[3] Intelligent automation applies the assembly line concept of breaking tasks into repetitive steps to improve business processes.
Common real-world applications include self-driving cars, self-checkouts at grocery stores, smart home assistants, and appliances.
[6] Businesses can apply data and machine learning to build predictive analytics that react to consumer behavior changes, or to implement RPA to improve manufacturing floor operations.
Data provided by hospital systems’ electronic health records can be processed to identify and educate patients, and schedule vaccinations.
42% of CTOs see “shortage of talent” as the main obstacle to implementing Intelligent Automation in their business, while 36% of CEOs see ‘upskilling and professional development of existing workforce’ as the most significant adoption barrier.