In the early 2000s, digital transformation was heralded as the future of business, a necessary evolution for companies eager to modernize, compete, and thrive in an increasingly digital world. Fast forward two decades, and the narrative has shifted dramatically. What was once seen as the ultimate business strategy is now being re-evaluated in light of new technological advancements, particularly the rise of generative AI. This shift marks a significant turning point in how businesses approach digital transformation, revealing that the concept, as we once knew it, is no longer sufficient. Today, it’s not just about digitizing operations—it’s about rethinking the very essence of business models to adapt and lead in a rapidly changing environment.

The Rise and Fall of Traditional Digital Transformation

The concept of digital transformation gained widespread traction after 2011 when Capgemini, in collaboration with MIT, defined it as “the use of technology to radically improve performance or reach of businesses.” This definition catalyzed a wave of digital initiatives across industries, as companies scrambled to adopt new technologies like cloud computing, big data, and social media to stay relevant. However, as Jim Harris, a digital transformation thought leader, points out, “Generative AI exposed the incomplete nature of digital transformation investments, emphasizing the pressing need to transform for an entirely new future of business.”

In its early years, digital transformation was often misunderstood. Companies equated it with digitization—simply implementing digital tools without fundamentally changing their business processes or models. This approach led to what many now consider the underwhelming outcomes of digital transformation. As Harris observed, “Digital transformation wasn’t really about transformation. Instead, a vast majority of companies were investing in digitization. Cloud and digital technologies were used to modernize business as usual rather than focus on transformative outcomes.”

This misalignment is evident in the numbers. According to KPMG’s 2023 Technology Survey, a majority of U.S. executives reported that they had not seen a significant increase in performance or profitability from their digital transformation investments. Further research from Boston Consulting Group (BCG) found that 70% of digital transformations fall short of their objectives, often with profound consequences. However, companies that genuinely embraced digital transformation—investing in competitiveness, productivity improvements, and better customer experiences—outperformed their peers, achieving 1.8 times higher earnings growth.

The Generative AI Revolution: A New Chapter in Business Transformation

The introduction of generative AI has sparked a new wave of business transformation, challenging the effectiveness of past digital transformation efforts. Unlike its predecessors, generative AI offers capabilities that extend beyond mere automation of existing processes—it enables entirely new ways of doing business. This distinction is crucial, as it marks the shift from technology-led transformation to executive-led business reformation.

Accenture’s 2024 report highlighted this shift, noting nearly 40,000 mentions of AI on earnings calls by the end of 2023, as C-Suite leaders prepared for a “massive technology shift.” The report underscores the fact that AI is no longer just a tool for efficiency; it’s a strategic asset that can fundamentally alter business models. As Harris aptly puts it, “Given its enormous potential, it should be no surprise that almost every CEO plans to invest heavily in generative AI.”

Yet, despite the enthusiasm, there is already a notable gap between expectations and reality. BCG research indicates that 66% of leaders are “ambivalent or outright dissatisfied” with their AI and generative AI progress. The main barriers include a lack of talent and skills, unclear AI roadmaps, and the absence of a dedicated AI strategy. This disconnect highlights the growing pains of a new era of transformation—one that demands more than just investment in technology, but a rethinking of business strategies and models.

From Automation to Augmentation: The Dual Nature of AI

One of the most significant distinctions between traditional digital transformation and the current AI-driven wave is the shift from automation to augmentation. Automation has long been a focus of digital transformation—using technology to streamline operations, reduce costs, and increase efficiency. While this approach has delivered benefits, it has also limited the scope of transformation to incremental improvements rather than radical innovation.

Generative AI changes this dynamic by introducing the concept of augmentation—enhancing human capabilities to achieve outcomes that were previously unattainable. Harris explains the difference: “Automation takes the work we did yesterday and repeats it at scale, saving costs while increasing efficiencies. Augmentation unlocks new opportunities to do the work we couldn’t do yesterday and achieve new value and outcomes tomorrow.”

This duality is where the true potential of AI lies. Companies that can successfully integrate both automation and augmentation into their operations will not only improve efficiency but also drive exponential growth and innovation. According to PwC’s 27th Annual CEO Survey, 70% of global CEOs see generative AI as significantly changing the way companies create, deliver, and capture value. Moreover, 64% believe that AI will increase the amount of work employees can accomplish, and 59% see it boosting productivity in their work.

Business Model Innovation: The Next Frontier

As companies grapple with the implications of AI, it’s becoming clear that the next phase of transformation will require more than just technological adoption. It will demand a fundamental rethinking of business models—how companies generate revenue, engage with customers, and deliver value. This shift from digital transformation to business model innovation represents the true endgame of the current technological revolution.

As Harris points out, the failure of many digital transformations can be traced back to a lack of clear goals, vision, and strategic alignment with the core business. “Investments hadn’t tied as much to business strategy and goals as they were to iterative improvements, digitization, shiny objects, unrealistic expectations, under-resourced budgets, training, expertise, and resources, and a lack of commitment to change management.” To succeed in the AI era, businesses must start with a clear vision of what they want to achieve and align their AI investments with strategic business objectives.

This shift is already underway. Cisco’s research identified significant gaps in companies’ readiness to embrace AI across six foundational business pillars: strategy, infrastructure, data, governance, talent, and culture. These pillars are critical for building a robust AI-driven business model that can adapt and thrive in an increasingly competitive landscape.

Leadership in the Age of AI: Driving Cultural and Organizational Change

One of the key lessons from the digital transformation era is the importance of leadership in driving change. Too often, digital initiatives were relegated to IT departments, with little involvement from top executives. This lack of leadership support contributed to the underwhelming results of many digital transformation efforts.

In contrast, the current wave of AI-driven transformation is being led by CEOs and CFOs, who recognize the strategic importance of AI in shaping the future of their businesses. As Harris notes, “Leaders are pivotal in driving change. They communicate vision, set the standards for success, and also set the bar for operationalizing future behaviors and norms. CEOs are responsible for creating the culture that the company embodies in its execution and evolution.”

This cultural shift is crucial. For AI to deliver on its potential, companies must foster a digital-first mindset that encourages agility, experimentation, and innovation. This means not just upskilling employees but also reshaping organizational culture to support transformation. Companies that succeed in this will be those that can inspire and empower their employees to embrace new tools and ways of working, driving continuous innovation and growth.

The Future of Business Transformation

As we look ahead, it’s clear that the transformation of digital transformation is just beginning. Generative AI and other emerging technologies are poised to reshape industries and redefine how businesses operate. But for companies to fully realize the benefits of these technologies, they must move beyond the limitations of past digital transformation efforts and embrace a more holistic approach to business model innovation.

This means rethinking not just how they use technology, but how they structure their organizations, engage with customers, and create value. As Harris concludes, “Let’s rethink digital transformation as business model transformation. Doing so will disrupt not only ourselves but entire industries. Not doing so will leave us open to disruption. It’s a gift we either give ourselves or our competitors.”

In the end, the companies that will thrive in this new era are those that can successfully navigate the complexities of AI and use it not just to automate, but to innovate. By placing AI at the core of their business strategies and fostering a culture of continuous learning and adaptation, they can turn the challenges of today into the opportunities of tomorrow.