Forrester defines digital process automation software as: Platforms that develop process applications with advanced programming principles with modeling, orchestration, dynamic case management, and AI-led support. Market definition Inline definition Customers use DPA software solutions to visually define, continuously improve, and manage process applications that connect people and system endpoints.

Predictive analytics to guide state transition has helped case management in areas such as predictive maintenance, government service, and investigations (see Figure 11). Maintain: Dynamic Case Management This graphic shows the maturity, business value, use cases, and sample vendors for dynamic case management and provides a definition, maturity rationale, and business value rationale for this technology. It has an associated spreadsheet that includes all the information presented.

Forrester defines digital process automation as: Platforms that develop process applications with low-code and advanced programming principles with modeling, orchestration, dynamic case management, and AI-led support. Customers use DPA solutions to visually define, continuously improve, and manage process applications that connect people and system endpoints.

However, the solution lags in providing queues and case management; visual link analysis trails in its use of AI agents; and data sources can’t be added to case screens. Case management uses a digital worker that provides investigation recommendations, but it isn’t an interactive copilot. Customer feedback. Customers love how quickly Nasdaq Verafin updates its solution. They would like better built-in reporting. Forrester’s take.

Its superior case management orchestrates workflows across channels and across the enterprise. Self-service resolves less complex inquiries, while complex cases are managed through the desktop, displaying journey, context, and guidance. Real-time AI coaching, knowledge, and next best actions adapt dynamically. Pega Blueprint accelerates workflow design by accepting process inputs via natural language, BPMN diagrams, documentation, etc.

For customer service, use cases include autonomous case management (customer-facing) to derive intent, classify the case, resolve the case, and automate follow-up; work order generation (customer-facing) to derive intent, classify the case, run diagnostics, create a work order, and schedule and dispatch a field worker; sentiment management (internal) that identifies, addresses, and escalates customer dissatisfaction based on analysis of sentiment; appointment management (customer-facing) that manages

Public Sector Cloud Portfolio (including OCI, SaaS, and Industry Applications for CRM, Case Management, and Regulatory Solutions) Salesforce. Agentforce Public Sector SAP. Public Sector Business Suite (SAP S/4HANA and SAP CRM/CX Portfolio for Government Missions) ServiceNow. Public Sector Digital Solutions TechnologyOne. OneGovernment SaaS (including Digital Experience Platform and Municipal Finance & Asset Management Solutions) Tyler Technologies.

Axon Ivy offers somewhat limited out-of-the-box case management packages and uses its own Case Map notation as an alternative to CMMN. It lacks native support for business rules but integrates with Drools. AI agent development lags. Axon Ivy is a platform for building a variety of process use cases with strong low-code features. Customer feedback. References express satisfaction with the vendor and product, particularly its strong orchestration capabilities.

In a later case management phase (additional triage), AI agent copilots in case management can collect and arrange additional comprehensive evidence as well as generate narratives of fraudster activities in or across transactions. AI agents observing, detecting, and remediating deficiencies in risk-scoring models.

APO Deal Sizes Also Vary APO platforms will be critical for running key enterprise processes: Long-running workflows with complex rules, such as case management, will be a prime target. APO platforms will build AI agents and model-driven automations with strong action and orchestration, offering more business value than general-purpose AI assistants.