business models. Meanwhile, regulatory pressure is increasing. Supply chains are becoming more fragile. Customers, employees, and investors are demanding greater transparency and accountability.
At the same time, the climate crisis is intensifying. Businesses are being asked not just to disclose their emissions, but to actively reduce them and demonstrate how their strategies support a net-zero future. This pressure isn’t coming solely from regulators; it’s also being driven by talent, customers, and capital markets. While AI drives transformation, sustainability is becoming a test of long-term business credibility.
And yet, we rarely see these two streams, AI and sustainability, strategically aligned. That’s a missed opportunity.
Too often, sustainability is seen as an obligation, a box to check to satisfy regulators and investors.
Too often, sustainability is seen as an obligation, a box to check to satisfy regulators and investors. But what if it could be something more? What if AI could turn sustainability from a burden into a driver of efficiency, cost savings, and new business opportunities?
AI has the potential to optimize resource use, detect inefficiencies, predict emissions patterns, and accelerate research and development (R&D) of sustainable innovations. When deployed thoughtfully, it can make sustainability efforts both smarter and more cost-effective. For example:
These aren’t future scenarios; they’re already happening. In sectors from manufacturing to retail to agriculture, forward-thinking companies are piloting AI-enabled initiatives. But real impact requires intentional design. The power of AI must be directed at the right problems, guided by the right values, and championed by leaders who understand that transformation starts with a clear vision and accountable execution.
In our book, we discuss a common leadership trap: treating AI and sustainability as tech and compliance problems, rather than strategic imperatives. When AI is viewed as “IT’s job,” and sustainability is left to Corporate Social Responsibility (CSR), transformation stalls. What’s needed is a cross-functional approach, championed from the top.
We’ve seen how organizational inertia can become the biggest obstacle. The people leading digital innovation often don’t speak the same language or have the same incentives as those working in sustainability. Bridging that divide requires more than task forces and steering committees. It takes leadership.
Leaders also underestimate cultural challenges. AI can create fear of redundancy or irrelevance. Sustainability can feel like a constraint rather than a catalyst. Success depends on narrative: leaders must frame twin transformation as a source of purpose and progress, not just pressure.
One insight from our research: when leaders visibly back both AI and sustainability, when they make the case that these are not separate initiatives but two sides of the same transformation, they unlock new energy across the organization. People want to work for companies that have a clear purpose and a plan to execute it.
Strategy alone won’t inspire.
Drawing from the novel and our real-world insights, here are five principles for leading a twin transformation:
The leaders of tomorrow will be those who stop choosing between tech innovation and sustainability, and start building the capabilities, cultures, and coalitions to pursue both.
Some will argue that companies can’t afford to tackle both AI and sustainability at once. We believe the opposite: companies can’t afford not to. The costs of inaction, on both fronts, are rising. The convergence of these two forces is not a theoretical future; it’s already reshaping industries.
Companies that treat AI and sustainability as complementary levers, not competing priorities, will be best positioned to respond to the next wave of disruption. They will be more adaptive, more resilient, and more trusted by their stakeholders.
The leaders of tomorrow will be those who stop choosing between tech innovation and sustainability, and start building the capabilities, cultures, and coalitions to pursue both. The twin transformation is not just about surviving disruption. It’s about stepping off the back foot and into a future you helped architect.
Are you ready to lead your own twin transformation? Start by bringing your AI and sustainability leaders into the same room. Challenge your assumptions. Look for the intersections. Because the future won’t wait, and neither should your strategy.
Read more about the book Twin Transformation.
All views expressed herein are those of the author and have been specifically developed and published in accordance with the principles of academic freedom. As such, such views are not necessarily held or endorsed by TONOMUS or its affiliates.
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