Artificial Intelligence and Robots are redefining the rules for organizational agility and business execution in the digital transformation age.

Intelligent Automation, integration of AI and RPA have led the industrial revolution and machine age by challenging previous business models. However, with changing technologies, automation technologies and traditional RPA will pave way for analytics and AI. Hence, it aims to support intelligent automation, combining case management, workflows and making intelligent automation suits, and BPM. However, this will play a significant role in digital transformation.

Digital transformation has been highly limited to the relative and repetitive process areas that are rule-driven. However, when integrating case management and data-driven intelligence with process automation, the entire process could manage or automate. Hence, Intelligent Automation broadly covers:

  • Natural Language Processing
  • Computer Vision
  • Machine Learning
  • Autonomics

However, decisions and AI are put to the composition of these devices, functionalities, and apps to obtain true intelligent automation.

Intelligent Automation

Intelligent Automation is speedily coming of age as bot and machine systems become smart in the mainstream. However, Intelligent Automation is also enticing new investors as an investment in the novel technology. It is driven foremost by the objectives of organizational and scalability agility. However, cognitive science and convergence of technology offer businesses powerful tools to challenge new models with more certainty.

Businesses are Escorting Change

The redundant process automation is the first step that has begun by RPA. However, an intelligent organization would strategically design automation to join its data sources and interconnect systems. It will enable users to quick response to the countless threats and opportunities in the business.

Intelligent Automation and Cognitive Governance

Cognitive governance is the tactical driver of intelligent automation in guiding scores of organizational outcomes. It facilitates the framework of implementing intelligent automation for the creation of business intelligence. It aims for better decision-making abilities thus reducing the manual processes that lead to delays.