Cognitive technologies are transforming everything from customer experience to product development, and augmenting or replacing human activity in everything from manufacturing to operations to human resources. They are also beginning to reshape finance – emphasis on the “beginning.”
In the Q3 2017 CFO Signals survey, only 42% of responding CFOs said their finance team is knowledgeable about emerging technologies, including cognitive. Moreover, only about one-third of CFOs in the same survey said they have moved beyond the pilot stage with these technologies to transform their finance function.
Why the hesitation? Could some of it be related to the myths around cognitive that seem to be as pervasive as the technologies themselves?
When ranking the benefits of AI, cutting jobs through automation is at the bottom of the list for our respondents. Enhancing products or creating new ones and making better decisions rank higher
To find out, Deloitte’s recent State of Cognitive Survey asked 250 “cognitive-aware” US executives from large companies about the current state of cognitive technology within organizations. These managers were knowledgeable about artificial intelligence (AI)/cognitive technologies and informed about what their companies were doing with the technologies.
They also were well-versed in the misconceptions about the technologies – misconceptions that may explain why finance may be holding back. In this issue of CFO Insights, we discuss five common myths that cognitive-aware executives have dispelled.
The bottom line? Cognitive technologies can be deployed now to address a wide a range of finance challenges.
Myth #1: The main use of cognitive technologies is automating work that people do
It is rare to find a story in the media about AI that doesn’t speculate about how the technology is destined to put lots of people out of work. (See Myth #2.) This is because it is widely assumed that AI is all about automating the work that people do.
But this is hardly the full story. As our prior research has shown, and the survey has validated, there are significant uses for AI that do not involve substituting machine labor for human labor.
Our analysis of hundreds of AI applications in every industry has revealed that these applications tend to fall into three categories: product, process, and insight. And these applications don’t necessarily involve automating work that people do.
Product applications, for instance, embed cognitive technologies into products or services to help provide a better experience for the end user, whether by enabling “intelligent” behavior, a more natural interface (such as natural language text or voice), or by automating some of the steps a user normally performs.
Process applications use cognitive technology to enhance, scale, or automate business processes. This might entail automating work that people were doing; but it also might involve doing new work that wasn’t practical to do without AI.
And insight applications use AI technology, such as machine learning and computer vision, to analyze data in order to reveal patterns, make predictions, and guide more effective actions. Again, in some cases this can be used to automate human work. But it is also used to do work that no human could have done previously because the analysis was impractical without the use of AI.
Survey respondents clearly believe that AI is important for more than automation. While 93% said its use was important or very important in their internal business processes, 88% ranked it of similar importance to the products and services they sell.
And, when ranking the benefits of AI, cutting jobs through automation is at the bottom of the list for our respondents. Enhancing products or creating new ones and making better decisions rank higher. The research shows that AI is about far more than automating work that people do.
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