5 tips on how to pick the right AI use cases

It's commonly known that AI feeds on data, yet the importance of data is often underestimated. "The scope and scale of the data problem in AI is far larger than most people realize," explained Jen Snell, vice president of Verint, a chatbot development company. "So many organizations run into problems with their projects due to data -- from data quality to managing and wrangling data for meaningful insights to labeling and model building," she said. "In the beginning, it seems easy, but as you look to grow at scale, change models, manage and ensure control over the system, it gets tricky." Snell shared a painful statistic: While 59% of executives believe AI could improve their use of big data, 85% of big data or AI projects fail.