Intelligent Automation solutions with integrated Artificial Intelligence
Automating purely to reduce cost isn’t transformation. It’s optimization. That’s fine if you’re only interested in short-term wins, but leading enterprises — the ones who beat born-digital competitors, keep customers and delight shareholders — are looking beyond cost reduction and envisioning long-term success.
Led by distinguished analyst Sarah Burnett, the team at Everest Research Group set out to help enterprise executives and automation practitioners understand the difference between Intelligent Automation (IA) and Robotic Process Automation (RPA). This result is this recent report: “Intelligent Automation: Accelerating from Short-term Wins to Long-term Strategic Business Outcomes: A Guide to Undertaking Automation-led Business Transformation.”A complimentary licensed copy of the report is available for download here, or read on for key points and our responses:
1. How is Intelligent Automation different from traditional RPA?
Robotic process automation (RPA) follows rules to automate work that has no variation. When you log into your email account, you enter a username and password the same way every time. RPA is great for these types of repetitive tasks, which often string together to form a simple business process, like: log in, click box, move file from Point A to Point B, log out.
Scalability and ROI problems of process automation rapidly emerge, however, when variation is introduced. How often does your business process change? How much of the high-volume work that inundates your team involves unstructured data? People adapt, but software bots that only follow rules do not.
This is why AI-driven Intelligent Automation is superior to rules-driven RPA. Intelligent Automation integrates all the capabilities found in RPA, plus adds capabilities to process automation only possible through bots that learn and adapt to data in real time. According to the Everest Group report, these are some critical features of what they call “RPA 4.0” or Intelligent Automation:
- “Machine learning, computer vision, text analytics and NLP” process unstructured data, automate tasks that require judgment, and detect and adapt to constant change
- “Predictive and prescriptive analytics” help leaders plan resources and set achievable KPIs, plus help ensure optimal operational results
- “Self-managing, self-healing robots” handle exceptions and reduce bot management
“In order to build a sustainable competitive advantage through business process transformation by means of Artificial Intelligence (AI), it is essential for enterprises to adopt a long-term process automation strategy that aims to implement intelligent automation solutions that combine both RPA and AI capabilities.”