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- Hyperautomation or Hype? Why 30% of Enterprises Are Betting Big
Hyperautomation or Hype? Why 30% of Enterprises Are Betting Big
What happens after you’ve automated everything you can see, but yet, inefficiencies still hide beneath the surface? How do organizations move from robotic process automation to systems that actually think and adapt? This article explores that evolution, from the RPA era to today’s hyperautomation boom, and introduces the next leap: the AgenticOS, an operating system that creates AI employees rather than tools. Discover how leading enterprises are redesigning processes with AI-first logic, using data to uncover hidden gains, and freeing humans to focus on creativity and strategy in a world where automation learns rather than just simply execute.
Ross Green
October 28, 2025
Table of Contents
Introduction:
A decade ago, the automation story revolved mostly around efficiency by using bots to handle repetitive tasks and robotic process automation (RPA) to take the edge off human workloads.
Today, that story has evolved into something much more intelligent, interconnected, and human-aware. Hyperautomation, which is the fusion of RPA, artificial intelligence (AI), machine learning (ML), and analytics, marked the turning point from isolated task automation to end-to-end process intelligence.
In short, RPA is rule-based and static, while machine learning adapts dynamically to new data and conditions.
But even hyperautomation is only a bridge.
What’s emerging now is an agentic operating system (AgenticOS), or a novel design by Custom AI Studio (CAIS) that involves a new layer of enterprise intelligence where AI agents don’t just execute work, but rather, they understand context, coordinate across systems, and act as digital employees alongside their human counterparts (source).
The AgenticOS creates AI employees rather than glued-on AI tools.
Created by Ross W. Green, MD (October 27, 2025). “From RPA to Hyperautomation.” Canva.com
This article traces that evolution.
Section 1 (“History & Today”) explores how automation matured from RPA in the 2010s to the hyperautomation wave of the 2020s, and ultimately why we’ve reached a new threshold where 30% of enterprises will soon automate over half their operations.
Section 2 (“How Hyperautomation Actually Works”) breaks down the mechanics behind this shift, including how leading organizations are redesigning workflows with an AI-first mindset, using process mining to uncover inefficiencies worth 10–40% productivity gains, and thereby redefining human roles by eliminating “glue work.”
Section 3 (“Measuring the Moment”) examines the enterprise impact, including cost savings up to 30%, trillion-dollar markets, and the execution gap that still limits most companies.
And finally,
Section 4 (“Looking Ahead”) peers into the next decade, where hyperautomation becomes foundational and the AgenticOS architectures turn businesses into adaptive, self-optimizing systems, thereby effectively acting as the autopilot for enterprise operations.
In short, we’re moving from automating tasks to engineering intelligence. The companies that master this shift, from RPA to hyperautomation to the AgenticOS, will think faster on top of thinking smarter, thereby continuously learning and adapting as living, evolving systems.
Section 1: History & Today
Before we explore the cutting edge of automation, it’s worth looking back at how we got here. This section thus traces the evolution from early Robotic Process Automation (RPA) in the 2010s to today’s era of hyperautomation, where AI, machine learning, and analytics combine to automate entire workflows.
You’ll also see how we reached the “30% threshold,” with a growing share of enterprises automating over half their operations, and what forces are driving this rapid shift.
Section 1.1: Beyond RPA: The Journey from Robotic Process Automation (2010s) to Hyperautomation Robotic Process Automation (RPA) first gained traction in the 2010s, allowing businesses to automate repetitive, rules-based tasks (like data entry or invoice copying) that were traditionally done manually. Over time, however, companies realized that simple RPA bots alone had limitations…read more here.  Created by Ross W. Green, MD (October 27, 2025). “Beyond RPA.” Canva.com | Section 1.2: AI vs. Human: The 30% Threshold: Why 30% of Enterprises Are Automating Over Half Their Operations by 2025 We’ve now reached a tipping point in adoption. Recent forecasts signal that roughly 30% of enterprises will have automated more than half of their overall operations by the mid-2020s (For context, that figure was under 10% just a couple years prior.)…read more here.  Created by Ross W. Green, MD (October 27, 2025). “What 30% of Enterprises Already Know.” Canva.com |
Section 2: Three Implementation Realities
If Section 1 showed how we arrived at today’s automation era, this section unpacks what makes modern hyperautomation tick, and why it works so differently than past approaches.
2.1: The AI-First Redesign explores how leading organizations are rethinking processes from the ground up instead of just automating inefficient workflows.
2.2: Process Mining Gold reveals how AI-driven analysis uncovers hidden inefficiencies worth 10–40% productivity gains.
2.3: The Human Handoff shows how automation eliminates “glue work,” empowering people to focus on higher-value, creative, and strategic work.
Together, these parts explain the practical mechanics, and human impact, of moving from basic automation to truly intelligent, end-to-end transformation.
Section 2.1: The AI-First Redesign and Rethinking Processes Instead of Automating Broken Workflows A hard lesson learned in early automation projects was that if you automate a bad process, you simply get a faster bad process. In other words, “digitizing dysfunction” doesn’t fix the underlying problem. Many organizations fell into the trap of taking an inefficient workflow…read more here.  Created by Ross W. Green, MD (October 27, 2025). “The AI Redesign” Canva.com | Section 2.2: Process Mining Gold: Uncovering Hidden Inefficiencies (and 10–40% Productivity Gains) Hiding in Plain Sight How do you find out what to fix or automate in the first place? This is where process mining has become an indispensable tool in the hyperautomation toolkit. Process mining uses AI and data analytics to dig through the digital footprints of your operations (logs from IT systems, timestamps from transactions, etc) and reconstruct the real processes that are happening in your business…read more here.  Created by Ross W. Green, MD (October 27, 2025). “Hidden Inefficiencies Can be a Gold Mine to Fix.” Canva.com | Section 2.3: The Human Handoff: Elevating Employees by Eliminating “Glue Work” One of the most intriguing promises of hyperautomation is that it can actually make human jobs more valuable and interesting. This sounds counterintuitive at first since automation is often seen as something that replaces human labor. But in practice…read more here.  Created by Ross W. Green, MD (October 27, 2025). “The AI to Human Exchange.” Canva.com |
Section 3: By the Numbers
By 2026, hyperautomation will be a defining enterprise discipline, with 80–90% of organizations embedding it into their technology roadmaps and core operations. Despite major cost-saving potential (up to 30%) and a projected $1 trillion market value, fewer than 20% of companies can effectively measure automation success, thereby underscoring a critical execution gap even as adoption accelerates.
Topic | Statistic (Latest Data) | Reference |
Majority of operations automated | 30% of enterprises will automate over half of their network activities by 2026 (up from under 10% in mid-2023) | |
Hyperautomation as enterprise priority | 90% of large enterprises treat hyperautomation as a key “staple” discipline (core practice) in their organization | |
Measuring automation success | Fewer than 20% of organizations have mastered measuring the success of their hyperautomation initiatives | |
Market for hyperautomation software | $1.04 trillion: Projected global market value of hyperautomation-enabling software by 2026 | |
Operational cost reduction potential | Up to 30% reduction in operational costs by 2025 for organizations leveraging hyperautomation at scale | |
Hyperautomation on technology roadmaps | 80% of organizations will have hyperautomation on their technology roadmap within the next 24 months |
Section 4: Looking Ahead, 1-3 years from now, 5-10+ years from now
Created by Ross W. Green, MD (October 27, 2025). “Is this all Farfetched?” Canva.com
In the very near term, we’re likely to see process mining and data-driven planning become standard practice before any automation project. Think of it as “measure twice, automate once” becoming the norm. Organizations have learned that blindly automating without understanding a process is suboptimal, so a best practice is emerging: diagnose and optimize the process first, then automate.…read more here.
Final Thoughts:
The automation story is no longer about replacing human effort — it’s about reimagining how intelligence itself is distributed across people, systems, and AI agents. Hyperautomation proved that end-to-end digital operations were possible; the rise of the CAIS’ AgenticOS now shows that these operations can be adaptive, conversational, and self-improving.
As enterprises cross the 30% automation threshold, the leaders will be those who treat automation as a living capability rather than just a one-time project, one that measures itself, learns from its own data, and continuously redesigns work around outcomes rather than effort. The next frontier building organizations that can think, act, and optimize like intelligent systems, not just automation!
In that sense, hyperautomation was the rehearsal, and the AgenticOS is the main act.
It’s the moment when the enterprise stops being a collection of workflows and becomes an integrated network of human and digital intelligence, operating with the same fluid coordination as a living organism.
Other resources:
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