In this article, Ivan Bofarull, Chief Innovation Officer at Esade and a thought leader in disruptive innovation outlines three key mechanisms for organisations—especially business schools—to turn disruption into opportunity. First, embrace optionality by exploring diverse future scenarios, leveraging tools like the “Disruption Compass” to navigate uncertainty. Second, adopt directionality, setting broad strategic pathways instead of rigid goals guided by an innovation thesis. Finally, develop critical capabilities that create asymmetric advantages, ensuring long-term value capture. These principles provide a roadmap for organisations to thrive amidst disruption, transforming challenges into catalysts for innovation and growth.

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In recent years, I have had the incredible opportunity to teach courses on disruptive innovation to senior leaders from both established companies and startups. One thing both types of organisations have in common is their need to transform. For startups, transformation means scaling up to become established companies, while for incumbents, it means becoming more like startups. This journey is non-linear for both, involving strategic decisions that rarely benefit from past practices. In today’s context of uncertainty, where multiple disruptions are the new normal, many organisations continue to reinforce their familiar paths. Incumbents focus on their most profitable customers, while startups incrementally improve upon what industry leaders already do. These approaches ultimately lead, sooner or later, to decline or insignificant gains.

One of the key takeaways from my interactions with senior leaders from both types of companies is that, beyond hedging against disruption, organisations need to become more disruption-friendly. They need to embrace disruption to evolve. Business schools and higher education institutions are not isolated from the context described. To become disruption-friendly organisations, I recommend adhering to three principles.

The Principle of Optionality

In venture capital, errors of omission can be far more consequential than errors of commission. Losing 1x of your investment on a failed company is manageable, but missing out on a major success could cost you the chance of a 1,000x return. As AI becomes a major force for change in various domains, universities should also embrace optionality. However, to do so effectively, it is essential to understand the type of business in which they operate. Rather than viewing business education from a product-based perspective (e.g., research, programmes, etc.), we should adopt an outcome-based perspective. What are students or participants trying to achieve when they attend business school? Is it access to new knowledge, the social component of a learning experience, or a new credential to signal qualities that will support their careers?

In my book Moonshot Thinking, I presented a framework for evaluating potential scenarios (options) that involve transformative, enabling technologies. Considering that the primary force of disruption is the capacity to codify parts of a business into digital elements, and that the main driver of execution is timing, I combined these two dimensions into what I call the “Disruption Compass,” generating four potential scenarios:

• S1: What can be easily codified in the short term, such as access to new knowledge. In the past, MOOCs and online platforms increased accessibility; in the future, AI will change the economics of content creation and personalised delivery. Embrace S1 now.
• S2: What will be partially codified in the short term, though certain ‘uncodifiable’ aspects will remain. This is the realm of augmentation, where, for instance, the learning experience includes both soft skills instruction and AI tutoring. Start building S2 capabilities now.
• S3: The aspects of education that will only be codified in the long term, such as the proliferation of AI autonomous agents that may eventually replace most faculty and even learn how to create new curricula and assess the students’ progress. Allocate separate resources to explore S3.
• S4: The ‘new scarcities’, those elements likely to remain less codifiable even in the long term. At a high level, consider the will to learn; at a micro level, consider durable skills and foundational knowledge, which will be crucial in assessing quality and biases in interactions with AI agents. Discuss S4 more deeply, as second-order thinking. Don’t forget it, as it could be your North Star.

Disruption Compass (applied to business education)

Different outcomes or ‘jobs to be done’ analysed through the lens of two core dimensions of disruption.

Which of these scenarios will dominate in the future? Raise your hand if you have a crystal ball! Which brings us to the next principle.

The Principle of Directionality

An organisation cannot sustain itself by simply exploring a variety of options. Steve Jobs once said that innovation is about ‘saying no to a 1,000 different things’. At some point, focus is essential, without it, innovation cannot compound, which is crucial for breakthroughs to accelerate and gain traction. Yet no one can say with certainty which scenario to prioritise. For this reason, I prefer discussing ‘directionality’ over fixed directions. The map may change, and our direction may need to pivot. Pivoting becomes easier and faster when our directionality is broad enough to allow for iteration, as long as it adheres to an overarching path. When focus is too narrow, an organisation may find it too risky to diverge or course correct.

Organisations, including business schools, have various ways to establish directionality. One method I recommend is designing a thesis of the future, or an innovation thesis. This should be a written document detailing potential scenarios (optionality) and identifying asymmetric beliefs that each of the scenarios might entail. Let’s be a bit speculative and imagine three possible directions that business schools may take:

1. Business schools become hubs of critical wisdom, preserving what makes us uniquely human, such as ‘human-to-human’ interactions and the cultivation of character and critical thinking.
2. Business schools become spaces for augmented learning, where faculty, students, and participants access a metaverse of data relevant to measuring, monitoring, and improving learning outcomes.
3. Business schools become platforms for lifelong learning, repositories of trust where curricula are built on foundational, research-driven blocks, and other players, including corporations can develop new content on top of them.

These directions stem from insights from the Disruption Compass and, combined and put together, could form the basis of an innovation thesis that would assign weights to each of the three pathways. Exploring this thesis and ultimately realising it brings us to the third principle: identifying the capabilities we need to build.

The Principle of Capability

Capability, not capacity, is where startups outperform incumbents. Startups often play in a space incumbents overlook, or deem unattractive, allowing them to develop capabilities that eventually negate incumbents’ advantages. Recognising which capabilities are needed for a specific thesis of the future, or directionality, is crucial to understanding how value will be created and captured substantially. Developing new capabilities can be challenging; established companies may need to endure not only technological changes but also significant cultural shifts and redefinitions of status structures.

Consider education: how will AI impact the profession of teaching and academic research? Will it alter business school structures meaningfully? Will more AI-generated content enhance or undermine faculty authority? As the cost of producing content decreases, the risk of irrelevance (or even misinformation) increases, requiring faculty to verify its quality and relevance. Likewise, students will require more, not less, foundational and expert knowledge, an area where core faculty excel.

In an AI-driven learning environment, the cost of receiving immediate feedback from tutors will drop significantly. However, will all feedback be impactful enough to encourage substantial behavioural change in students? Or will more AI-generated feedback demand greater in-person support from learning tutors to uncover relevant, non-obvious insights?

Finally, how will autonomous agents capable of assessing student skills impact business schools’ ability to capture value? To what extent will higher education institutions retain their core role as providers of centralised trust, or will trust evolve into a more decentralised system? If so, what new partnerships—a capability in itself—should business schools pursue? Traditionally, business schools have collaborated with other institutions, accrediting bodies, and media rankings. In a decentralised trust system, business schools will need to establish entirely new networks, perhaps even exploring the space of decentralised autonomous organisations.

Final call to action

Although no prescriptive advice is definitive, preserving the principle of optionality means business schools should embrace probabilistic thinking: while they should invest in reinforcing the core, existing capabilities, they should already be allocating 10-20% of their resources to explore new capabilities essential for the future. My asymmetric belief is that AI will enable a new era of flourishing in human critical thinking, empowering us in similar ways as the spreadsheet or the calculator once empowered maths or finance. Let’s embrace it!