Hyperautomation trends for 2025
One of the most promising emerging technological trends is hyperautomation, an end-to-end unification of automated functions that powers efficiency at scale. Many organizations leverage artificial intelligence (AI), machine learning (ML) and robotic process automation (RPA) to automate independent business functions in a highly integrated and efficient way.
However, forward-thinking businesses take hyperautomation further to get the most out of their people, processes, and technology.
Below, we’ll dive into the hyperautomation 2025 outlook and how AI drives automation in general, expanding upon hyperautomation specifically. We’ll touch on the need for increased security assurance, some industry-specific applications of the technology, the role that data and analytics play, and what the future looks like for hyperautomation trends.
The rise of AI-driven automation
Hyperautomation leverages advanced technologies such as AI, machine learning (ML), and robotic process automation (RPA) to enable deeper and more complex use cases for automation. Integrating AI and ML within hyperautomation solutions allows for more intelligent, adaptive, and scalable automation processes. At base, hyperautomation is a supercharged application of robotic process automation (RPA), where bots move beyond basic tasks and contribute to higher-order business goals.
One strong example of AI innovation in automation comes from making and managing digital footprints to track and act on user behavior patterns. These footprints create dynamic insights into customer sentiment, allowing for targeted outreach.
By leveraging advanced technologies like AI, machine learning, and robotic process automation (RPA), hyperautomation enables better data-driven decision-making and enhances efficiency across tasks that once required human oversight.
The expansion of hyperautomation
While many technologies have leveraged AI in automation before, the robustness of hyperautomation can’t be overlooked. One of the biggest trends to look out for in years to come is greater productivity and accessibility of the tech.
The secondary impacts of this expansion will be felt throughout every industry as full-scale digital transformation becomes more feasible.
Companies that haven’t already switched to contemporary technologies and platforms should be able to with powerful, flexible automation. Generative AI (genAI) has transitioned from a programmer’s tool to a public benefit.
Migrating resources and computing processes to the cloud, collecting and operationalizing data, preparing for scalability, optimizing the user experience, and keeping all data secure have never been easier.
In particular, there are two main areas in which hyperautomation will expand.
1. Advanced automation capabilities
AI technology is improving so rapidly that it’s confounding technology experts worldwide. What that means for hyperautomation is greater practical functionality.
Features to look out for in 2025 and beyond include but are not limited to:
- Greater ML capabilities, allowing for swifter development of deeper insights
- More complex tasks, moving beyond basic inputs to intelligent selections
- Corrective capabilities, like editing or scanning for and making improvements
- Training development and delivery based on company-specific information
- Business automation via streamlined and sorted communication channels
These functions will increase the scope of AI and ML capabilities, improving their current performance and paving the way for wider utilization.
2. RPA integration with other technologies
Businesses have used RPA to automate things like clicking, scrolling, and other baseline inputs without capturing the complex psychological, social, and human underpinnings that motivate them.
But with hyperautomation, that is all changing.
Because hyperautomation unifies baseline automation with a capacity for learning and intelligence, it enables smart, automated activity. This, in turn, allows far greater applicability of these kinds of inputs, simulating human decision-making in real-time across a much wider variety of software, hardware, and systems. Nearly any app or program can now utilize development, testing, and maintenance automation.
Increased focus on security and compliance
With increased volume and diversity of data come bigger and more insidious threats to security and privacy. Cybercriminals of the future will leverage AI to attempt to compromise data, so hyperautomation is key to future-proofing security.
Hyperautomation will help organizations deal with AI-based security challenges like:
- Automated phishing and social engineering scams
- AI-powered malware development and deployment
- Misinformation and fraud schemes using deep-fakes
- Reconnaissance powered by automated AI and ML tools
Hyperautomation helps organizations scan for and detect threats, identifying and addressing them holistically by cross-referencing against all available threat intelligence. It also allows regular system-wide audits and remediation to ensure infrastructure and controls function as intended.
Simply put, automating security makes it more effective.
Another related element to consider is compliance. Hyperautomation will be used to meet and exceed the requirements of existing and emerging security regulations.
Industry-specific applications of hyperautomation
Forward-thinking businesses in every industry will constantly find more impactful uses for hyperautomation. They and the managed service providers (MSPs) they work with are always looking for tasks to automate or optimize with big data insights.
In particular, some of the biggest advancements will come in:
- Manufacturing: Enhance production efficiency through hyperautomation in factories.
- Healthcare: Automate sensitive data processing using hyperautomation and gain deeper insights into patient care.
- Research: Process vast quantities of data to test hypotheses and drive discoveries.
- Financial services: Improve both compliance processes and customer service through automation.
- Digital footprint: Guard digital reputation and security.
- Customer experience: Enhance customer experience through personalized interactions and understand customer sentiment more effectively using data-driven insights.
- Decision-making: Make more informed, data-driven decisions across industries.
- Accuracy: Increase the accuracy of tasks and operations through automation.
- Resource allocation: Improve resource allocation, not by replacing people, but by making their jobs easier and more rewarding, increasing job satisfaction and retention.
- Product/service value: Understand and optimize the value of product or service offerings.
- Customer purchase behavior: Analyze and predict customer purchase behavior to drive sales strategies.
- Cost savings: Reduce operational costs through efficient processes.
- Scalability: Scale operations seamlessly through automation.
Let’s take a closer look at a few specific industries:
Hyperautomation in manufacturing
Manufacturing already sees some of the highest use of AI in volume and intensity. According to an MIT Sloan study of AI use across industries, manufacturing had the highest overall usage of AI and the largest combination of high—and medium-intensity usage relative to other industries.
Moving forward, those usages will only increase.
The major impacts of AI and hyperautomation on manufacturing come in many different forms, but two of the most common relate to factory performance. Smart factories leverage hyperautomation to account for various production needs that previously would have required direct human force or oversight. Now, it’s all (or mostly) AI.
AI and ML allow for intelligent predictive maintenance. Thanks to hyperautomation, expensive, high-leverage equipment are now safer and more efficient in the long term.
Hyperautomation in healthcare
Hyperautomation can streamline client (patient) management and admin functions in healthcare and optimize analogous functions in other industries.
A specific use case with wide applicability in and adjacent to healthcare is in the secure, compliant, and efficient electronic health records (EHR) processing. Any business that processes healthcare-related information typically needs to protect it according to the Health Insurance Portability and Accountability Act (HIPAA).
However, these protections often prove difficult to implement given the sheer volume and diversity of data and challenges in accurate risk monitoring and mitigation.
Hyperautomation helps companies scan for, detect, and safeguard data considered protected health information (PHI) under HIPAA, streamlining compliance efforts.
Hyperautomation in financial services
Hyperautomation aids secure recordkeeping and maintenance efforts in financial services operations. As in healthcare, fintech and other finance concerns collect and process sensitive information. There are also many overlapping regulatory concerns, which are increasingly challenging at scale.
Hyperautomation helps unify and optimize processes for anti-money laundering (AML) and know your customer (KYC) compliance. By automating data and access monitoring, all required information is stored and processed securely and made available to stakeholders who need it with minimal (if any) interruptions to service.
In addition, hyperautomation enables more dynamic and responsive chatbots that can help customers access critical information efficiently. It allows a move beyond basic inquiries to detailed guidance and feedback on potential transactions.
The critical role of data and analytics
Big data analytics have been critical to innovating, surviving, and thriving in every business environment for over a decade now. Automation and hyperautomation are driven by data and, in turn, empower companies to make better, smarter use of it.
However, effective use of big data is not just about generating or collecting as much data as possible. All information also needs to be selected, screened, and cleaned efficiently to ensure quality.
Hyperautomation will allow companies to enact these higher-order processes at the point of collection and generation, making more and better data available and actionable more efficiently. The practical effect will be leveraging data in real-time rather than waiting for lengthy (and costly) clearance periods.
The future of hyperautomation
Looking ahead, hyperautomation’s growth will be driven by advancements in the underlying technology. Innovations in AI, ML, RPA, and more will enhance functionality and accessibility, giving more businesses opportunities to leverage hyperautomation.
Advanced automation technologies to look out for in 2025 and beyond include:
- More complex generative adversarial networks (GANs)
- Quantum, edge, and other innovative computing approaches
- Swifter and more accurate natural language processing (NLP)
- Predictive analytics with greater accuracy and assurance
With respect to its economic impact, the hyperautomation market is estimated at $12.95 B as of 2024, and it is expected to reach $31.95 B by 2029. Its compound annual growth rate (CAGR) of 19.80% will be driven primarily by growth in the Asia-Pacific market and moderate growth (and the largest overall share) in the US.
Prepare for hyperautomation today
The future of automation tech is here, and forward-thinking businesses are already taking advantage of the benefits it provides. In the years to come, we’ll see further expansion of hyperautomation capabilities and adoption driven by AI, ML, NLP, and RPA. This will all lead to greater productivity, security, and data-driven optimization across industries.
To learn more about hyperautomation and trends to expect in 2025 and beyond—and how to take advantage—download our eBook on hyperautomation.
Or get in touch today to see firsthand how ConnectWise can help you leverage hyperautomation.
Overall, hyperautomation provides small to mid-size businesses significant potential to operate more efficiently, reduce costs, and grow sustainably.
