Novas regras de BaaS podem elevar custos e concentrar mercado
Imagem: Finsiders Brasil | gerada por IA via ChatGPT/OpenAIAnálise da Tendências, a pedido da ABBaaS, aponta impactos especialmente para empresas menores e especializadas
Imagem: Finsiders Brasil | gerada por IA via ChatGPT/OpenAIAnálise da Tendências, a pedido da ABBaaS, aponta impactos especialmente para empresas menores e especializadas
Em contexto
- Tema: Inteligencia Artificial — IA aplicada al negocio: casos, límites, costos y gobierno.
- Fonte: Finsiders Brasil
- Publicado: 14/10/2026
Continuar lendo na fonte original →
Trecho publicado automaticamente pelo radar do site. O texto completo pertence ao veículo e está vinculado acima.
Why it matters
Adopting AI in a company is less like buying software and more like hiring someone. You have to teach it the context, review its work at the start, and define what it can sign off alone and what it cannot. The stories worth reading are the ones showing somebody solving that part, not the announcement part.
I measure AI maturity with an uncomfortable question: can anyone explain, in one line, what decision the model makes and who answers if it gets it wrong? Where that is clear, the project moves. Where it is not, it stays in permanent pilot and gets cancelled with the excuse that the technology was not ready.
What usually goes wrong
The mistake I have seen repeat most is measuring nothing before starting. It gets deployed, everybody feels things improved, and when somebody asks by how much, there is no answer. Without a baseline there is no way to defend next year's budget, and that is where good projects die.
What to watch
- Where the data ends up and under what contract, especially when customer information is involved.
- Whether the organisation can change provider without rebuilding everything, which is the proof it did not get locked in.
- Which concrete process is touched and how it is measured before and after; with no baseline there is no result, only opinion.
How I read this entry
I would use it for a talent conversation rather than a purchasing one. The capability that needs installing is not operating a tool, which changes every six months, but framing the problem well and judging the answer. That one stays in the house.
The original story is published in another language; the excerpt is quoted as the publisher delivers it and the commentary is written in English.
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Living through this in your own team?
Open the chat and tell me how you're handling it. I'm interested in comparing notes.
