Think. Automate. Transform.

As 2025 approaches its conclusion, I thought to share on where AI stands today and what must be done in 2026 to transform it into a trusted business partner rather than a source of fear. This year has been a decisive turning point in the evolution of artificial intelligence. What once felt like experimental promise has now become an indispensable force across industries. No longer limited to pilots or niche use cases, AI has matured into a mainstream driver of productivity, creativity, and innovation. From healthcare diagnostics to financial forecasting, supply chain optimization to personalized education, its impact is both visible and undeniable. Yet, with this rapid growth has come a parallel wave of anxiety. Employees worry about displacement, customers question the ethics of data use, and societies grapple with the implications of machines making decisions once reserved for humans. Fear, often fueled by misinformation or lack of transparency, has become a barrier to adoption. Th...

In the evolving landscape of artificial intelligence, the idea of a “brain switch” - a mechanism to activate or deactivate cognitive power on demand -   is no longer just a metaphor. It’s becoming a design principle. Just as the human brain toggles between rest and focus, AI systems are increasingly being built with the ability to regulate their cognitive load, switching between passive observation, active reasoning, and strategic inaction based on context. This concept is already visible in everyday AI applications. Take virtual assistants like Siri , Alexa , or Google Assistant . These systems remain in a low-power “listening” state until activated by a wake word. Once triggered, they switch into a high-cognition mode - parsing language, retrieving data, and executing tasks. This is a literal implementation of a brain switch: conserving energy and attention until a stimulus demands engagement. Autonomous vehicles offer another compelling example. Self-driving cars continuou...

This month’s my tech series blogs dives into AI’s emotional ripple effects - how it shapes mental health, fuels loneliness, and deepens social isolation. As these tools weave into our daily routines, their psychological impact deserves just as much attention as their technical brilliance. We kicked off with AI Hallucination; today, I’m excited to share the second chapter: AI Psychosis . Let’s keep peeling back the layers. AI hallucination and AI psychosis are metaphorical terms used to describe errant behavior in artificial intelligence, but they differ in scope and implication. AI hallucination refers to an AI generating false or fabricated information that appears plausible - like inventing citations or misquoting facts - often due to gaps in training data or misaligned reasoning. AI psychosis, while not a formal technical term, is sometimes used provocatively to describe more severe, systemic breakdowns in AI behavior, such as persistent delusions, incoherence, or erratic out...

In this month technology series, we’ll dive into the lesser-discussed emotional dimensions of artificial intelligence - how it can influence mental health, contribute to feelings of loneliness, and even intensify social isolation. As AI tools become more embedded in our daily lives, understanding their psychological impact is just as important as grasping their technical capabilities. To begin this journey, let’s explore a foundational concept: AI hallucination. Put simply, AI hallucination happens when an AI makes things up. It might give wrong answers, invent fake facts, or describe things that don’t exist - like saying the Eiffel Tower is in Berlin or generating an image of a cat with three eyes. These mistakes aren’t intentional; they occur because the AI is trying to be helpful and sound confident, even when it doesn’t fully understand the question or lacks accurate information. It’s a bit like someone guessing with great certainty - and getting it completely wrong.  From a ...