Across forums like Reddit, professionals are debating whether robotic process automation (RPA) has reached its limits. While RPA transformed repetitive tasks, the next frontier is Agentic Process Automation (APA)—intelligent, adaptive, and context-aware automation.
Unlike traditional RPA, APA uses AI agents, machine learning, and natural language processing to make decisions, handle exceptions, and optimize workflows in real time.
This blog explores how agentic AI is reshaping process automation and how no-code process automation tools like FlowForma are pushing the future of agentic process automation with AI-powered innovations. But first, let’s cover some fundamentals.
Agentic process automation systems utilize AI agents and advanced machine learning algorithms to execute and automate complex workflows autonomously while mandating human intervention at key decision points or when required. It combines natural language processing, data analysis, and AI capabilities to make decisions, manage exceptions, and optimize business processes in real time.
Unlike traditional robotic process automation, which relies on predefined rules and rule-based tasks, agentic systems adapt dynamically, perform tasks across multiple systems and software applications, and streamline operations.
This intelligent automation approach reduces human error, automates repetitive tasks, and boosts operational efficiency, freeing both business and IT teams to focus on higher-value, strategic work rather than substantial human intervention.
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💡It is important to note that Agentic AI and agentic process automation might sound similar, but they solve very different problems. Agentic AI powers individual agents; agentic process automation orchestrates these agents across end-to-end workflows. |
Suggested reading: A comprehensive guide to process automation
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Traditional automation methods rely on predefined rules, requiring reconfiguration whenever there’s a change in input, approval hierarchy, or data format.
In contrast, agentic process automation uses AI technology to interpret intent, analyze inputs, and select optimal paths autonomously—making it suitable for complex business processes and real-world variability.
Key differences include:
|
Aspect |
Traditional automation |
Agentic process automation (APA) |
|
Concept |
Executes predefined, rule-based tasks |
Works toward defined goals using reasoning and decision logic |
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Use cases |
Automating repetitive tasks, standardized data exchange, high-volume, low-decision work |
Multi-step complex workflows with exceptions, unstructured data handling, and compliance-driven operations |
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Data handling |
Structured data only |
Uses intelligent document processing and data analysis for both structured and unstructured data |
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Error handling |
Stops when exceptions occur |
Detects, corrects, or escalates exceptions automatically |
|
Human involvement |
Needs supervision for exceptions |
Operates with minimal human intervention under defined business rules |
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Scalability |
Routine tasks, limited governance |
Scales complex workflows with embedded governance |
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Implementation focus |
Script configuration and traditional RPA deployment |
Process optimization through reasoning and orchestration with agentic automation agents |
Benefits of agentic process automation
Agentic Process Automation (APA) excels by maintaining high performance under changing conditions and reducing human oversight, without compromising control over key processes.
APA agents handle deviations in data or unexpected inputs by validating information, identifying missing components, and routing exceptions for review.
FlowForma’s AI Agent Rule acts as your intelligent assistant, executing predefined actions based on your instructions. It automates intelligent actions such as:
For example, FlowForma’s AI Agent can streamline IT security compliance workflows such as completing ISO, SOC 2, or penetration testing questionnaires. Instead of lengthy email exchanges, external vendors can securely upload documents through an Engage Form. The agent then extracts key details, validates responses, identifies missing information, and classifies risks (high, medium, low).
If the AI Agent Rule identifies any issues or discrepancies, it automatically triggers follow-up flows involving relevant approvers (e.g., Head of R&D, Security, or HR). When criteria are met, the process can even auto-approve submissions, saving hours of manual review while improving accuracy and security.
The result? Faster approvals, fewer errors, stronger governance, and significant time savings—all while maintaining full transparency and compliance.
APA agents use AI and data analysis to assess dependencies before acting, ensuring accurate decisions across complex workflows.
FlowForma AI Agent Rule ensures consistent, validated actions and delivers intelligent recommendations based on real-time data. On the other hand, the AI Summarization Agent triggers summarization at any stage in your process to receive:
These capabilities empower teams to make faster, well-informed decisions across every stage of the workflow lifecycle.
APA solutions automate tasks like approvals and compliance reviews, scaling easily as your business grows. With FlowForma, teams can design, deploy, and adjust workflows at scale—whether for onboarding, supplier management, or compliance—without relying on IT.
Users can:
This approach puts automation in everyone’s hands, cutting the time from idea to live process, simplifying complex workflows, and automating even unstructured or manual tasks. Built-in analytics enhance compliance and audit readiness while unlocking smarter insights for continuous improvement.
Moreover, when building a supplier onboarding workflow using the FlowForma AI Copilot, you can define specific triggers, rules, and conditions to dynamically fit your requirements (as demonstrated here).
The FlowForma Discovery Agent (as shown below) further accelerates design by listening during meetings, identifying process requirements, and automatically generating workflow drafts, improving efficiency and alignment between business and IT teams.
With each cycle, APA improves decision-making models and adapts to new conditions. lowForma supports continuous optimization through real-time monitoring, data-driven recommendations, and adaptive automation.
FlowForma Insights further enhances this capability by turning performance data into visual dashboards and reports that reveal trends, risks, and opportunities. Users can track process health, identify bottlenecks, and measure ROI in real time—enabling continuous improvement and greater transparency across all automated workflows.
APA reduces the need for manual reconfiguration and maintenance, driving higher ROI. FlowForma’s transparent, process-based pricing ensures cost efficiency with no hidden fees, making it a budget-friendly solution.
You can explore FlowForma’s pricing plans in detail on this page.
APA eliminates repetitive tasks, allowing employees to focus on exceptions and strategic improvements. FlowForma’s AI Agent Rule plays a key role by automating routine, rule-based actions such as reading uploaded documents, extracting data, and validating content—saving hours of manual effort.
It ensures data is accurate, complete, and properly formatted before entering workflows, reducing human error and improving reliability. By returning structured data directly to forms or systems, it accelerates approvals, reporting, and downstream processes for higher operational efficiency.
Once configured, the AI Agent Rule scales effortlessly to handle large data volumes without extra staffing, while results are automatically synced across systems for seamless, end-to-end automation. It also provides consistent decision support, executing predefined actions reliably across audits, compliance checks, and reporting processes. Combined with FlowForma’s no-code platform, business users can automate independently and act faster, while IT teams retain governance and control.
FlowForma’s Summarization Agent complements this by providing concise, real-time updates on completed steps, key decisions, and blockers—helping teams track progress, improve collaboration, and maintain full process visibility without manual oversight.
APA ensures transparency with automated logs and reasoning data, making audits easier.
FlowForma supports compliance by embedding audit trails and real-time governance controls, keeping your processes audit-ready at all times.
How FlowForma’s compliance modules work
APA is a major step forward from traditional automation, offering adaptive workflows that improve continuously, while AI-powered process automation tools like FlowForma make it easier to scale, maintain compliance, and keep costs down.
FlowForma has also created a specific product, FlowAssure, to help with risk assessment.
FlowAssure AI Agents
FlowAssure supports vendors uploading questionnaire answers, reports (ISO, SOC2, pen tests) and then its agents automatically classify, score and flag. From an APA viewpoint, this means:
The agentic approach supports faster turnaround. For example, FlowAssure claims reduced review times from days to minutes. Agents can not only score assessments but can trigger next steps — escalate to the right stakeholder, initiate remediation workflows, send alerts, etc. That orchestration is a hallmark of APA (agents acting, not just humans reacting).
How does agentic process automation work?
Agentic Process Automation executes workflows autonomously by combining data interpretation, reasoning, orchestration, and continuous learning. Here are the seven key steps demonstrating how agentic process automation works in practice:
Each automation starts with a clear outcome. This could be resolving a customer issue, completing a transaction, or reconciling a record. The system interprets this goal as the target state to achieve.
The agent gathers all relevant information from databases, APIs, forms, and communication channels. It handles both structured data and unstructured inputs like documents, messages, or logs.
The agent evaluates inputs, identifies dependencies, and breaks the goal into manageable tasks. It establishes the order of execution while following policies and compliance rules.
The agent performs actions across connected systems—updating records, sending notifications, approving transactions, or invoking APIs. Each step is tracked for transparency and traceability.
The agent continuously observes progress and detects exceptions. If a system is unavailable or data is incomplete, it adapts, reroutes, or requests human input instead of failing.
After execution, the agent analyzes results to refine decision-making rules. Future workflows leverage this knowledge to perform more efficiently and accurately.
Now, let’s understand how agentic process automation works through an example.
In compliance-driven environments, FlowForma’s no-code platform provides a governed framework for integrating agentic intelligence into structured workflows with full transparency.
To understand agentic process automation in action, consider Blackpool Teaching Hospitals NHS Foundation Trust, where administrative workflows like New Starter forms, Requests for Agency Spend, and Clinical Safety Checks were automated using FlowForma.
NHS testimonial
FlowForma automatically gathers data from forms, approvals, and records, identifies missing details, and routes tasks to the right staff. Incomplete forms trigger data requests instead of halting progress, while multi-department approvals and exceptions are managed seamlessly.
This reduces delays, minimizes errors, and keeps compliance-sensitive workflows running smoothly.
FlowForma’s blend of agentic intelligence and no-code automation has helped the BTH streamline over 70 processes—improving accuracy, saving time, and freeing staff to focus on higher-value work. Read the full case study here.
Agentic Process Automation (APA) is transforming how regulated industries handle complex, rule-driven processes. By combining data-driven reasoning with adaptive decision-making, APA automates workflows that once relied heavily on human oversight.
I recently hosted a webinar discussing the top three use cases of Agentic Process Automation. Check out the recording here below.
Here’s an overview of the key applications of agentic AI in process automation in top industries:
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Industry |
Top agentic process automation applications |
Insurance |
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Financial services |
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Healthcare |
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Manufacturing |
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Construction |
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Let’s dive into the detailed exploration of the top applications.
In insurance, APA streamlines workflows like claims processing, policy management, and customer service—reducing manual errors, accelerating approvals, and ensuring faster compliance reviews.
AI agents can automatically read, validate, and complete IT security questionnaires for vendor or software assessments, helping insurers meet ISO, SOC 2, and other regulatory standards more efficiently.
One of the world’s largest insurance brokers, Aon, has automated its claims management process, eliminating manual interventions and improving approval times.
By automating these processes, the company achieved faster claims resolution, improved compliance in a highly regulated environment, and delivered a more consistent and efficient experience for both customers and staff. [Read the full case study here.]
In financial services, automating client onboarding, audit reporting, and compliance processes can reduce the time spent on manual data entry, enhance data consistency, and ensure timely compliance with regulations such as DORA.
For example, Grant Thornton saw significant improvements in client onboarding and audit reporting workflows after automating these processes.
By reducing the time spent on manual tasks, the firm not only improved the accuracy of financial reports but also accelerated its client service, enabling faster decision-making and better compliance adherence.
In healthcare, the need for efficient patient intake, appointment scheduling, and claims processing is paramount. Automating these administrative tasks frees up healthcare providers to focus on what matters most: patient care. Automation also ensures compliance with strict regulatory standards (such as HIPAA), which is critical in the healthcare industry.
At Blackpool Teaching Hospitals NHS Foundation Trust, the automation of patient intake and verification processes significantly reduced processing time, enabling staff to devote more time to patient care. This streamlined approach improved operational efficiency and patient satisfaction, all while maintaining strict compliance with NHS regulations.
In the construction industry, managing project approvals, site inspections, and safety compliance is complex, involving multiple stakeholders and strict regulations like OSHA. Automating these workflows leads to faster project timelines, fewer errors, and greater accountability.
For Downer New Zealand, automating project approval workflows and resource planning enabled the company to reduce administrative overhead, speed up project execution, and improve overall project management efficiency. This approach helped Downer meet project deadlines and ensure the quality of work while managing compliance and risk.
Automating key processes in the manufacturing industry, like inventory management, production scheduling, supplier management, and onboarding, streamlines operations and improves outcomes.
With FlowForma AI Copilot, manufacturers can automate supplier onboarding by describing workflows in natural language, as shown here.
This eliminates manual data entry, speeds up procurement, and ensures accurate supplier data, resulting in faster time-to-market and better cross-team collaboration without compromising quality.
Introducing autonomous behavior into process automation raises technical and governance challenges. Each must be addressed systematically to achieve reliable performance.
Below are key challenges organizations face when adopting agentic automation, and how platforms like FlowForma help address them.
Automated systems must operate within clear guardrails, with full visibility and accountability, while keeping sensitive data secure.
How FlowForma addresses it: Embeds governance within each workflow, maintaining complete audit trails, approval hierarchies, and real-time visibility into automated actions. Importantly, all data is hosted in the organization’s own SharePoint environment, ensuring that FlowForma does not store or manage data externally.
Inaccurate data can disrupt downstream decisions and outcomes.
How FlowForma addresses it: Applies validation rules, field checks, and approval checkpoints to maintain clean, consistent data across all connected systems.
AI-driven decisions must be traceable and explainable.
How FlowForma addresses it: Generates detailed process logs and reasoning paths, allowing teams to view, audit, and justify every automated decision.
Connecting multiple enterprise systems can slow automation deployment.
How FlowForma addresses it: Uses pre-built connectors and no-code integration templates to link systems quickly and automate complex workflows without coding.
Autonomous agents require secure permissions to act across systems.
How FlowForma addresses it: Enforces role-based access, data encryption, and approval gates, ensuring every automated activity remains secure and compliant.
Automation adoption can stall if users lack confidence in autonomous systems.
How FlowForma addresses it: Supports phased rollout and pilot workflows, allowing teams to test, refine, and build trust before scaling automation enterprise-wide.
Agentic Process Automation is evolving from simple task automation to autonomous, goal-driven workflows that adapt in real time. This shift is powered by intelligent agents capable of reasoning, learning, and collaborating across systems, moving beyond traditional rule-based automation.
In fact, one of our top 5 predictions for 2025 was exactly this shift toward adaptive, autonomous workflows—entailing how APA will increasingly enable agents to manage processes end-to-end while humans focus on strategic oversight. Watch this video to learn more.
FlowForma’s top five predictions on the future of AI Agents
Let’s walk through the top drivers propelling the future of agentic process automation.
The global agentic AI market is experiencing rapid growth. According to MarketsandMarkets, the market is projected to expand to USD 93.20 billion by 2032, reflecting a compound annual growth rate (CAGR) of 44.6%.
The concept of the agentic organization is gaining traction, where intelligent agents are integrated across all layers of the value chain. This model enables continuous optimization and autonomy at scale, with human supervisors providing strategic oversight rather than manual intervention.
Despite the promising outlook, Gartner warns that over 40% of agentic AI projects may be discontinued by 2027 due to weak business alignment or overestimated capabilities. Successful adoption of APA requires:
In the next decade, APA will evolve from automating discrete tasks to managing end-to-end, outcome-based processes. By enabling agents to interpret meaning, adapt to context, and collaborate with humans, APA will drive:
The future of Agentic process automation is focused on moving from traditional, rule-based workflows to more flexible, intelligent systems that can act on intent, analyze data, and drive results autonomously, while keeping compliance and transparency intact.
For IT and automation leaders, APA offers a way to scale complex processes without adding overhead or losing control. Achieving this requires strong governance, structured workflows, and effective data management, which are essential for any successful automation journey.
FlowForma simplifies this transition. Here’s how the platform supports your process automation goals:
Ready to improve agility and streamline your operations with the power of agentic process automation? Book a Demo and see how FlowForma transforms your workflows.