6 Tips for Better Artificial Intelligence Implementations

Most organizations fail at artificial intelligence (AI) implementations in the workplace or elsewhere because they lack the skills, staff and resources, as well as, potentially unrealistic expectations, according to an IDC survey. IDC found more than 60% of organizations reported changes in their business model in association with their AI adoption, and nearly half have a formalized framework to encourage considerations of ethical use, potential bias risks and trust implications. Further, a quarter of organizations have established a senior management position to make sure they get things right. "AI can create better outcomes to highly variable problems by constantly changing the rules," said Mike Orr, COO of Grapevine6. "The challenge for enterprises is, 'How do we know it's working?' This is an important question when even a small failure can mean something as serious as introducing institutional bias or regulatory violations."