AI & Machine Learning
When Jobs Become Commodities
It pays to ask yourself whether your job is common and repetitive enough to be done by a machine.
It pays to ask yourself whether your job is common and repetitive enough to be done by a machine.
A new phase of technology-enhanced work is upon us.
The value of enterprise-level AI depends on what an organization’s people do with it.
In the first half of 2017, these MIT SMR articles attracted the most readers.
A panel at the 2017 MIT CIO Symposium discusses how artificial intelligence will transform how we work.
Managers already struggle to put data to intelligent use; AI may add to their difficulty.
The challenges of leading companies through the AI revolution were examined in a recent symposium.
The novelty of self-driving cars overshadows the real promise of AI: augmentation of human skills.
How soon will smart machines start looking out for our health?
The synergism of Big Data and artificial intelligence holds amazing promise for business.
Automation brings with it questions about what to do about worker displacement.
Instead of eliminating human workers, AI may create new jobs requiring updated skills and training.
Businesses should understand that in the long run, the promise of AI is self-limiting.
The best use of digital technology is assisting human workers to maximize innate capabilities.
The challenge we face today is not a “world without work” but a world with rapidly changing work.
How AI affects organizations’ use of and relationship to time — in reacting, managing, and learning — may be a tough adjustment.
Managers should start incorporating AI into business processes now.
A new MIT SMR and BCG initiative investigates the challenges and opportunities AI offers business.
AI is expected to be the single most disruptive new capability for companies in the next decade.
Subscription e-commerce uses AI to offer personalized, low cost, convenient products. It’s working.