Data, AI, & Machine Learning

Six strategies can help guide data science teams toward greater success in cross-unit projects.

The data science management process, job moves for pay equity, and political concerns in M&As.

In this webinar, speakers discuss the benefits and pitfalls of monitoring in-person and remote workers.

Moderna’s chief data and AI officer explains how AI helped the pharma company develop a COVID-19 vaccine in record time.

This Strategy Guide explores implementing AI as part of a larger digital transformation strategy.

Organizations should manage data science with an appropriate structure and enterprisewide process.

Many organizations have challenges with deploying AI. Wealth management is a clear exception.

Monolithic, highly interdependent organizations can become modular ones by embracing microservices.

There’s power in integrating subscription-based software, platform marketplaces, and machine learning.

Elizabeth Renieris of the Notre Dame-IBM Technology Ethics Lab discusses how businesses can responsibly govern AI projects.

This Strategy Guide offers expert advice on gauging your organization’s technical readiness for AI.

PepsiCo’s Colin Lenaghan discusses AI’s role in the company’s pricing strategy and ongoing digital transformation.

Practical strategies for hybrid work, linking good intentions to intentional actions, and Daniel Kahneman on “noise.”

A dedicated team can help maximize the utility — and competitive advantage — of automation systems.

Home Depot’s Huiming Qu discusses how the home improvement retailer leverages AI to improve the customer experience.

Identifying the potential public harm of new AI tools should be part of prelaunch due diligence.

The Me, Myself, and AI podcast delves into how automotive supplier Cooper Standard uses open innovation to leverage AI.

Bart De Langhe and Stefano Puntoni explain how organizations can make better decisions with data.

Adapting roles amid organizational change, “invisible” leadership transitions, and new digital olfaction technologies.

Dramatic changes within the life sciences industry present unique opportunities to use AI.