Leaders must deliver rapid AI innovation while handling many related people management challenges, ethical dilemmas, and security risks. One key is developing strong AI leadership skills while recognizing that human judgment remains essential. Get expert advice to help your team succeed with AI.
Peer coaching plays a foundational role in developing human skills that technology cannot replace.
The skills challenge requires shifting initiatives and resources to where they are needed most.
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.
A new article series explores opportunities to reimagine the future of workplace learning.
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.
Companies that emphasize collaboration between AI and human workers are best positioned for success.
New technologies can help solve critical global problems in energy, medicine, and urban planning.
To gain business agility, leaders must deconstruct jobs into tasks and deploy workers based on their skills.
In this webinar, Jeffrey D. Camm and Thomas H. Davenport explain how the COVID-19 pandemic has impacted the practice of data analytics.
There are differences between what constitutes a successful early AI pilot and success in other types of IT ventures.
Revolutionary recommendation engines, data access as a leadership priority, and the essentials of successful corporate social justice efforts.
Transforming a company into a truly data-driven business involves fundamental organizational changes.
Data accessibility must be managed from the start of AI projects in order to be implemented in production.
