Data & Data Culture

Lufthansa launched an effective program to turn all its leaders into data leaders and propel its digital transformation.

The nonprofit is delivering technology and services to help its staff build AI applications efficiently and safely.

Smart organizations need smarter KPIs. This report outlines how leaders can create and capture value from smart KPIs.

Generative AI tools suit some decision-making situations, but not all. Here’s how to pick the best approach.

Three new surveys of data executives have identified five trends they’ll be paying attention to in 2024.

Is your AI project using the right data, and is it set up to succeed? Ask the right questions to head off failure.

On the Me, Myself, and AI podcast, Chevron’s Ellen Nielsen explains how AI supports workers and operational efficiency.

Employees in connector roles can bridge the gaps between departments that often thwart data science project success.

Leveraging data assets for significant financial returns requires company-wide effort and education.

A data monetization matrix can help leaders assess opportunities and approaches for converting data into revenue.

FedML technology could help smaller companies train their machine learning models on larger, decentralized data sets.

On the Me, Myself, and AI podcast, learn how social scientists help facilitate human-machine collaboration at Intel.

Many finance offices aren’t benefiting from advanced analytics. A new framework can help CFOs assess their data skills.

The journey to be more client-centric has brought a focus on artificial intelligence and data at Northwestern Mutual.

Reveal data piece by piece instead of all at once to give it narrative structure — and meaning.

Based on their research, the authors share four key ways companies can advance their strategic data-sharing initiatives.

The human side of data continues to challenge companies.

Artificial intelligence is quietly improving the management of data, including its quality and security.

This issue of MIT SMR focuses on creating and managing successful, engaged teams in a pandemic-changed world.

New data-efficient AI techniques can help when developers lack sufficient volumes of labeled training data.