If you’re from the world of automation, you must have heard the two buzzwords – Hyper Automation and Intelligent Automation.
As per the research reports, the industrial automation market will likely surpass around $459.51 Billion by 2032 and will grow at a CAGR of 9% during the tenure from 2023 to 2032. These statistics indicate the indispensable growth of automation and how extensively enterprises are navigating the intricate realm of Hyper Automation and Intelligent Automation to streamline business processes.
As enterprises grapple between these two approaches, delving into their intricacies becomes crucial for making informed decisions that align with organizational goals and pave the way for unparalleled operational efficiency.
So, let’s get started with their definition and gradually learn the core difference between Hyper Automation and Intelligent Automation through this blog.
What is Hyper Automation? – Understanding the Term
As per IBM, Hyperautomation, as a concept, automates everything worthy of automation within an enterprise. It provides a seamless framework for deploying different automation technologies strategically, either separately or in tandem, augmented by Artificial Intelligence (AI) and Machine Learning (ML).
With the right adoption strategy, Hyper Automation can streamline enterprise processes using Intelligent Process Automation (IPA), which is nothing but a combination of Robotic Process Automation (RPA), Artificial Intelligence (AI), and other technologies with minimal human intervention.
Apart from IPA, Hyper Automation often leverages other technologies like Natural Language Processing (NLP), Optical Character Recognition (OCR), and Intelligent Document Processing (IDP) to provide superior automation capabilities leveraging data from different sources.
By implementing a dedicated Hyper Automation platform, you can:
- Reduce your automation cost and align your business and IT processes.
- Enhance your company’s security and governance.
- Seamlessly measure the ROI of your automation and establish future automation priorities.
- Streamline back-office and customer-facing operations.
- Improve the quality, speed, accuracy, cost, and efficiency of your operations and processes, thus improving the net revenue and market share.
What is Intelligent Automation?
Intelligent Automation leverages Artificial Intelligence (AI), Business Process Management (BPM), and Robotic Process Automation (RPA) to transform enterprises digitally and scale decision-making capabilities.
Artificial Intelligence (AI) – It’s the main decision engine of Intelligent Automation, and enterprises can use Machine Learning (ML) and complex algorithms to analyze structured/unstructured data, create a knowledge base, and make predictions.
Business Process Management (BPM) – It’s also called Business Workflow Automation and automates workflows, making business processes more agile and consistent. Enterprises from across industries use BPM capabilities to improve customer interactions and engagement.
Robotic Process Automation (RPA) – It leverages bots/software robots to wrap back-office tasks like data extraction, form filling, etc. RPA can conveniently leverage AI insights to handle complex tasks and other use cases.
The perfect blend of these components can digitally transform the enterprise workflows and processes and elevate customer experience.
- Intelligent Automation can:
- Process unstructured data
- Automate tasks that require judgment.
- Detect and adapt to consumer and business changes.
- Facilitate resource and KPI planning.
- Manage exceptions and make internal course adjustments.
Hyper Automation vs Intelligent Automation: What Differentiates Them?
Hyper Automation and Intelligent Automation concepts work similarly, ushering enterprises into a new era of efficiency, but still have subtle differences that one may unknowingly overlook.
So, the following segment helps you understand the core differences between the two:
Primary Use Case
Hyper Automation can automate multi-step processes and standard digital workflows using cognitive processes, while Intelligent Automation relies on intelligent algorithms to automate operational workflows and muti-step tasks.
Tools and Technology Required
Hyper Automation leverages multiple Machine Learning (ML), packaged software (Process Mining, No Code/Low Code Apps, Analytics), and Automation Tools, while Intelligent Automation requires custom development and leverages multiple Machine Learning (ML) modules and automation tools.
Outcome
Leveraging Hyper Automation, enterprises can create smart and efficient operations, while Intelligent Automation can make their complex operations more efficient and streamlined.
Governance Approach
Hyper Automation operates on a People-first and Process-first approach, while Intelligent Automation operates solely on a Process-first approach.
Implementation
Hyper Automation generates the highest ROI in the long term and demands a certain level of digital infrastructure maturity and cross-system orchestration to deliver outcomes. On the contrary, Intelligent Automation Services generates a significantly higher ROI and requires unconstrained data access and a suitable environment for deployment.
The Bottom Line
Hyper Automation and Intelligent Automation will exist for a long time since robust AI engines foster efficiency within enterprises, enabling proactive decision-making capabilities. Implementing automation becomes a cakewalk under the right guidance and with a proper implementation strategy.
So, if you are considering building an end-to-end automation capability for your enterprise, connect with our experts today and reap the full benefits of automation via quality-assured services from iOPEX.
