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Industry Landscape
The hyperautomation market is experiencing rapid growth, driven by enterprises seeking efficiency, cost reduction, and enhanced experiences. AI and low-code/no-code platforms are democratizing automation, moving beyond traditional RPA to intelligent, end-to-end process transformation. Companies are increasingly investing in solutions that integrate various technologies to achieve comprehensive digital transformation.
Total Assets Under Management (AUM)
Global Hyperautomation Market Size in United States
~The global hyperautomation market size was valued at USD 13.9 billion in 2022.
(24.9% CAGR)
- Driven by digital transformation initiatives.
- Increasing adoption of AI/ML in business processes.
- Demand for cost reduction and efficiency.
Total Addressable Market
19.9 billion USD
Market Growth Stage
Pace of Market Growth
Emerging Technologies
Multimodal AI
Integrating various data types like text, image, and speech into AI models, enabling hyperautomation solutions to understand and interact with the world in a more human-like and comprehensive way.
AI TRiSM (Trust, Risk, and Security Management)
A framework to ensure AI models are explainable, fair, secure, and compliant, becoming critical for deploying trustworthy and responsible hyperautomation solutions at scale.
Process Mining & Task Mining
Advanced analytical techniques that automatically discover, map, and analyze business processes from event logs and user interactions, providing critical insights for identifying and optimizing automation opportunities.
Impactful Policy Frameworks
NIST AI Risk Management Framework (AI RMF 1.0, 2023)
Published by the National Institute of Standards and Technology, the AI RMF provides voluntary guidance to manage risks associated with the design, development, use, and evaluation of AI products, services, and systems.
It will likely influence enterprise procurement decisions, pushing companies like Cuber AI to demonstrate adherence to ethical AI principles and robust risk management for their solutions.
Executive Order on the Safe, Secure, and Trustworthy Development and Use of Artificial Intelligence (October 2023)
This broad U.S. Executive Order outlines a comprehensive approach to AI regulation, focusing on safety, security, privacy, equity, and competition, and mandates various federal agencies to develop AI standards and guidelines.
It will drive increased scrutiny on AI model transparency, data privacy practices, and security within hyperautomation solutions, potentially increasing compliance costs but also fostering greater trust.
California Consumer Privacy Act (CCPA) and California Privacy Rights Act (CPRA) (2018/2020)
CCPA, amended by CPRA, grants California consumers extensive rights regarding their personal information, including the right to know, delete, and opt-out of the sale or sharing of their data, with strict requirements for businesses handling such data.
Cuber AI must ensure its hyperautomation solutions, especially those handling customer data, comply with stringent data privacy and consent requirements, particularly when processing or storing PII.
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