Why Should I Subscribe To Your SaaS?
Apocalypse Or Not, Needs To Be Managed
Hey, fellow Leader 🚀,
I am Artur, and welcome to my weekly newsletter. I am focusing on topics like IT Management, Innovation, and Leadership, with an Entrepreneurial mindset. My goal is to help you navigate the IT corporate landscape. Make better decisions, create awareness, and share real-world stories.
One of the big effects of AI is its impact on the SaaS ecosystem.
Using AI as a means to leverage coding is creating an image that some solutions might be built in-house instead of being bought through a procurement process.
It doesn’t matter who is right or wrong. What matters is how we navigate this uncertainty, and how we pull the best strategy for our teams and solutions.
An important alert: We are all saying that AI is speeding up development.
However, this might not be true. A study conducted by METR in 2025 concluded that development was 19% slower, while developers had the perception that they were 20% faster.
However, METR revised the same study in 2026 without finding conclusive productivity gains yet.
The reason: AI is too fresh, too new, and people are still adapting to AI.
My advice: Hold off on deep structuring of the IT department (layoffs or starting to replace SaaS with massive in-house built solutions).
The SaaS Apocalypse
We are starting to read everywhere that SaaS will have a hard time because of AI.
Why do I need to buy your SaaS if I can build it in-house cheaper?
The reasoning behind the SaaS apocalypse makes sense. However, some companies might not have the IT structure to have multiple complex products built in-house.
It’s a valid management consideration.
However, I strongly advise being cautious when making these decisions.
It is not clear what are the impacts of AI are on the development process as of today. Making too many rushed decisions can cost the company strategic momentum.
Also, it is not clear how much development is being sped up with AI.
It is important to mention that code production is only one part of the complex challenge of building software: Stakeholder management, business requirements, and testing strategies are key pieces as well.
Agreeing on how to approach a problem, testing it, with a strategy that conveys to multiple stakeholders, is still a complex problem that AI barely scratches the surface of.
Code production is just one variable of many in Software Engineering.
The idea that AI can be leveraged to replace SaaS subscriptions is valid and should be analyzed. However, it is important not to take on a challenge too big to handle.
In the meantime, the SaaS ecosystem is indeed challenged by the possibility that many of its customers will replace its offer with in-house solutions. Or, their competitor leveraging AI could move faster than before, outpacing their current solutions with better features and overall products.
The uncertainty is high, and you (as client) should take advantage.
Negotiate Your SaaS First
Before moving in any direction, just assess how much your current vendor is offering. It is possible that the price might not change, and maybe you can get a more competitive offer.
Gaining time to see how AI will move next is your best option right now for a conservative approach.
If you have systems that you feel are too expensive for what you are paying, maybe it’s a good opportunity to evaluate the idea of launching an RFP process and maybe switching vendors.
For this last option, we should calculate the cost of such a project: How much CAPEX (investment is needed) and how much OPEX (operational costs) the vendor will be offering.
This provides a good overview of what the financial costs of switching vendors would be and the payback period of such a move.
An important consideration while negotiating your new price is also to adjust the timeframe.
What I call “Forever Systems”, which are systems that are core but don’t require any investment in innovation, make sense to have extended contracts (3 to 5 years).
However, for other systems, it would make sense to negotiate the terms for short periods (1-2 years).
The goal of these shorter periods is to assess how AI will impact the market, if there are different vendors with a more competitive offer.
Or if, in the meantime, the company gets the internal capability and conditions, it might be worth analyzing if the product can be built in-house.
Let’s Do It In-House?
While you are running numbers, maybe it is interesting to check internally how feasible it is to build the solution yourself.
However, be mindful:
Do you have the internal development teams capable of producing the software at the required level?
Do you need to recruit developers during the “Project Phase”?
How many developers would you need to maintain the new system?
What are the custom-built requirements you would like to have in an in-house solution?
Where will the solution be hosted? Is the support and infrastructure team sized to maintain the new platform?
Are there any extra licenses required to build and maintain the new system?
There are a lot of questions to be asked about the decision to build in-house.
Mostly, the goal is to answer these questions and transform the answers into a figure that you can calculate in a spreadsheet.
The greatest advantage of having an in-house product is that you are building your custom, tailor-made solution, which can greatly leverage the company’s added-value and better distinguish it from the competition.
However, is this new set of features worth the investment? Add a 10–15% delta to the financial figures to absorb any misfortunes.
These decisions need to be made pragmatically.
Overall, use the shadow of the SaaS apocalypse to your advantage as a client.
It has been a wild ride since I published the first article on the SoW. Exchanging views with you and hearing feedback on how these articles have been useful is what drives my motivation to write. Leave a comment, subscribe to the SoW, and be part of the community.
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Cheers,
Artur