Data, AI, & Machine Learning

A webinar summarizing lessons learned in AI implementation from the 2019 Winning With AI Report.

Avoiding the technology trap, AI needs a human touch, and good storytelling with data.

New research sheds light on key changes companies must make to become innovation leaders.

History shows we should focus more on policy than technology challenges when confronting automation.

No matter how compelling it seems, data alone won’t win people over unless infused with a story.

Preparing for CEO turnover, demystifying AI, and operating in the age of online outrage.

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.

A human-AI workforce, today’s tech bubble, dealing with deregulation, a misplaced focus on metrics.

The true underperformers in this digital disruption era are not measures but their managers.

The most effective use of AI: Symbiotic systems enabling humans and AI to work to their strengths.

How companies are making AI pay; tread cautiously in a transparent world; CIOs step up their game.

Gain actionable insights from peers and AI experts during a live Twitter chat.

Our flawed approach to the AI race, corporate boards get less cozy, and not much love for Libra.

Why do workable analytics-based strategies always seem to fail when the playoffs start?

We’ve unlocked our site and curated reading lists to help you solve your key business problems.

Re-skilling done right, telling a good data story, and three big points on disrupting yourself.

To solve the issue of advanced analytics talent concentration, companies need to think creatively.

This case study follows Mondelez International’s project to implement RPA as part of its AI journey.

A classic bar, line, or pie chart is often the best choice for communicating information.