AI & Machine Learning
How to Build Good AI Solutions When Data Is Scarce
New data-efficient AI techniques can help when developers lack sufficient volumes of labeled training data.
New data-efficient AI techniques can help when developers lack sufficient volumes of labeled training data.
Embedding data, analytics, and artificial intelligence into products has been a game changer for businesses.
Most companies that are using AI are deploying it for augmentation, not large-scale automation.
This issue of MIT SMR focuses on customer relationships and their connection to innovation and value.
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.
Businesses must use data and analytics to better anticipate consumer needs and humanize digital interactions.
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.
Fostering tech-mediated collaboration, dignity in employee data use, and in-house social intrapreneurship.
DBS Bank’s CEO exemplifies how a willingness to experiment and even fail can help advance new technologies like AI.
New value creation with strategic data assets, in-store shopping to build customer loyalty, and habits to enable enduring culture change.
To monetize data, companies must first transform it so it can be reused and recombined to create new value.
Six strategies can help guide data science teams toward greater success in cross-unit projects.
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.
Companies that emphasize collaboration between AI and human workers are best positioned for success.
Data-driven decision-making anchors on available data, which can lead decision makers to focus on the wrong question.
Leaders need to examine their core beliefs if they want to prosper in a COVID-19 world.