Technology Implementation
AI in Business: Myths, Reality and How to Reap Value
Getting business value from AI means separating myths from facts.
Getting business value from AI means separating myths from facts.
Retailers can avoid displacement and connect with customers by focusing on digital experience.
Done right, automation can be a win for everyone — even workers.
Banks need a clear AI strategy to get digital transformation right.
Makers of AI applications should stop overpromising, be transparent, and consider certification.
Retail companies that neglect machine learning do so at their peril.
Digital customer service platforms offer better service when they use customer-centric language.
Properly orchestrated, cybersecurity can reduce costs and increase revenue.
As KPI dashboards evolve, they’re transforming how executives manage themselves.
Balancing discovery with execution is the key to successful digital innovation.
Smart contracts using blockchain enable faster, more secure digital agreements.
Research shows greater KPI transparency and clearer alignment are key to overall KPI effectiveness.
With a new scrutiny around technology user data and privacy, we must not forget about the potential dangers of the technology itself.
The 2018 Artificial Intelligence Report by MIT SMR shows early leaders pushing forward with an eye toward scale.
A webinar from MIT SMR discusses how cloud technology promises to upend how people work and learn.
Consider three key questions when determining how to make blockchain a useful part of your business strategy.
Viewing technology as a set of solutions misses opportunities to innovate in bigger, bolder ways.
Automation will affect jobs in four ways. The path jobs take depends on what kind of value they provide — and how.
Cybersecurity can no longer be an add-on — companies must invest in future-proofing their systems.
The future of AI looks much like the present, with machines helping humans to do their jobs better, not replacing them.