AI & Machine Learning
#MITSMRChat: Implementing AI
MIT SMR and BCG host a Twitter chat focused on the corporate adoption of AI.
MIT SMR and BCG host a Twitter chat focused on the corporate adoption of AI.
As sports become ever more analytical, can there be such a thing as too much data?
How cities deal with AI-related changes will determine which ones will thrive in the future.
The time when companies could simply ask the world to trust AI-powered products is long gone.
Top-down management is good for building operational excellence but not rapid innovation.
The most effective responses to digital disruption don’t make use of technology at all.
A successful pitch for AI must overcome economic, technical, political, and cultural hurdles.
A value chain lens reveals a growing cybercrime ecosystem and new strategies for combating it.
Instead of living in silos, technology must be integrated into all aspects of business.
A webinar describing what companies need to effectively use AI and automation for operations.
To adopt intelligent technologies, companies need to develop both the right tools and human capital.
Cognitive speed bumps in AI design can prompt users to engage in reflective thought.
Five capabilities and four practices help companies generate business value from AI applications.
China is taking the lead on developing new technology focused on mobility.
Consumers’ concerns about data privacy are offset by a desire for personalized service.
Digitally maturing companies are not only innovating more, they’re innovating differently.
Chatbots aren’t replacing human customer service agents — they’re making them more efficient.
Smart machines can help pick crops and reduce traffic — but what’s their impact on privacy?
Utilities field workers are on the front lines when there’s a crisis. How can tech empower them?
Will Chinese technology companies gain a first-mover advantage in the race for 5G?