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Contrary to the ChatGPT boom, artificial intelligence (AI) and machine learning (ML) technologies have been around for quite some time but only recently gained momentum outside of the tech sectors. 

We’re seeing the topic of AI, in particular, everywhere these days: the news, social media, executive board rooms, and fiscal budgets. Leadership knows adopting new technologies is critical to staying relevant and competitive in the market today and five years from now, but this motive leads to a skewed perception or misuse of the technology itself. In fact, nearly a third of IT executives (32%) say their company leadership sees AI as a marketing tool for enhancing brand perception instead of technology that can drive business outcomes and product strategy. Yes, AI deployment is widespread, but 72% of those IT executives say their leaders don’t fully understand the technical capabilities available, so it makes sense another study found only a slim 12% of companies have a mature AI strategy in place. 

Beyond a general misunderstanding of the tech’s capabilities, the state of AI is facing a number of obstacles. Research reveals company expectations are too high, organizations lack the right tools to propel initiatives beyond the experimentation phase, business and product application falls on the shoulders of the wrong internal team, and ultimately, leadership isn’t prioritizing AI/ML with the urgency needed to be successful.

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