Fast and to the point...
Companies (as we know them) suffer in the present and are not organizations adapted to the future.
Because?
Because the model emerged a hundred years ago, with the purpose of raising enormous sums of capital, to invest in machinery (assets) and be able to reach production scale.
So that?
To gain access to new consumers, the emerging middle classes, with competitive costs.
In short:
Companies, as we know them today, are structures of repetition in scale.
And then?
The problem is that repetition is fragile to increasing shocks and disruption. Business models do not survive and must adapt.
Traditional barriers to entry (including capital) are not enough.
And on the other hand...
The context is brutally different. For example, what do consumers have in common?
Practically nothing.
They don't accept generic products, customization is the norm, they look for value and purpose.
But also...
Exponential technologies cause the marginal cost of production to tend to 0 and we do not depend on capital.
Starting without capital with new methodologies is possible and increasingly common.
Organizations no longer necessarily have to employ thousands of people.
Today it can be undertaken without initial investment, without thousands of employees, and without financial risk. But most continue to operate with old theory.
Conclusion?
Business theory needs to adapt, and in the last 20 years, it has completely changed.
The problem?
The information does not reach entrepreneurs or businessmen, it is sleeping in the books.
The best explanatory theory of what is happening is by Clayton Christensen, and rests on a 1997 book.
Yes, more than 25 years ago.
Christensen explained that disruption begins when startups accompany the evolution of a new technology by entering through the margins of the market.
First they serve users ignored by the leaders: unprofitable niches, small segments. Then, as technology improves, they take the incumbents' lower-margin niches. And when functionality is sufficient to enable progress toward the mass market, they go all-in.
By then, it's already late. Disruption occurs. And the leaders are left out of the game.
Christensen calls it the Innovator's Dilemma, because the rational behavior of CEOs leads them to defeat. Focused on protecting profitability, responding to shareholders and taking care of their best customers, they neglect the future.
That was the classic cycle.
But now, with the democratization of generative Artificial Intelligence, everything changes.
The functionalities enabled by this AI no longer take years to mature. With each updateweek by weekcapabilities emerge that match or surpass existing solutions.
And startups can, from the start, solve real problems on a massive scale. No capital. No infrastructure. No heavy structures.
(Another chapter is how to sustain that advantage: democratization also shortens the adoption delay by incumbents, leveling the field).
Disruption no longer warns. And many times, there is no time to prepare. It no longer advances step by step. Break in. And transform.
Therefore, continuing to operate with the usual assumptions is today the biggest risk for any organization.
My advice today?
Don't stop learning about business, strategy and innovation. AI is not a technical topic. It is a strategic issue.
Big hug, Francisco Santolo
How to apply AI with sense, strategy and real value and not invest in technology without criteria!
Artificial intelligence accelerates but does not cause the business revolution. The organizations we know as companies, created to repeat at scale, have a prior expiration date.
It is true that AI has been dictating the winners for 2 decades: Amazon, Google, Netflix, Alibaba, Tencent, among others, leveraged AI.
Today generative AI democratizes and accelerates. Transform the way we work, decide and create value. But the real challenge is not technological: it is strategic, organizational and human.
I see it all the time: companies paralyzed by the complexity of AI, while others rush to hire agents, buy solutions or automate without clarity or meaning.
What do they have in common? They start with technology and neglect strategy, they put the tool over the value generation and capture model.
The starting point, however, should be something else: the intuitive, exploratory and strategic understanding of the impact that AI can have on the business. And for that we must always focus on the business actors.
Before investing time, money or efforts in LLM, tools or agents, it is necessary to ask ourselves: What part of the business model or operating model can be enhanced with AI?
What differentials can we develop? What actions of our competitors or substitutes could be a threat?
Where are we repeating tasks that could be automated? What key decisions could be better supported by data? What part of the customer experience could be further personalized? Where could we gain scalability or speed without losing focus on the value we provide? What scope does the data we have and can acquire enable us to innovate in new industries or verticals?
This analysis allows for something fundamental: aligning AI with strategy and organizational design, and not simply using it as a fad or an accessory. When that happens, AI stops being a solution imposed from the outside and becomes an internal engine of continuous improvement, efficiency and learning.
Not all organizations need the same thing. Not everyone should apply the same tools. Therefore, before replicating what others do, we need criteria to evaluate, design and build our own way of integrating AI, according to our purpose, context and capabilities.
AI can fulfill different roles within the company: It can be a layer of intelligence that amplifies collective knowledge, a data-based learning system that adjusts and improves processes, or a tool that frees up time and energy for more creative and strategic tasks.
But its value is not in what it does on its own, but in how it integrates into the value design that already exists. It is not about replacing people, but about empowering them. It's not about following fashion, but about thinking strategically.
The organizations of the future will be those capable of turning data into decisions, learning into adjustments, iterations and pivots, and tools into sustainable results. Where AI does not replace, but rather enhances, human intelligence and the ability to positively impact.
Therefore, the true path is not technical, it is organizational. It is culture, it is strategy, it is a business and value model.
And like everything worthwhile, it begins with understanding, testing, applying, measuring and adjusting. In community, with criteria, and with a very clear focus: generating value for key actors, always taking care of what is most important: people.
What do I offer you to continue learning and applying:
I recently taught a class for HR managers on the use of AI and virtual collaborators in Training & Development, with specific cases, applicable tools and strategies to implement it gradually and effectively. I largely demonstrate that almost no technology, tools or programming is needed when you clearly understand what you want to achieve.
Many of those ideas can be transferred to other areas of the business. ?? If you want to take that class, write IA in the comments and I'll be happy to share it with you.
Additionally, if you want to continue exploring this path, I invite you to join our Scalabl® AI Learning Community, where we explore together real AI applications for business, productivity and strategy. With live masterclasses, practical content and a global community to share and co-create value. ?? You can learn more at ?? www.scalabl.com/ia
