In the era of Generative Artificial Intelligence, the boundary between software and services is disappearing. A boundary that was once clear: The software manufacturer would "wash their hands" of a poorly executed deployment and reap the rewards when it was done well. It was part of the game.
The article from Sequoia Capital, “Services: The New Software”, proposes a provocative thesis: with AI, we have stopped selling just SaaS tools for people to work with; we have entered the era in which we sell the Work completed (outcome).
Intelligence vs. Judgment (critical thinking)
In software development, writing code is primarily a matter of intelligence. Knowing what to build involves judgment, which requires experience and common sense, an instinct that develops over years of practice.
This includes decisions about which features to implement, taking on technical debt, or when to release an incomplete product. Software engineering accounts for more than half of the use of AI tools in professions, as it is, to a large extent, a job of intelligence.
The Accountants' Example: Tool vs. Shared Responsibility
I hear a lot about the end of accountants, but for a small business in Brazil, the cost can start from R$119.00 per month with Omie, Contabilizei, or Conta Azul, plus around R$1,000.00 per month for a good accountant to close the books and who you can talk to if you have questions or when the tax authorities come knocking.
Therefore, as long as these platforms are not jointly responsible and truly supportive in the event of an audit or accounting and financial strategy, they will remain just tools.
The End of the Era of Body Shopping
I had never worked with staff allocation, and when I entered the ServiceNow market, I was told: "Here it has to be Bodyshop; otherwise, you won't succeed." I don't know if it was due to my lack of experience in "selling people" (BodyShop) or my extensive knowledge in genuine consulting projects, but we decided not to sell a single BodyShop, and the market reacted very positively to that.
Thus, when a company simply "allocates" people without critically addressing business problems, it ends up competing directly with automated models, whose operation should be scalable and extremely inexpensive.
Thus, in this context, the focus shifts from the ability to "do" to the ability to "decide what to do," highlighting the importance of human judgment and strategic intelligence in today's business environment.
The Dilemma of Software Giants
You must be thinking, who is he to question the success models of giant, trillion-dollar software manufacturers like SAP, Microsoft, Salesforce ServiceNow, Monday, etc.? And you'd be right: I'm just another person in the bread line.
But from my place in line, I can see that these giants are already facing structural obstacles. That's because the model that made them billionaires is, ironically, what makes it most difficult for them to adapt to the AI age.
Normally, these companies charge per seat, per employee, per agent, per resolver, or per asset, and today they realize that the AI narrative is: reduce the number of agents, with my AI resolving issues automatically.
Since Wall Street never sleeps: Transitioning to a "pay-per-performance" model rather than a pay-per-target model is an extremely high-risk financial maneuver for these companies.
New Revenue Models
The Sequoia article states that for every $1 spent on tools, $4-$6 is spent on services (consulting, implementations, or recurring and managed services).
Now, consulting firms may be well positioned because they already:
- They sell results instead of licenses.
- They operate within the client's processes.
- They understand where human judgment is needed and where automation can replace it.
- They have a relationship with the customer.
Therefore, instead of selling hours to configure a module, a partner could sell a guaranteed business outcome (e.g., "automated IT integration") supported by a proprietary AI agent built on the ServiceNow platform. Zero risk for the customer!
Conclusion: Evolve or Become Utilitarian
The message is clear for both service companies and software manufacturers.
For service companies, the imperative is to become "Full-Stack": not just suggesting technology, but building internal AI layers that make their consultants superhuman, delivering high-value end results.
For software giants, the challenge is both strategic and cultural. They need to decide whether they prefer to be the tool used by humans or the engine that replaces human labor. However, they know that the second option destroys the subscription-based growth model that sustains them today.
In the age of AI, software is the service, and intelligence is the orchestrator that decides who will capture the value generated.
Consolidated analysis based on Sequoia Capital's thesis and the challenges of the current SaaS ecosystem.
Article produced by Marcelo Theophilo, CEO of 4MATT.
With over 20 years of experience in the IT industry, he is the Director of ITAM, ITOM, and CMDB Services at 4MATT. We are a leading ITAM and CMDB consulting firm in Latin America. Marcelo holds certifications in SAM, FinOps, ITIL, COBIT, and ISO 19770 and is a CMDB specialist on the ServiceNow platform. He also has experience in projects for medium and large-sized companies.
Recognized as Microsoft's Leading Software Asset Management Consultant of the Year for Latin America, Marcelo has spoken at over 180 events on ITAM and SAM. He is also a member of the FinOps Foundation, ServiceNow Practice Leader at 4MATT, and Chapter Leader of the ITAM Forum in Brazil.
