Hyperautomation is the sophisticated integration and coordination of multiple automation technologies to optimize complex business processes and augment human capabilities for enhanced productivity. It spans intelligently automating tasks and workflows by weaving together AI, RPA software, IoT systems and analytics.

Traditionally businesses automated routine tasks ranging from email classification to data entry via basic robotic process automation (RPA) scripts mimicking keyboard and mouse actions. Yet with AI advancements like computer vision, speech recognition and natural language processing, automation expanded to more complex work involving analysis, communication and judgment.

Hyperautomation synthesizes these approaches by layering RPA, AI and analytics so systems can handle nuanced multiphased responsibilities while learning to continually improve over time without ongoing coding. For instance, an AI-enhanced supply chain bot could track purchase orders via IoT sensors, query shipment quality data in documents, negotiate rates based on pricing history, authorize blockchain payments and issue customer notifications.

The hyperautomation advantage stems from enabling sophisticated yet adaptable automation across disconnected platforms so employees need only handle exceptions. Governance dashboards would monitor automated workflows end-to-end with ML optimization directing any weaknesses to human agent review. That maximizes automation’s scale while retaining necessary customization.

According to McKinsey research, over 70% of companies have begun piloting some hyperautomation initiatives with AI-powered business process reengineering focused on customer relations, risk monitoring and strategy analysis. Gartner projects hyperautomation driven by ML algorithms to handle the bulk of repetitive office work by 2025.

Yet critics argue an over eagerness to automate white-collar human roles could negatively impact wages and employment rates long-term across many industries. Thus a balanced approach assessing jobs needing uniquely human skills versus repetitive tasks algorithms can support remains key to smooth workforce transitions. Either way, hyperautomation looks set to accelerate how business gets done this century.