This column series looks at the biggest data and analytics challenges facing modern companies and dives deep into successful use cases that can help other organizations accelerate their AI progress.
After deploying hundreds of AI solutions, financial services company USAA is breaking new ground with generative AI.
This Canadian bank has become known for developing AI tools that are both innovative and responsible.
The nonprofit is delivering technology and services to help its staff build AI applications efficiently and safely.
Three new surveys of data executives have identified five trends they’ll be paying attention to in 2024.
Unilever examines its AI projects with a risk analysis process that looks specifically for ethical trouble points.
Even with its deep AI experience, Mastercard is feeling its way toward how it uses generative AI.
New AI tools can produce text, audio, and images. What does that mean for creative professionals? Two experts weigh in.
The journey to be more client-centric has brought a focus on artificial intelligence and data at Northwestern Mutual.
The human side of data continues to challenge companies.
Embedding data, analytics, and artificial intelligence into products has been a game changer for businesses.
Disciplined experimentation is bringing the use of artificial intelligence into clinical health care at Mayo Clinic.
Plenty of organizations dabble with AI, but Mastercard’s capabilities — and confidence — set it apart.
Health care organizations are seeing significant savings using AI in administrative systems.
Respondents to recent global surveys say their organizations are capturing substantial value from AI.
Scotiabank’s focus on AI projects likely to deliver value in a short time frame is paying off.
DBS Bank’s CEO exemplifies how a willingness to experiment and even fail can help advance new technologies like AI.
Many organizations have challenges with deploying AI. Wealth management is a clear exception.
Dramatic changes within the life sciences industry present unique opportunities to use AI.
Only a third of data executives feel that their role is “successful and established.”
