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Enterprise AI agents:evolution for your automation efforts

Deploy enterprise AI agents inside a governed orchestration layer that coordinates people, systems and AI, with oversight and audit built in.
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$126.9B

global agentic AI market by 2029

82%

companies plan AI agent workflow integration in the next 1–3 years

3.5 X

ROI for organizations investing in agentic AI

Flowable recognized in the Gartner® Magic Quadrant™ for Business Orchestration and Automation Technologies 2026
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Flowable is included in Forrester’s Adaptive Process Orchestration Landscape
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What are enterprise AI agentsand how do they work?

Enterprise AI agents are the next evolution in artificial intelligence (AI), with systems progressing from task-based automation and content generation to proactive decision-making and goal pursuit. It builds on earlier forms of AI, including predictive analytics and generative models, by introducing a new layer: context-driven autonomy. Enterprise AI agents represent the shift from isolated tasks to intelligent orchestration.

Unlike traditional or generative AI, which often focuses on singular actions like creating a document or predicting a result, enterprise AI agents are outcome driven. This subtle shift allows an AI agent to take a broader view of a problem, enabling it to break complex goals into multiple steps, choose what to do next at any given point, and refine its approach as conditions change. These agents reason, plan and make decisions within defined boundaries based on context and intent.

These agents operate within a structure known as agentic architecture, which ensures agents act independently but always within clearly defined boundaries. When evaluating solutions, open standards like BPMN and CMMN serve as key buyer criteria for the orchestration layer and case models. Flowable delivers this structure through functionality such as case models, orchestration layers, and governance rules, making enterprise AI agents safe, scalable, and enterprise-ready.

Overview

Why agentic AI
changes the game

Traditional AI does one thing at a time - generating content, recommending actions, or classifying data - but business workflows are rarely that simple. Real-world workflows require coordination, decision-making, and adaptability.

Agentic AI introduces a new layer of intelligence to dynamically respond to what’s happening, remember past events, and adjust to reach the defined goal. Whether onboarding a customer or handling a claim, they know what success looks like and pursue it autonomously.

This shift from automation to orchestration makes agentic AI ideal for businesses managing complex, business-critical processes at scale.

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Use Cases

Unlocking real-world use
cases with AI agents

Agentic AI makes the most impact in sectors where precision, adaptability, and throughput matter most. Discover some of the top Flowable AI agent use cases right now.

Banking

Agents can control areas such as Know Your Customer (KYC) checks, complex compliance risks, and onboarding flows, ensuring increased accuracy and reducing cycle time. One of the big global banks implemented an AI system that reduced KYC processing time from days to minutes while improving fraud detection by 20%. A wealth management conglomerate deployed compliance agents to boost their AML requirements and achieved around 60% reduction of false positives within 12 months.

Insurance

Opening an account means proving who someone is, and AI does the first pass: reading IDs, verifying documents, matching data against records. Most applicants clear automatically. Anything ambiguous, a mismatch, a sanctions hit, an incomplete file, routes to a compliance officer for judgment. Every step, automated or human, lands in one audit trail. The obligation is the record proving due diligence happened, in order, every time.

Government

A purchase request comes in, and AI classifies the spend category and checks it against policy: budget limits, preferred vendors, contract terms. Requests within policy proceed automatically. Anything crossing a defined threshold, dollar amount, category, exception, goes to the right approver every time. The orchestration layer applies the rules consistently across every request, so approvals do not depend on who noticed the email first.

Healthcare

Not every case fits the structured path. When a claim, application, or order breaks the pattern, missing information, conflicting data, a judgment call the process did not anticipate, the case management layer takes over. A knowledge worker drives resolution, pulling in whatever steps the situation needs, with AI surfacing relevant history, suggesting next actions, and drafting responses. This is adaptive case management handling the work that does not repeat.

Boosting teamwork impact with AI agents

AI agents bring practical improvements to both business operations and technical delivery.

For customer facing teams

Agents can automate form handling, validation, and customer responses - reducing wait times and improving service quality.

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In sales and service processes, agents can track real-time interactions, personalize follow-ups, and instantly surface next-best actions.

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Agents can guide users through required documentation, flag governance gaps, and initiate policy and activity reviews in compliance-heavy environments.

For technical teams

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Agents can generate documentation, create test scripts and plans, or prepare deployment steps, significantly speeding up multiple areas of the software lifecycle.

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By monitoring system events, predicting failures, and launching resolution workflows based on predefined triggers, agentic AI agents can act as an always-on threat detection capability.

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With Flowable, developers can define agent roles visually using low-code editors or directly in code, embedding logic without rebuilding the full stack. This controlled flexibility enables rapid iteration and easy maintenance.

Benefits

Maximizing business performance with autonomous agents

Agentic AI does more than just automate; it transforms how work gets done. By coordinating tasks, making decisions, and adapting to change, agents unlock new ways to scale services, reduce costs, and improve experiences. They bring intelligence to every part of a process, delivering consistent value across the enterprise.

Boost productivity

Agents reduce manual work by taking over multi-step, context-heavy workflows. They operate 24/7 with consistent logic.

Scale operations

Agents adjust in real-time to shifting workloads, policies, or user behaviour. They scale and adapt faster than human resources without needing breaks.

Accelerate decisions

With access to context, data, and goals, agents support faster, more accurate decisions, independently or with humans in the loop.

Support innovation

By automating both routine and dynamic processes, agentic AI frees teams to focus on higher-value work and customer-facing improvements.

Cost savings

Agentic AI brings a new level of responsiveness, insight, and adaptability to your processes.

Get your AI enterprise-ready

Design, deploy, and scale agentic workflow orchestration.

Flowable Agentic Case Platform

Agentic AI does more than just automate; it transforms how work gets done. By coordinating tasks, making decisions, and adapting to change, agents unlock new ways to scale services, reduce costs, and improve experiences. They bring intelligence to every part of a process, delivering consistent value across the enterprise.

Building trustworthy
agentic AI apps with Flowable

Flowable provides everything you need to build, run, and govern agentic AI. Agents operate inside Flowable’s case models, which are structured environments that manage agent goals, data, permissions, and progress.

These case models keep the agent grounded in process logic while allowing autonomy to unfold in controlled stages. Of course, human-in-the-loop oversight and clear audit trails are provided to ensure visibility and trust at every step. With Flowable, AI agents can:

01
Trigger flows based on logic or events

AI agents in Flowable can initiate processes or sub-processes when specific conditions occur. Whether reacting to a data threshold, user action, or external event, agents know when and how to act. This agility gives you a responsive system where agents can proactively keep work moving, escalate delays, or launch recovery paths without waiting for human input.

02
Track their own progress

Agents don’t operate in isolation but understand what they’ve done, what’s next, and where they are in the flow. Flowable’s case models allow agents to retain context over time, enabling long-running, multi-step automation with full awareness of history and goals. This self-awareness creates an intelligent system that learns from what it does and adjusts dynamically.

03
Call APIs and access enterprise systems

Flowable makes it easy for agents to integrate with your existing tech stack. Agents can retrieve or update data in core platforms such as CRM, ERP, or document systems through standard APIs, connectors, and service tasks. This connectivity gives agents the information they need to act intelligently and ensures their actions fit seamlessly into enterprise workflows.

04
Escalate or ask for help when uncertain

Not all decisions should be made by AI alone. Flowable allows agents to hand off work or flag decisions when confidence is low, rules are unclear, or human input is explicitly required. This controlled collaboration makes agentic AI safer and more accountable, especially in regulated or customer-facing environments like banking and healthcare.

You stay in control. The agents do the work.

What’s coming next for agentic AI

Today’s agents can automate, decide, and coordinate, but the next wave will bring even more power, safety, and flexibility. Advances in context awareness, access control, and orchestration tools will help organizations deploy agents more broadly, with greater confidence and control.

The next evolution of agentic AI will unlock even more enterprise capability.

Memory
Agents will retain context across sessions, meaning they can learn from previous interactions and apply that knowledge to future tasks. As memory improves, agents will reduce repetition, improve handovers, and drive smoother user experiences, allowing them to respond more personally, accurately, and efficiently.
Entitlements
Entitlements define what each AI agent can access, see, or do within a process. These permissions ensure agents act within authorized boundaries, preventing errors, limiting risk, and supporting compliance.
Tooling
Orchestration platforms like Flowable will continue simplifying the design, monitoring, and scaling of AI agents. Improved tooling will make testing, updating, and governing agent behaviors across teams easier. This capability will help organizations move faster while maintaining visibility and confidence in how agents operate.

Consider the bigger picture

As these capabilities mature, agentic AI will become foundational in how businesses automate, orchestrate, and adapt.
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Challenges and risks with agentic AI

Agentic AI introduces new opportunities, but it also brings new responsibilities. As agents become more capable, organizations must think carefully about trust, access, data quality, and team readiness. Addressing these challenges will ensure agentic AI delivers long-term value without unexpected setbacks.

Trust and explainability

Autonomous agents must be accountable. Organizations need mechanisms to trace decisions, audit behaviour, and explain outcomes, especially in regulated environments.

Data quality and governance

Agents rely on structured, up-to-date data to act accurately. Weak governance or fragmented data sources can undermine outcomes and introduce unnecessary risk.

Security and access control

As agents gain more responsibility, they need tightly managed access to data and systems. Weak access controls can increase risk and lead to costly mistakes or security breaches.

Skills and readiness

Many teams aren’t yet equipped to deploy or manage agentic AI. Success requires collaboration with the right tools to bridge gaps across business, IT, and data functions. The right architecture, oversight, and gradual rollout strategies all help to mitigate these challenges.

FAQs

FAQs