TL;DR:
AI adoption is creating a massive divide between businesses that adapt quickly and those that delay.
Most small and medium businesses are stuck in outdated AI evaluation cycles while the technology rapidly evolves.
Traditional business constraints are disappearing as AI makes bespoke software development dramatically cheaper.
Companies are shifting from providing software tools to delivering direct business outcomes through autonomous systems.
The current tech landscape requires continuous adaptation rather than periodic innovation cycles.
The scales are tipping in favor of the bold and adventurous builders. Computers are getting smarter by the day, adopting personalities, and gaining access to programmatic infrastructure for value. Everyone's talking about AI, but how many companies are ready to meaningfully adapt their businesses?
There is a silent renaissance in progress. One that will rewrite the rules of business. Yet, many business operators have every reason not to pay attention. And I don't blame them.
Less than a year ago, I was the CEO of a mature SaaS company. We talked a lot about AI and ran some experiments. But the responsibilities and priorities of daily business life took precedence. It's a tale as old as time with disruptive innovations.
It's been ≈two and a half years since ChatGPT dropped. The pace of improvement since then has been nothing short of staggering. In practice we’re about to commoditize the average knowledge worker. Yet my conversations with friends across various businesses reveal that adoption and experimentation remain stuck in that "ChatGPT moment".
The rules of business are being rewritten in real-time. It’s going to create a massive bifurcation in the business landscape: Those who gets it and those that don’t (or get it too late).
AI agents running autonomous micro-businesses. Single founders operating swarms of agents to build billion-dollar solo ventures. Agents embedded in existing companies, replacing some humans, coordinating with others.
None of this is sci-fi. It’s all either happening or going to happen – soon.
The transition won't happen overnight. Some changes will be so gradual that incumbents miss them completely. Others will make headlines that shake everyone to their core:
What happens to software engineers when agents write better code?
What becomes of management consultants when agents can research and present pretty slides in minutes?
How do creative agencies compete when AI can generate and iterate on campaigns in seconds?
Legacy businesses face a stark choice: cling to path-dependent models and risk
obsolescence, or venture into the uncertain terrain of AI and blockchain.
Small and medium sized businesses, particularly service-oriented ones will likely be the slowest to adapt. There are several reasons why:
Path Dependence
Talent Gap
The Time Lock Trap
Principal-agent problem
Path dependence is the most expensive fallacy in business. Historical decisions constrain future adaptability, and right now, that's severely limiting everyone's ability to adapt. Companies find themselves trapped by their past investments - in technology, in processes, and most importantly, in mindset.
Then there's the talent gap. It's particularly pronounced in the early phase of tech diffusion. Over time, efficiencies will embed down the stack into software. But for now (and likely the next ≈5 years), there will be big competitive advantages to gain by adapting and adopting early.
Many parts of both AI and blockchain are in “raw” states. This creates a technological threshold.
The problem isn't just about technical skills. It's about understanding the potential of these technologies to reshape entire business models. Most organizations lack people who can bridge the gap between traditional business operations and emerging technologies.
Here's how AI adoption typically goes at a company: Form a task force. Evaluate potential for a set period. Propose solutions. Adopt some, throw away most. Go back to business as usual.
The problem? While your task force is finding something impossible to solve with AI today, your competitor's figuring out how to do it tomorrow. Much of the "AI evaluation" happening at SMBs comes from board directives, with management more motivated to check boxes than unearth uncomfortable truths about the new rules of business.
This traditional approach to innovation adoption simply doesn't work in the current environment. The pace of change is too rapid, and the implications too profound, for periodic evaluation cycles.
This trap is understandable, for a service-oriented business, there’s nothing natural about rigging an “always-on” tech function, but it may be what’s required in order to continuously adapt as the tech evolves.
There's another challenge lurking beneath the surface: misaligned incentives. The principal-agent problem occurs when decision-makers act in their own self-interest rather than in the best interest of the organization.
In the context of AI and blockchain adoption, this manifests in several ways:
Managers protecting their territories from automation
IT departments resisting changes to established systems
Executives avoiding risky but necessary technological transitions
Boards preferring short-term stability over long-term adaptation
We're moving from software as a service to agents that deliver outcomes. Take customer support - it's historically been great business building customer service tooling. But what if instead of getting tools to do customer service, you get software that does customer service for you?
This shift fundamentally changes the value proposition of business software. It's no longer about providing tools for humans to use, but about delivering direct business outcomes through autonomous systems.
But, this dynamic impacts much broader than software/tech businesses.
Cost compression in software development is unlocking new possibilities. Traditionally, two things limited how much we could build software into business processes:
Level of complexity
Software-to-human labor ratio
In some case, we hit at technological ceiling. In other cases it was just better ROI to solve with human labor.
We’re now entering a phase where the cost of building bespoke software is collapsing. Previously unthinkable, today a mid-sized service SMB could build their own bespoke agent-based software to both fully automate and semi-automate (with human coordination) major operational workflows, and even entire business functions.
I think there’s a double-digit profit margin increase potential from adopting AI augmentation for these types of businesses in the years ahead.
But most won’t. For all the reasons stated above.
Just as we saw the emergence of digital-native companies in the internet era, we're now seeing the rise of AI-native organizations. These aren't just businesses that use AI tools - they're enterprises built from the ground up around AI capabilities.
Characteristics of AI-native organizations include:
Continuous learning and adaptation
Automated decision-making processes
Dynamic resource allocation
Real-time market response
Scalable operations with minimal human intervention
For legacy businesses, adoption is a massive challenge. But for those who manage it? The competitive advantages are extraordinary. It requires an always-on tech layer that continually iterates.
This makes me think there’s an opportunity for a new kind of private equity/holdco play, where the AI capabilities sits at a parent level. I expect we’ll see some of these strategies emerge soon.
Another example is what crypto investor Santiago Santos is doing with his new fund, Inversion Capital. Building their own blockchain network, acquire businesses and unlock efficiencies by putting those businesses on crypto rails. In this case, the blockchain network becomes a business operating system. There are many interesting strategies that can be imagined from this basis; acquiring businesses via the treasury of a blockchain network, launching cross-business incentive and reward mechanisms (again funded by treasury grants).
If the above paragraph makes your head spin, it proves my point.
Many of the unlocks and strategies that can be executed as a function of these technologies require deep understanding of those technologies in the first place.
The rules of business are being rewritten. We're moving into an era where the boundaries between human and machine capabilities are increasingly blurred, and where traditional business constraints are being eliminated by technological advancement.
The question isn't whether to adapt, but how fast you can do it before the tumble dryer cycle ends. Those who embrace this renaissance early will help shape the new paradigm. Those who wait may find themselves playing catch-up in a game where the rules have fundamentally changed.
As always, reach out to me on X or Farcaster if you have feedback or are working on something cool you want to discuss.
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