We all know that there are troves of data that exist online about us and our browsing, clicking, and spending habits. However, given all that information and the people that spend their lives on the internet, how do those who tailor the ads we see parse that information? As with many things these days, it's useful to have machines to help. RJ Talyor is the CEO and founder of Pattern89, an Indianapolis-based marketing firm using the power of artificial intelligence (AI) to help advertisers figure out what works and what doesn't when it comes to the ads we see everyday. I spoke with him about how AI is helping marketers figure out not only who to target, but what elements to include in those ads.

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."

Marketers who look for artificial intelligence to provide fresh insights don't always get what they want. Insights are not always easy to categorize, let alone evaluate and implement. The result: patterns that may be intriguing but unprofitable to pursue. I recently asked R. J. Talyor, Founder and CEO of Pattern89, an AI firm that helps marketers predict their campaigns' performance, for his thoughts. Paul Talbot: Since marketers began to use AI, what unintended consequences of significance have emerged?