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AI Business Process Automation Built on Process Orchestration

Govern AI inside high-stakes business processes, with auditability, human checkpoints and open standards built in.
Overview

What is AI business process automation?

AI business process automation is the practice of running AI inside business processes that are governed by a process orchestration layer. The orchestration layer decides when an AI task runs, what data it sees, and where a human reviews the result. AI handles the routine, repeatable work such as classification, extraction, prediction and content generation, while the process keeps control of sequencing, exceptions and audit. This is what lets enterprises run AI in high-stakes, judgement-heavy workflows without losing oversight.

Benefits

The benefits of AI in automation

Organizations that successfully implement AI-based tasks can yield a wide range of benefits. A few of the main ones being:

Process control, even with AI in the loop

AI tasks run as steps inside a governed process, not as a black box bolted on the side. Sequencing, exceptions and escalation stay under your control, whatever a given AI step decides.

Workflows your auditors can trace

Every AI task carries a full lineage: what it saw, what it decided, and who reviewed it. That traceability is what lets high-stakes workflows pass an audit.

Faster decisions, with humans where they need to be

AI clears the routine, repeatable work so people can focus on the judgement calls. Human review sits at the points that actually need it, not everywhere by default.

AI with Flowable

At Flowable, we provide full flexibility in choosing when and where to integrate AI. While we recognize AI's potential in automation, we understand it may not be suitable for all use cases. The decision to use AI should be based on the tangible benefits it offers to organizations according to its maturity level.

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Orchestrate AI inside your business processes
Process orchestration is the layer that makes AI safe to run at scale. AI tasks are components of the process, not its centre of gravity. Guardrails matter, but process control is what actually makes it work.
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Build human judgement by design
In real-world scenarios, business processes are dynamic. Flowable's case management capabilities empower organizations to effectively handle unpredictable processes that require human decision-making by design. Use AI to support decision-making with securely stored data at any given point. Integrating AI into human workflows fosters adaptability, enabling real-time decisions and seamless collaboration.
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Built on open standards: BPMN, CMMN, DMN
Enterprises evaluating an AI process orchestration platform should ask whether it's built on open standards. Flowable supports BPMN, CMMN and DMN, meaning your processes, cases and decisions are portable, inspectable and not locked in.
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Unify technologies for optimal efficiency
Flowable's flexible architecture empowers enterprises to integrate seamlessly with RPA, AI, chat applications, and enterprise systems, streamlining operations and boosting productivity through a single source of truth. Open API support and a broad range of out-of-the-box connectors ensure fast, unified connectivity across your existing systems and data sources.
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AI that learns from your process data
Flowable's contextual model generation helps modelers create process models faster, drawing on AI to speed up and simplify development work. Beyond modeling, Flowable's process automation generates vast amounts of data, which it efficiently aggregates from various systems. This rich dataset can be used to train machine learning (ML) models and power other AI initiatives, helping businesses predict trends, automate decision-making, and enhance operational efficiency.
Use Cases

Where Flowable runs AI inside business processes

Claims processing

A claim arrives and AI handles intake, classification, and triage: reading documents, flagging missing data, and routing by type and severity. Simple, low-risk claims move straight through automated stages. High-value or high-risk claims stop for human review before payout. CMMN governs the case work, BPMN structures the sequential stages, and DMN drives the routing rules, so decisions stay auditable and adjustable.

Customer onboarding

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.

Procurement and approvals

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.

Exception handling at scale

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.

See AI-powered process automation in action

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FAQs

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