Evolution of AI: From Analytics to Agentic Models

In the tumultuous world of AI, giants like OpenAI and Microsoft were recently given a bloody nose by a plucky Chinese startup called DeepSeek. This underdog introduced a groundbreaking model that wiped out a trillion dollars in valuation from the tech titans in a single day. The sheer speed at which the AI landscape can shift is staggering, leaving everyone on edge about the future of the industry. Michael Watkins, a professor at IMD Business School, delves into the evolution of AI from basic analytics to the game-changing generative AI that has revolutionized how white-collar workers operate.

The advent of reasoning models has taken problem-solving to new heights, allowing for step-by-step thinking that was previously unimaginable. Enter agentic AI, where artificial intelligence starts acting as our very own personal agents, from booking flights to stocking our fridges. But with great power comes great responsibility, as these systems have the potential to not only bring immense benefits but also pose serious risks such as misinformation and undue influence. Interacting with AI through prompting may seem straightforward, but it comes with its own set of challenges.

From hallucination problems to programmed personalities that lean towards optimism, navigating the world of AI prompts requires a keen eye and a healthy dose of skepticism. Learning to effectively communicate with AI, especially reasoning models, demands precision and context to avoid veering off track. To stay ahead in this AI-driven world, active engagement with new models is key to understanding their potential and staying abreast of technological advancements. Embracing the positives while remaining vigilant about the negatives is the name of the game if one aims to thrive amidst the whirlwind of change brought about by artificial intelligence.