About Michael

1996 - 2004

Early Scholastic & Athletic accomplishments set the foundation for his leadership, academic achievement, and bias for action

2005 - 2009

During his PhD Michael starts experimenting with little known GPU computing for matrix operations and parallel processing for efficiently training computationally intensive prediction machines for consumer demand problems,

2010 -2013

As a professor at NYU Stern Michael authored key research on ML/AI methods and computational approaches for marketing measurement and optimization problems

2013 - 2021

Michael leads the creation and go to market releases of three successful commercial cloud software products for marketing measurement and optimization

2022

Michael leads the launch of AIOS a next generation agentic AI cloud software for marketing campaign creation, measurement, and personalization

Meet Michael

Visionary AI strategist, Michael Cohen, has pioneered explainable machine learning (ML) solutions for consumer data-driven marketing, setting a new standard in predictive intelligence and data analytics.

With extensive experience in developing, launching, and scaling data, prediction, and AI products for marketing operations, automated decision-making, and privacy-centric intelligence, Michael has transformed the marketing technology ecosystems with systems that drive true business growth. His leadership has shaped innovation roadmaps that prioritize explainability and actionable insights, empowering organizations to optimize marketing campaigns, enhance customer experience, and ensure regulatory compliance.

Michael has launched several enterprise cloud software businesses with novel predictive intelligence platforms, most recently
AIOS, which delivers a high fidelity view of the customer journey, empowering marketing teams with powerful creative insights and outputs, precision analytics, and seamless targeted cross-channel optimization.

Known for building and using prediction machines to solve complex issues—from user privacy to data lag elimination, Michael’s approach to machine intelligence reduces labor costs, boosts efficiency, and eliminates data silos, setting the bar for return to MOIC in AI in the marketing and advertising landscape.