Data, AI, & Machine Learning

Amit Shah, president of 1-800-Flowers, explains why lifelong learners are the best technical talent.

Hiring with AI, creating learning organizations, and cultivating a high-purpose culture to support leadership at all levels.

Employers can vet people more ethically and accurately with explainable AI.

Will Grannis of Google Cloud explains the organization’s collaborative approach to AI and machine learning innovation.

This Strategy Guide covers identifying AI use cases — and how to know when AI isn’t the best answer.

Testing can guide decisions such as who needs to work in an office and what work hours are optimal.

TCS and Halliburton Landmark executives discuss digital transformation in the oil and gas industry.

Preparing workers for a digital future, targeted learning, and the emotions of returning to the office.

Companies are taking different approaches to preparing their workers for the digital future.

Anticipating and withstanding cyberattacks — cyber resilience — must become a companywide concern.

Lyft’s Craig Martell talks education, eliminating bias, and cross-functional collaboration on machine learning projects.

Data science obstacles, concerns about data executive roles, and the virtual hiring process.

Only a third of data executives feel that their role is “successful and established.”

Organizations that struggle to gain payback from data science efforts can recognize and overcome five common obstacles.

Making diversity and inclusion real, clarifying pandemic data, and how Amazon will innovate post-Bezos.

The authors describe three key challenges leaders face in communicating pandemic data and how to address them.

Planning for the post-pandemic workplace, managing hybrid teams, and optimizing your organization for AI.

To deliver on the promise of AI, leaders must focus on improving their organization’s culture and decision-making capabilities.

This webinar outlines how human-AI collaboration leads to measurable results for organizations.

Workforce ecosystems, machine discovery, human-machine collaboration, and the inventor of Wikipedia.