The 451 Take
Comparing current and future adoption rates, compliance
Finally, the survey data suggests that algorithmic trading is a more niche use case of interest to those in investment banks and brokerages. Other use cases in the survey include customer service, wealth management, loan/credit card approval, marketing, product recommendations, process automation
Since retailers live and die by their ability to convert potential customers into repeat buyers, it's not surprising that retailers are focused on using machine learning to improve customer engagement. In fact, according to the survey, customer engagement was the most popular use case among respondents, with 45% currently deploying machine learning as part of next-generation customer engagement tools. Retailers have access to a wealth of
The survey results also show that demand prediction and supply chain enhancement are areas getting a boost from the use of machine learning, where AI is working alongside humans to spot patterns in vast, disparate datasets. Payment processing is important for ensuring customer satisfaction, so it's not surprising that it is one of the retail-focused use cases with the largest expected net growth, especially given the fragmentation of the US payments market and the improvements machine learning offers.
Other more transformative use cases such as product design and creation seem to be more than a few years out, based on the survey results. In addition to those discussed above, other use cases cited include post-sales customer service, digital/data security, physical security
It should come as no surprise that practitioners in the healthcare space are excited to apply machine learning at the point of care. According to the survey results, 46% of respondents are employing machine learning in their patient monitoring systems, the highest of any of the surveyed use cases. Another related use case – clinician workflow optimization – also polls very well. By applying the technology to the growing volume of data generated by IoT medical devices and other lifestyle data, healthcare providers hope that intelligent patient monitoring and clinician workflow optimization tools will allow doctors to focus on the higher-level decision-making that improves patient outcomes.
Quality assurance and product design and creation are two future use cases that seem to excite manufacturers. Better optimized and automated QA processes not only reduce costs but also enhance product quality. Automated product design is a headier challenge that could allow users to gain
Assembly line optimization is one of the manufacturing use cases with the largest net gain, suggesting that respondents are interested in deploying machine learning to bolster this area in the future. Other use cases surveyed include digital/data security, physical security, and supply chain logistics and management.
Nick Patience is 451 Research’s lead analyst for AI and machine learning, an area he has been researching since 2001. He is part of the company’s Data, AI & Analytics research channel but also works across the entire research team to uncover and understand use cases for machine learning. Nick is also a member of 451 Research’s Center of Excellence for Quantum Technologies.
Jeremy Korn is a Senior Research Associate at 451 Research. He graduated from Brown University with a BA in Biology and East Asian Studies and received
Keith Dawson is a principal analyst in 451 Research's Customer Experience & Commerce practice, primarily covering marketing technology. Keith has been covering the intersection of communications and enterprise software for 25 years, mainly looking at how to influence and optimize the customer experience.