Companies that use Intelligent Automation and RPA to enhance customer-facing experiences will find themselves with a definitive competitive advantage.
Robotic Process Automation (RPA) enables companies to automate routine business tasks, thus limiting overhead, amplifying productivity and freeing employees to concentrate on complex or unique business needs. This functionality is even more impactful when paired with Intelligent Automation (IA), when Artificial Intelligence (AI) is used to partially or fully automate the creation of new RPAs.
Advanced IA functionality can be found in various automation solutions such as 1RPA, which is able to independently structure unstructured data or design a new automation just by observing humans execute a task. The implications of IA-fueled RPA are clear in regards to ROI within an enterprise, however the biggest benefits may be felt by customers.
More Automated Services
Just as physical and transactional automation amplifies output, automating the creation of new automations greatly increases the number of bots that can be built in an accelerated timeframe. IA can lead to far more user-facing RPAs than could have been possible when relying on human creation alone.
For example, IA might be used by an online printer ink retailer to build an RPA that emails deals for a new ink cartridge to customers based on a data-driven prediction of when they would need a new supply. This automation could be crafted and edited with IA far more easily than in a previous technological era and therefore benefit customers with convenience and savings in a timelier manner.
However, IA creating automations also has a secondary benefit in the form of improved service delivered by human workers who are no longer bogged down with routine, high-volume tasks. Automations can handle rote processes instead, and bots can be created more quickly.
Not only does IA lead to more automations, but it ensures that the ones it creates are optimized for maximum impact. Like any intelligent technology, IA can observe and quantifiably measure the efficacy of any particular automation (e.g., an automation involving auto-generated emails could measure the open and engagement rates) and report back to human colleagues, or — dependent on the system’s level of autonomy — independently tweak the automation in pursuit of better metrics (e.g., change the timing of the email sent or the content of the messages itself).
An IA system could even launch various flavors of an automation as part of an A/B test to determine the best version, and the “lessons” learned in these tests could then be applied to new RPAs in the future. When human intermediation is removed from the automation process, it also removes any inherent human bias, which allows machines to make decisions based on data and guaranteeing automations which will make the most impact.
IA can transform how enterprises do business on the backend in order to increase efficiency and productivity. However, companies that use this technology to also enhance the customer experience will be able to generate a definitive competitive advantage.