Artificial Intelligence is revolutionizing industries by automating processes, analyzing vast data sets, and delivering valuable insights. Generative AI, a cutting-edge branch of AI, excels at creating original content—ranging from text and images to music and software code—by identifying patterns in data. As it continues to evolve, generative AI is accelerating innovation and boosting efficiency in sectors such as marketing, healthcare, finance, and entertainment, reshaping the future of business and work.
A steady rise in the application of exponential technologies, primarily artificial intelligence and machine learning, has necessitated a deep understanding of and broad capabilities for driving business growth for business leaders and managers in an evolving global economy. The AI and ML: Leading Business Growth program is a unique opportunity to explore and excel at a global level, with a no-code approach, and the knowledge, tools and best practices needed to drive strategic business growth powered by AI and ML.
El mundo empresarial se enfrenta a nuevos retos y se transforma con la aparición de cada nueva tecnología, pero hay tres objetivos que son invariables en el tiempo para todas las organizaciones. Estos son:
We are in a world where the new technologies of Cloud, IoT, AI/Machine Learning, and Cloud Data-Stacks are re-architecting how organizations operate. DevOps and DataOps driven organizations move thousands of times faster than others.
To master this “Tsunami” of data we need to leverage new tools and new data analysis techniques. We need to master the new Cloud datastores where we can query petabytes of data in seconds.
We need to understand how to leverage the new data-in-motion pipelines to make business decisions in seconds rather than days or weeks.
La implementación eficaz de la tecnología requiere de una cuidadosa planificación, evaluación y gestión para garantizar que se aplique lo que más beneficie a tu organización, en función del personal, producto, servicio y objetivos.
Champion the current complexities of technology implementation for your organization.

Tommi Jaakkola is a Thomas Siebel Professor of Electrical Engineering and Computer Science and the Institute for Data, Systems, and Society. He is also a member of the Computer Science and Artificial Intelligence Laboratory. His work pertains to inferential, algorithmic and estimation questions in machine learning, including large scale probabilistic distributed inference, deep learning, and causal inference.

Dr. Stuart E. Madnick is the John Norris Maguire (1960) Professor of Information Technology, Emeritus in the MIT Sloan School of Management, as well as a Professor of Engineering Systems in the MIT School of Engineering. He is also Founding Director of Cybersecurity—MIT Sloan’s consortium for improving critical infrastructure cybersecurity—and the Co-Head of the MIT Information Quality (MITIQ) Program. He is the author or co-author of more than 400 publications, including Computer Security, one of the first books ever published on the topic of cybersecurity.