Gartner defines the accounts payable application market as cloud-based solutions that use intelligent automation to empower finance teams to independently manage end-to-end invoice processing, execute payments, and maintain master data across one or more ERP systems. These applications deliver configurable workflows, real-time analytics, and integration with procurement and treasury systems, creating a unified and scalable accounts payable operation.
Compliance monitoring solutions leverage capabilities to detect anomalies in processes or employee behavior. These solutions enhance misconduct reporting channels by providing chief compliance and ethics officers (CCEOs) with ways to detect misconduct and take action on it, in near real time. They help organizations meet regulatory requirements by enabling real-time detection of violations, conducting risk assessments, and managing incidents from identification to resolution. These technology resources also support efforts to automate compliance workflows, prioritize responses based on severity and impact, and potentially take advantage of regulatory self-disclosure incentives in a timely way. Tailored dashboards offer oversight for stakeholders, ensuring transparency and accountability. These solutions are typically used by compliance officers, risk managers, auditors, and legal teams in industries like finance, healthcare, government, energy, and tech to ensure adherence to regulations, internal policies, and industry standards.
A DTO is a dynamic software model that relies on operational and contextual data to understand how an organization operationalizes its business model, connects with its current state, responds to changes, deploys resources, simulates future states and delivers customer value. A DTO platform is a technology platform that supports the creation, management and operationalization of a DTO.
Gartner defines process intelligence platforms as solutions that combine development and runtime software tools to mine, analyze, model, design, and monitor processes. They offer capabilities such as process and task mining, process modeling and designing, advanced process analysis, alerting, SLA and threshold-based tracking, anomaly detection, and interactive decision support by providing data about current processes and their conditions. AI and process automation opportunity discovery: By analyzing task and process-level data, the platform can pinpoint bottlenecks, delays, governance issues, compliance gaps, and manual handoffs that are ideal candidates for task or process automation and AI augmentation. It can also identify redundant steps and resource constraints that contribute to process inefficiencies. This use case helps discover and design to-be workflows by providing prioritized opportunity lists with estimated ROI, enabling enterprises to accelerate automation initiatives and maximize operational efficiency. Furthermore, this use case extends to providing a business operations context to ground AI agents, ensuring alignment with organizational goals and compliance requirements. Process improvement and optimization: This use case is essential for enterprises seeking to improve and optimize their operations by discovering, designing, modeling, and analyzing business processes. This enables end users to collaboratively redesign workflows (such as customer journeys, service delivery, or internal operations), leverage simulation capabilities to test future-state scenarios, and evaluate the impact of proposed changes. It also needs a centralized repository for storing process models, best practices, and improvement initiatives, enabling easy access, version control, and knowledge sharing across teams. Finally, through predictive and prescriptive analytics, users can identify optimal process improvements, anticipate outcomes, and make data-driven decisions that align with strategic objectives. Governance, risk, and compliance: Monitoring of process executions against regulatory requirements and internal policies ensures visibility into compliance. Automated audits, conformance checks, and risk scoring highlight policy violations and control weaknesses, empowering stakeholders to mitigate risks, enforce governance standards, and maintain audit trails. Bridging strategy to execution for digital transformation: This use case bridges the gap between strategic planning and daily operations by enabling data-driven actions. For example, when leadership sets a target customer satisfaction score, process intelligence tracks metrics such as response times and handoff delays, alerting teams to corrective steps and enabling process redesign where needed. If market data indicates a surge in demand, the platform simulates impacts across manufacturing and logistics, recommends adjustments, and updates roadmaps accordingly. By linking objectives, such as cost-to-serve reductions or quality improvements to key performance indicators (KPIs) and actionable triggers, organizations can ensure that every decision directly supports customer outcomes. Operations intelligence: This use case leverages dashboards, SLA tracking, and anomaly detection to continuously monitor process performance. It alerts to surface imminent issues, such as delays or exceptions, while historical and predictive analytics guide rapid root-cause analysis.
Gartner defines task mining as a combination of techniques to infer useful information from low-level event data available in UI logs derived from the underlying operating system or through observing application UI interactions. This data comes from individual users or a cohort in the form of screen recordings, keystrokes, mouse clicks and data entries. Additional mining capabilities interpret the data by applying natural language processing (NLP), optical character recognition (OCR) and artificial intelligence (AI) techniques to correlate data in different ways. Task mining helps an enterprise identify inefficiencies and automation opportunities, increase worker productivity, and enhance the employee experience.