Many leaders are excited about the promise of AI coding tools that can make it easier for novices to write code and, seemingly, make experienced coders less essential. Yet these tools make experience more—not less—important,

I used an AI tool to predict my long term care needs, including if and when I'll need help bathing and eating, and how much that care will cost.

Microsoft Copilot, Google Gemini, Grammarly, Canva — the list of tools teachers can use to get hours back in the day is growing.

Stanford faculty across disciplines are integrating AI into their research, balancing its potential to accelerate analysis against ethical concerns and interpretive limitations.

In 2026 (and beyond) the best benchmark for large language models won’t be MMLU or AgentBench or GAIA. It will be trust —something AI will have to rebuild before it can be broadly useful and valuable to both consumers and businesses.

It is undeniable that AI tools have shifted from cautious experimentation to widespread adoption, and clinicians are actively seeking these solutions. There will be more progress in 2026, but it won’t be linear. Here are three predictions as we go through the inevitable ups and downs and realize the promise of a truly disruptive technology.

"The business sense uses of AI are ones that we think of as enhancing productivity for the human beings that are involved in a particular task," said Oxman.

Discover the top AI tools that help beginners learn automation through simple workflows, visual builders, and clear explanations without coding.

Now available in all English-speaking markets, LinkedIn Hiring Pro uses AI to sort through job applicants for the best potential candidates. Based on early user research, LinkedIn found this feature saved small businesses more than six hours each week of their recruitment processes.

We’ve seen the first AI-generated commercials, songs and even social media influencers outside of healthcare. Will pharma be next?