New MIT Sloan Management Review insights cover types of AI startups, using agentic AI tools for knowledge work, and why AI isn't boosting productivity.
As businesses adopt AI, they need to rethink how they make money. Understanding these four new business models is a place to start.
AI really can pay off. But leaders must take a systematic approach, understand how the technology works, and let their team leaders determine how it’s used.
A study found that trained LLMs can identify what customers want as well as expert market reach analysts, who are freed up to apply their expertise to high-leverage tasks.
Value creation is the true measure of successful AI implementation. It starts at proof of concept and considers AI’s impact on an industry, not just a company.
Stalled projects and workarounds cause chaos in too many organizations. Dynamic work design offers a way to address this through continuous, hands-on problem-solving.
In a $3.2 trillion industry, nobody can draw a complete picture of a patient’s life and health.
Transformative technologies like artificial intelligence succeed when societies make parallel social investments to ensure gains are distributed equitably, MIT Sloan researchers find.
Enterprises looking to make the most of agentic AI will have to rethink how work gets done and how teams are organized, without forgetting the human workers who set their companies apart.
Open-source and open-weight AI models perform well and cost less — but users opt for closed models 80% of the time, according to new research.
