2025 Year in Review: Artificial Intelligence
Isolated tools or experimental demos no longer define artificial intelligence; it is rapidly becoming an active participant in how work, media, and systems operate. What once felt like incremental progress has now entered an acceleration phase, where AI systems are beginning to reason, create, and learn in ways that directly shape real-world outcomes.
As 2025 wraps up, several shifts signal a meaningful transition in the AI landscape. From autonomous agents that can plan and act independently, to video generation technologies that blur the line between what is real and what is synthetic, and even to growing concerns about the limits of available training data, AI’s evolution is raising both new possibilities and new questions. Together, these developments offer a glimpse into where artificial intelligence is heading and what that trajectory means for society, trust, and the future of digital systems.
AI Agents Are Here
After AI tools, mainly LLM-based ones, gained popularity as productivity boosters in recent years, 2025 was destined to be the year of the AI agent. Unlike previous tools, agentic AI is designed to reason, plan, and act independently: setting goals, breaking them into actionable steps, and executing tasks across systems with minimal human oversight.
Real-world examples remain largely unexplored, but the potential and interest are clear. We’ve already glimpsed the future of AI agents in new AI browsers that can plan trips for you, identify your needs, and purchase necessary items, all while ensuring on-time delivery. Concerns exist about impacts on the workforce and governance of these agents, but the hype remains strong.
Video Generation Goes Mainstream
A few years ago, a video of actor “Will Smith” eating pasta showed that AI-generated videos still had a long way to go before being convincing. Fast forward to today, and AI videos are now almost indistinguishable from real ones. All it takes is a phone app and an internet connection to create a video of anyone doing whatever you want them to do.
Already, numerous “AI vs. Real” challenges leave people guessing whether videos are filmed with cameras or created in a data center, and the results are concerning. Even seasoned journalists and researchers are fooled by these videos, and the implications of that on public trust are still uncertain as deepfakes become more widespread.
Not Enough Data on the Internet
For a while now, there has been a growing concern about AI growth: current development methods need ever-growing data sets to be trained on, and the AI’s thirst for data is growing faster than the internet itself. Current AI models have, for the most part, already gobbled up all the data on the web, and the need for new sources of data is growing.
One suggested source has been synthetic data, essentially using AI-generated data to train AI. However, a new method has recently been employed, especially for models beyond LLMs: live video. This approach has become more common in robotics and has already shown promising results in this area.
