Stripe announced a paradigm shift this week that makes it clear the digital landscape is changing. In our newsletter, we’ll be sharing information to help the nonprofit sector prepare for the new digital reality.

Our stance, as always, will be: sovereignty, security, and ethics. In this edition, we summarize Devin Santos’ article about LLMs in 2026. LLMs (Large Language Models) are a type of AI trained on massive amounts of language data. Like a glass of juice with all the fruits and vegetables in the world, blended and digested in one gulp.

Before, they could process, understand, and predict text. Now they can reason, make decisions, interpret, write code, and automate workflows.

These enhanced capabilities mean that LLMs are central to the digital transformation strategies of any foundation or association. They help organizations reduce costs, scale faster, and generate insights in ways that previously required too much manual work.

Here are some examples to help you understand better. LLM applied in some sectors.

1. Analysis of medical records, follow-up management, and digestion of complex reading volumes

• LLM analyzing medical records, reading large volumes of scientific information to identify potential medical treatments, drugs, and research.
• LLM responding automatically, quickly, and accurately to patients.
• LLM reviewing contracts, suggesting changes, and updating to evolving regulations.

2. Prediction and Decision-Making through Patterns

• LLM detecting patterns to reveal potential anomalies and prevent fraud.
• LLM detecting patterns for authorization (e.g., loans).

3. Personalized Information at Scale

• LLM creating content tailored to each individual.
• LLM evaluating and rating, answering questions 24/7.
• LLM recommending products and predicting purchase intent in real time.
• LLM interacting across different channels and in multiple languages. It’s clear that the focus is on efficiency, scalability, personalization, and eliminating friction.

But it’s not all perfect. There are risks such as hallucinations, risks associated with sensitive information, reproduction of training biases, and long-term risks.
To manage these, an ethical AI framework, continuous data validation, and transparency are recommended. AI governance will be key to balancing innovation and trust.
The winners will be those who adapt quickly and build responsibly. We will be there to confidently evolve toward whatever the digital future holds for foundations, associations, cooperatives, and other non-profit organizations in Spain, Latin America, and the rest of the world.