What does the future of intelligent automation look like? Organizations today are already investing much time and effort into what we call systems that "do". But this is the starting point for what we see as the evolution towards systems that "think" and systems that "learn".
- Systems that "Do": Allow non-programmers to automate rules-based, multi-application activities. Usage areas include application processing, claims adjudication, accounts payable and receivable, invoice reconciliation, data entry/extraction and report generation.
- Systems that "Think": Able to make decisions autonomously using logic when variances occur in the processes they execute. Effective with less defined processes and unstructured data. Usage areas include service desk incident resolution, complaint management and resolution, network security management, and customer service.
- Systems that "Learn": Able to analyze vast amounts of unstructured input and execute non-rules based processes. Can apply different rules in different situations. Usage areas include prescriptive pricing engines, virtual service agents and retail engagement systems.
We believe that systems that learn will ultimately evolve into systems that "adapt". They will use what they learn to improve their processes according to their environment, defend themselves from security threats, and interact more seamlessly with other systems and with people.