Generative AI is reshaping society much like Gutenberg’s printing press once did. The printing press democratised knowledge, shifting power from the literate few – primarily monks and the elite – to the masses. Today, GenAI is democratising capability, enabling people and organisations to accomplish tasks previously reserved for experts. Yet, as with every technological revolution, the benefits won’t be distributed evenly.
The history of technological advancement reveals a consistent pattern: Raw technological power matters less than its practical application. While people tend to focus on the technological innovation rather than the value it provides, it’s the value that creates markets. Technology alone rarely drives lasting value; technology is but a catalyst. In this light, GenAI has true potential not for its impressive technical capabilities but in how it transforms industries and functions.
Unlocking potential
The businesses that dominate tomorrow will be those that apply AI vertically, not generically. In other words, the key to unlocking AI’s potential lies in its application to specific contexts.
For example, in the early days of computing, relational database management systems, programmed in Structure Query Language (SQL), were revolutionary. They provided a structured way to store and retrieve data, but their true value emerged when they were embedded into vertical applications. Salesforce transformed customer relationship management by layering industry-specific workflows and user-friendly interfaces on top of SQL databases. Similarly, Shopify democratised e-commerce by abstracting the complexities of database management into a platform designed for small businesses.
Today, GenAI is at a similar inflection point. The true value of large language models (LLMs) is emerging through verticalisation, which refers to the application of the technology to specific industries or functions by combining general-purpose LLM capabilities with domain-specific knowledge and workflows. For example, vertical AI applications are already transforming industries, from tools for strategy analysis that incorporate industry-specific insights to AI-driven sales workflows that optimise customer engagement and AI tutors that personalise education for individual learners.
This isn’t a future possibility – it’s happening now. The ability of some LLMs to excel in tasks like coding or writing is arguably a vertical in itself. Historically, SQL databases had front ends that were much like the front ends of today’s LLMs. Remember green-screen terminals and text-based interfaces? Those were early verticals. Over time, they evolved into deeper, more interactive applications that added far more value (the internet itself started as a text-based vertical application!). The same evolution is now underway with AI.
Yet even as AI provides powerful tools for innovation, it also raises the competitive bar across industries. When everyone has access to similar technologies, the advantage lies not in the tools themselves but in how effectively they’re implemented in specific vertical contexts.
Consider the retail industry. Amazon’s AI-powered logistics and recommendation engines have set a new standard for efficiency and customer experience. Companies that failed to integrate AI strategically didn’t just fall behind – they disappeared. Take the famous example of Kodak who invented digital cameras but failed to integrate AI into the processors to make the pictures better until it was too late. This pattern is repeating across industries, from healthcare to finance and supply chain management.
In our work with global organisations, we’ve observed that successful AI implementation requires more than sporadic technology adoption; it demands systematic approaches that blend traditional business acumen with AI capabilities. The companies that thrive are those that think of AI not as a technological add-on but as a core component of their business strategy.
Institutional entropy: A real risk
In physics, entropy refers to the natural tendency of systems to move towards disorder – the proverbial hot cup of coffee becoming lukewarm. In the age of AI, institutional entropy manifests as diminishing differentiation, relevance and competitiveness the organizational equivalent of becoming lukewarm. Organisations that fail to adapt to AI don’t just stagnate – they shrink as competitors move faster, work smarter and redefine the playing field.
Vertical AI applications are an antidote to business entropy. By combining the rigour of traditional frameworks with the flexibility of GenAI, these tools enable organisations to think bigger, move faster and act smarter. They provide the structure needed to organise thoughts, test assumptions and communicate ideas – all while maintaining strategic clarity.
For example, in strategic decision-making, raw LLMs can generate ideas, but they lack the context and nuance required for effective strategy. Vertical AI tools, on the other hand, can incorporate industry-specific insights, historical data and collaborative frameworks to enhance human judgement. This is where the real value lies.
The risk of entropy is particularly acute for consultants and business professionals who become complacent. Just like automated assembly lines can do virtually anything repeatedly faster and cheaper than manual processes involving blue-collar workers, LLMs are threatening to outdo their white-collar counterparts. Every technological breakthrough has engendered fears about the future of jobs, but this doesn’t mean we surrender to the notion that the future is hopeless.
History shows that these fears need not come to pass. Today’s doctors, lawyers, scientists and professors may feel as threatened as the switchboard operators of yesterday did. But like how the jobs lost to automation have been replaced by new and better opportunities, the impact of GenAI will likely follow the same pattern. It is likely to do away with many as-is processes, while creating new roles that require creativity, coordination and ethical judgements – and other areas where machines currently fall short of human capabilities.
Through our extensive work in this field, we’ve found that the most successful professionals are those who view AI as a collaborator rather than a competitor. They focus on developing skills that complement AI capabilities, like complex problem-solving, interdisciplinary thinking and ethical judgment. These uniquely human capabilities will become increasingly valuable as routine tasks are automated.
The future of AI is vertical – and it’s already here
The stakes are high. Organisations that embrace vertical AI and implement it systematically will thrive. Those that don’t risk obsolescence at an unprecedented pace. The question is not whether to adopt AI but how to do so strategically.
Based on our research and consulting experience, we recommend a three-pronged approach: First, identify the specific functions or processes where AI can create the most value. This requires a deep understanding of both the technology’s capabilities and the organisation’s strategic priorities. Second, invest in vertical AI applications that are tailored to these functions. Generic AI tools may look impressive in demos, but it takes industry-specific applications to deliver real value and a sustainable competitive advantage. Third, develop the organisational capabilities needed to maximise the value of these tools. This includes not just technical skills but also the leadership, culture and processes that enable effective human-AI collaboration.
Slow AI adoption isn’t just a missed opportunity – it’s a surefire way to fall behind. The organisations that thrive won’t be the ones patiently waiting; they’ll be the ones that fully integrate AI into their strategic DNA, treating it as the engine of future growth instead of a passing novelty.
As Bob Dylan sang,
The slow one now
Will later be fast
As the present now
Will later be past
The order is rapidly fadin’
And the first one now will later be last
For the times they are a-changin’
This shift is already underway. The winners will be those who recognise that AI, like past revolutions, is not about the technology itself but about how it transforms business, strategy, and decision-making – especially as it moves from empowering individuals to revolutionising organisational processes. Verticalisation is the natural progression, and it’s happening now.
“INSEAD, a contraction of “Institut Européen d’Administration des Affaires” is a non-profit graduate-only business school that maintains campuses in Europe, Asia, the Middle East, and North America.”
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