Blog

AI: A Tool for Human Augmentation — Not End-to-End Automation

In a recent study from the Stanford University SALT Lab (Shao et al., 2025) titled “Future of Work with AI Agents: Auditing Automation and Augmentation Potential across the U.S. Workforce” , the authors offer a thoughtful, data-driven assessment of how AI agents map to real human work. In this post, I summarise the paper's key findings—and situate them within my own AI philosophy and approach at Accéder , where I firmly believe that intelligent machines should augment humans.

Spiking Neural Networks – From Research Curiosity to Enterprise-Grade Advantage

Introduction: A New Kind of Neural Network For decades, Spiking Neural Networks (SNNs) were primarily studied in neuroscience as models of how biological neurons communicate. The complexity of their training limited their commercial potential—until recent breakthroughs in algorithms and neuromorphic hardware changed the game. Today, SNNs can be trained using surrogate-gradient methods and hybrid ANN→SNN conversion , running efficiently on GPUs or on emerging neuromorphic processors.

Agentic AI: The Excitement, the Anxiety, and the Leadership Gap

A deep dive inspired by EY’s latest Agentic AI in the Workplace report By Oscar González Iñiguez (OGI) – Founder & CEO, Accéder Artificial Intelligence has finally entered its Agentic phase — where AI systems go beyond simple tasks to act, reason, and decide alongside humans. And according to a major new study by Ernst & Young LLP (EY US) , employees are not resisting this evolution. In fact, 84% of workers are eager to embrace Agentic AI in their roles.

Neuromorphic Computing 101 – Why the Future of Enterprise AI Looks More Like the Brain

1. Introduction: AI Meets the Brain Modern AI is still built on computer architectures designed decades ago for spreadsheets and databases. CPUs and GPUs execute tasks sequentially or in large matrix batches—fast, but power-hungry and inefficient for real-time, always-on industrial environments . By contrast, the human brain runs billions of neurons on roughly 20 W of power and reacts to events almost instantly. Neuromorphic computing aims to bring this brain-like efficiency.

Beyond LLMs: Building Brain-Inspired AI for the Next Era of Enterprise Intelligence

The Current Power of LLMs in Enterprise AI Over the past few years, Large Language Models (LLMs) have reshaped how enterprises think about AI. The enterprise LLM market is growing explosively. In 2024 it was estimated at around US$4.6 billion and is projected to reach more than US$41.6 billion by 2033 , with a CAGR of ~28.3 % . Some reports estimate broader LLM / generative AI segments at CAGR ~36.9 % through 2030.

Context-Aware AI: Redefining the Future of Personal Assistance

Imagine starting your day with technology that anticipates your needs before you express them. Upon waking up, a context-aware artificial intelligence (AI) agent greets you: "Good morning. I’ve rescheduled your meeting to 11 a.m. since you didn’t get much rest last night. Also, your coffee maker is preparing your favourite blend." This isn’t science fiction—it’s the reality of contextual AI, a technological revolution turning machines into proactive and highly intuitive personal assistants.

How Artificial Intelligence is Transforming Businesses in Mexico, the United States, and Canada

The adoption of artificial intelligence (AI) is rapidly reshaping the productivity landscape across North America. Mexico, the United States, and Canada are at the forefront of this transformation, with an increasing number of organizations integrating AI technologies to optimize operations, reduce costs, and remain competitive in the global market. The Case of Puebla, Mexico: A Transformation Model In Mexico, Puebla stands out as a leader in this movement, with over 75,000 businesses leveraging AI to enhance efficiency and effectiveness.