The vast potential AI holds for businesses worldwide is of little doubt. But flawed strategy, poor approaches to process change, expertise shortfalls and a general lack of technical understanding prevent many enterprises from deriving value from artificial intelligence.

Among the 90 percent of companies that have invested in AI fewer than two out of five say they’ve made any business gains, according to Winning With AI: Pioneers Combine Strategy, Organizational Behavior and Technology,” a survey of 2,500 business executives conducted by MIT Sloan Management Review and Boston Consulting Group (BCG). AI includes associated technologies such as machine learning (ML) and natural language processing (NLP), both of which aim to ape human thought.

And while implementing AI does present technical hurdles, as has reported, experts from BCG and Gartner discuss five pitfalls to deploying AI in the enterprise, along with solutions for success.

1. IT-led AI leads to wasted opportunity

Many businesses let IT shepherd AI development and deployment, treating it much the same way they might the deployment of ERP systems, says Shervin Khodabandeh, a BCG partner who co-leads the firm’s GAMMA AI practice. This is a significant misstep because general AI solutions won’t help the business, Khodabandeh says.