The State of AI

The State of AI Decision-Making

March 12, 2020

AI is everywhere, and the use cases and new implementations are growing. Almost every day in the news, you see articles about new ways that AI is being implemented to solve problems and increase productivity for businesses. There’s no question that AI is rapidly changing and improving the way we do businesses, but there is still great hesitation as business leaders question the best way to implement such a large (and complex) technology.

To get a better understanding of successful AI implementations, we worked with The Harris Poll to gather data from mid-to-high-level executives about the planning process and organizational effort behind AI decisions. Here’s what we found: 

The time is now. 

Not surprisingly, 96% of respondents agree that the adoption of AI technology is critical for their company’s business success. However, 52% of respondents believe their company does not adopt AI technology as quickly as it should. Implementations are often long and complicated. In fact, if an AI technology can easily be implemented, it’s probably not well-integrated enough and the quality of results will suffer. If AI has the possibility of being a competitive advantage for your business, it’s important to get started on decisions now.

Involve the right teams. 

Our research found that decisions about AI technology most commonly lie with Technology/IT departments, who are also the primary users of these solutions. Neither of these results is particularly surprising. However, there is also a large use-case for AI in the contact center space to improve customer experience. Interestingly, according to the research, contact centers do not have much involvement in making AI decisions (28%), even though they are the third most frequently cited company area utilizing AI technology (64%). For AI implementations to be as successful as possible, it’s important to involve all affected teams in order to have a well-integrated and cohesive enrollment strategy. 

Who pays?

Although many different pricing models exist for AI implementations, and properly integrated solutions will actually save your business money in the end, one of the biggest questions regarding an AI decision will always be around the cost. It’s important to remember that AI is different than most technologies when it comes to implementation. First off, instead of one technology, AI is typically comprised of an array of technologies. Secondly, AI systems require tuning and training, which may require additional resources post-implementation. 

Simply put, pricing for AI is often more than a one-and-done fee. Self-funded AI projects are undoubtedly attractive to large enterprises. However, AI projects typically must be planned for in a budget cycle. Nine in ten mid-to-high level executives surveyed (90%) agree that self-funded AI projects are the most compelling to companies. Moreover, virtually the same proportion (91%) agree that AI projects for contact centers are particularly appealing because they can be self-funded.

It’s about more than just money. 

While soft benefits associated with AI technology appear to be well-recognized by mid-to-high level executives surveyed, most of them agree that generally, companies tend to underestimate those benefits. Soft benefits such as the potential for competitive advantage (66%) and ability to accelerate digital transformation (63%) are frequently cited as very important potential outcomes of AI technology, although falling in the middle of the pack of primary drivers determining whether to proceed with AI project implementation (44% and 43%, respectively). However, nearly three-quarters (72%) agree that companies tend to place a lower value on the soft benefits of AI technology. 

How will this affect an AI decision? Be sure to enroll decision-makers in the understanding that soft benefits, such as better customer experience, will result in more revenue and a higher competitive advantage in the end.

Want to see more?

See the full research report to learn more from the results of our survey.

AI Decision Making Report

Research

The State of AI Decision-Making

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