Analytics & Business Intelligence
Why Smart Companies Are Giving Customers More Data
To launch successful products that delight customers, companies need a new approach to data analytics.
To launch successful products that delight customers, companies need a new approach to data analytics.
How to boost innovation capacity and institutional pride, and addressing tech inequity and the ethics of automation.
The increasing adoption of AI and robots has implications for jobs, biases, and data privacy.
New AI applications have immense potential to revolutionize communication and deepen human relationships.
The most effective human capital investment initiatives have a common core: opportunity.
Swarm systems draw input from individuals and use algorithms to optimize system performance in real time.
Collisions between innovators and existing players are forcing executives to rethink their strategy.
Business leaders must rethink data management to succeed with machine learning.
How companies assign responsibility for analytics is a crucial factor in exceeding business goals.
IBM’s Mark Foster discusses what makes digital transformations succeed — and why it takes humanity.
Our experts reveal where leaders should focus their efforts in 2020 and beyond.
Companies implementing AI must protect customers’ autonomy, privacy, and individuality.
Leadership behaviors that build trust, purpose, and energy bolster collaboration and engagement.
MIT SMR authors David Bray and R “Ray” Wang discuss how people-centered design principles can serve as a framework in AI implementation.
Companies already use data to make marketing decisions. Will deep learning enable a leap forward?
A webinar summarizing lessons learned in AI implementation from the 2019 Winning With AI Report.
No matter how compelling it seems, data alone won’t win people over unless infused with a story.
Just because a company can build an AI-infused product doesn’t mean it should.
Tom Davenport, Alex Breshears, and Abbie Lundberg discuss the specific challenges enterprises face in machine learning, and how they can create an end-to-end, factory-like capability.
The true underperformers in this digital disruption era are not measures but their managers.