We Have Entered the Adoption Era: why creating has never been easier, and driving adoption has never mattered more

We have entered the Adoption Era.

This is not a software problem. It is a shift in the limiting factor of the economy. For decades, the question was: how do we build faster, cheaper, with fewer people? Today, thanks to AI, developing an internal tool, prototyping a process, documenting a procedure, or launching a SaaS takes a fraction of the time it did five years ago. A consultant produces in two weeks what used to take six months. An executive can code a prototype alone that they would have outsourced.

Humans, however, do not learn faster. They do not change faster. They do not decide faster. The gap between machine speed and organisational speed has never been more visible — and that is exactly what thousands of SMEs are living through right now.

The easier it becomes to create, the harder it becomes to make something a standard.

Relative Cost Theory

Here is what has inverted. Not an opinion — an economic structure.

Building an internal ERP used to take eighteen months. Today, four months is sometimes enough. Training teams? Still six to twenty-four months. Time did not compress on both sides equally.

I see this pattern every week in SME cases: services, light industry, distribution, construction. The founder invests — sometimes €20,000, sometimes €200,000. The demo is convincing. The launch is announced. Three months later, the conversation has already shifted. You almost never hear: "We underestimated how long it takes to change a habit." Yet that is often the right reading.

Why everyone gets it wrong

Three views of the same numbers

Nobody is wrong. They are observing three different problems. The executive looks at the number of users today. The project manager looks at the quality of the solution. The employee looks at their immediate workload. In reality, success depends mostly on the speed of human change adoption — which follows curves documented for over sixty years.

Behind the numbers, there is often silent guilt. The executive signed the budget. They convinced the board or their partner. They announced the transformation with fanfare. When the numbers stall, the thought loops: "I made the wrong decision." That fear pushes them to redo the project — change tools, change vendors, relaunch an RFP. Sometimes that is the right call. Often, it means starting from zero at exactly the wrong moment.

The classic scenario: panic → tool change → still 3 users out of 10 → "My teams resist change" → counter reset to zero. Six more months lost. Sometimes twelve.

Changing software almost never resets habits to zero. It always resets learning to zero.

Imagine being offered a keyboard that would let you type 30% faster — once mastered. On day one, you would be twice as slow. If you measured only the first week, you would conclude the keyboard is a disaster. The problem would not be the keyboard: it would be the adaptation period. That is exactly what teams experience when a new tool is imposed on them.

Same logic with the dishwasher: as long as the sink remains an acceptable alternative, some people will keep washing by hand. As long as Excel remains possible without consequence, some teams will keep using it. This is not bad faith. It is cognitive economics.

Case A or Case B?

If your platform has 3 users after 6 months, don't first ask whether you built the wrong tool. Ask whether you are in the middle of the curve.

This is not a software problem. It is as old as humanity.

As we saw with Rogers' curve, innovations that transform the world almost all go through a phase where they seem to fail. An executive looks at their project six months after launch. History looks at innovations five to twenty years later. It is like judging a marathon at the third kilometre.

The printing press took decades to transform society. The telephone took years to become a household object. The Internet took more than twenty years to reshape commerce, communication, and information. Each went through a period where serious observers doubted its real utility.

The iPhone, in 2007, was "useless" for much of the market. BlackBerry dominated. Nokia dominated. The physical keyboard was considered essential. Analysts called it a gadget. Then habits shifted — not in one year, but over a decade. BlackBerry and Nokia did not disappear because their products were bad. They disappeared because the market eventually adopted a different gesture.

ChatGPT, late 2022, was a "gadget" for many executives. By 2025, AI projects are everywhere — not because the idea was new, but because the market was finally ready to adopt it. The innovation was not the problem. Adoption timing was.

Microsoft Teams is the most telling illustration for businesses. Millions of licences paid for long before real use — employees kept using email, Skype, or WhatsApp. Then integration into Microsoft 365, the removal of Skype for Business, imposition as the official channel, and the 2020 pandemic shifted behaviours. Roughly 20 million daily active users by late 2019, roughly 75 million in April 2020, over 300 million in 2023. The software did not change as much as the organisations did.

Slack followed the same trajectory. Launched in 2013, the dominant objection was: "We already have email." The first teams to adopt were mostly developers and startups — classic early adopters. Then leadership noticed fewer emails, faster decisions. Roughly one million daily active users in 2015, over 12 million in 2019, before a Salesforce acquisition for nearly $28 billion in 2021.

ERPs are the closest example to SME transformation. Week 1: "Why can't we do it the old way?" Month 2: "It was simpler with Excel." Month 8: gains appear. A year later: nobody wants to go back to the old system. ERP integrators have long known that a successful project is as much a human project as an IT project.

Project timeline

The worst moment to judge a transformation is often when the tool already works, but habits have not yet changed.

What this changes

Adoption pyramid

Everyone talks about the first two levels. Winning companies master all six.

Create → Deploy → Drive usage → Drive preference → Habit → Standard. Most projects stop at deployment. They confuse "the tool is available" with "the tool is adopted." Software is not adopted when it is installed. It is adopted when it becomes harder to work without it than with it.

LinkedIn is saturated with posts like "I built a SaaS in a weekend" or "Here are the 50 best prompts." Very few talk about the day after — the real adoption time, the months when nobody uses it, the pivots needed to shift habits. Creating is spectacular. Adopting is invisible. Yet that is where projects succeed or fail.

The cost of attention

AI explodes the quantity of available innovations. It does not explode teams' cognitive capacity to absorb them. More tools, more agents, more workflows — no more capacity to change habits in parallel.

The cost of attention rises. The cost of change rises. Competition for habits rises. This is not an individual productivity problem. It is a real economic shift: scarcity is no longer the ability to produce, but the ability to capture and retain organisational attention.

Sales is adoption. Consulting is adoption. Startups are adoption. Internal platforms are adoption.

A company that sells drives adoption of a solution. A consultant drives adoption of a way of working. A startup drives adoption of an innovation. An internal platform transforms habits. Laws, management, products, markets, cultures — all follow the same pattern. This is not a software topic. It is a systemic one.

This concept extends what I formalised in The Substitution Illusion: AI accelerates, it does not replace. Here, it accelerates creation so much that the gap with adoption becomes unbearable — and visible.

See the full definition in the System Lexicon →

The new rules of the game

For thirty years, company valuation rested on the ability to create faster than competitors. AI transforms that equation: creation becomes a commodity. What remains scarce is internal adoption, the ability to convince a market, the speed to turn an innovation into a standard.

The next monopoly will not be creation. It will be adoption.

The new factor of production is no longer design — that has become a commodity. Scarcity is driving adoption: an idea, a product, a method, a transformation, a culture. Change management, sales, marketing, product, and economics converge on the same bottleneck.

Six levers, four mistakes

The four mistakes that kill adoption: keeping the software optional while the old system still exists; imposing double entry (Excel + platform); not using the tool yourself as an executive; never sanctioning non-use. A platform never becomes the standard because it exists. It becomes the standard because the previous standard disappears.

The six levers that work: start small — one process, one friction point; choose two or three natural ambassadors and let them train others; set an end date for old circuits (no more WhatsApp for this flow, no parallel Excel); measure what matters — tasks completed, time saved, errors avoided, not just logins; communicate wins every week; lead by example from the top — open the platform in meetings, refuse workarounds.

For the operational angle — the 85% of AI projects that never reach production — see: Why thousands of companies will die from AI automation.

For two centuries, the economy rewarded those who knew how to produce.

For twenty years, those who knew how to digitise.

For a few years, those who knew how to use AI.

The next decade will reward those who know how to drive adoption of what everyone is now capable of creating.