Technology Implementation
Designing AI Systems With Human-Machine Teams
Many organizations don’t understand the value of teaming machine capabilities with human abilities.
Many organizations don’t understand the value of teaming machine capabilities with human abilities.
Creating a culture of small teams of high-performance engineers will maximize productivity.
Effective teams depend on mutually reinforcing functional and cultural change processes.
Tinder’s entrance into the dating app industry was a literal game changer.
The first trillion-dollar companies are platform-based. Challenges and opportunities lie ahead.
Solving complex problems with crowdsourcing means tailoring the crowd to the problem’s scope.
Recruiting women directors can pave the way for long-term support of innovation and creativity.
Companies looking to become market leaders face two challenges: getting ahead — and staying there.
There are specific ways for women to be more successful in pitch situations.
AI and automation are changing labor markets worldwide, but developing nations will be hit hardest.
Six risks that business leaders can begin to strategize around now.
Companies implementing AI must protect customers’ autonomy, privacy, and individuality.
New research offers companies a framework for managing successful country portfolios.
Redesigning jobs should be seen as a process that enables work to be redefined to create new value.
Companies already use data to make marketing decisions. Will deep learning enable a leap forward?
Facial recognition tech can identify and analyze key emotional states — but must be used with care.
The most effective use of AI: Symbiotic systems enabling humans and AI to work to their strengths.
When employees represent the views of customers, management needs to have their backs.
Small-scale piracy sometimes offers surprising benefits for IP rights holders.
Why do some business ecosystems dominate their markets over time while others fail?