Explore how Marlon Dumas, Apromore co-founder & CPO, bridges process intelligence and AI to drive smarter, compliant, and end-to-end automation.
Marlon, can you share a bit about your professional background and your journey to co-founding Apromore, where you now serve as Chief Product Officer?
My journey to co-founding Apromore began in 2009 while leading research on process mining at Queensland University of Technology. Alongside my former PhD student and collaborator, Marcello La Rosa, we developed an open-source platform named ‘AProMoRe’ that quickly gained global traction with support from Prof. Wil van der Aalst (often called the Godfather of Process Mining) and contributions from more than 15 institutions. As demand grew for scalable, business-friendly process intelligence tools, we saw a clear opportunity. Backed by The University of Melbourne, we spun out as a company in 2019 after securing our first customers. Marcello and I pushed the pause button on our academic careers and built a team to rebuild Apromore from the ground up as a cloud-native SaaS product. As Chief Product Officer, I now lead our product vision, bringing together research, innovation, and enterprise needs to help organizations unlock value through process intelligence.
How does process intelligence act as a grounding mechanism to ensure autonomous agents operate effectively within complex workflows?
Process intelligence provides the contextual backbone that autonomous agents need to act with precision. Without understanding the “as-is” and “to-be” processes, AI can just as easily reinforce inefficiencies, propagate risks or even break processes.
Apromore, for example, integrates process mining with AI to deliver predictive and prescriptive insights that inform agents about likely outcomes and compliance risks—enabling truly adaptive, goal-aligned automation across the enterprise. It ensures that every AI-triggered action is backed by accurate, contextual data and aligned with business rules, risk controls and compliance obligations.
What risks do organizations face when deploying AI without integrating process intelligence, and how can these be mitigated?
Deploying AI in isolation often results in blind automation, where tasks are often executed efficiently but not necessarily effectively. This can lead to increased compliance violations, SLA breaches, or bottlenecks simply being shifted downstream. The risks include regulatory penalties, reputational damage, and operational disruption. Mitigation lies in embedding process intelligence into every stage of AI deployment: from discovery and design to monitoring and governance.
Think of a loan origination process: an AI agent may automate approvals based on predefined rules, but without understanding upstream dependencies or downstream risks, it might approve an incomplete or non-compliant application. With process intelligence, however, the agent sees the full picture. It can assess the sequence and conditions of every step, recognize violations in real-time and trigger escalations or corrective actions. Platforms like Apromore provide the kind of embedded operational awareness, auditability, and simulation capabilities required to deploy AI responsibly and sustainably.
As AI matures, how should leaders evolve their automation strategies and enterprise architectures to maximize business value?
It is very tempting to deploy AI to automate individual tasks. This leads to quick wins. However, to deliver sustainable long-term value, leaders must channel AI into end-to-end process optimization and orchestration. This involves embedding AI within a data-driven enterprise architecture—where process mining, simulation, and monitoring feed into intelligent orchestration layers. Apromore enables this shift through predictive and prescriptive capabilities that inform both tactical and operational decisions. Leaders should focus on modular architectures that support adaptability and integrate process intelligence as a core capability to align AI efforts with strategic business outcomes.
In what ways can process intelligence enhance operational resilience amid supply chain shocks, regulatory changes, and talent shortages?
Process intelligence acts as an early warning and response system. By continuously monitoring key processes, Apromore helps organizations detect deviations, simulate “what-if” scenarios, and assess control effectiveness in real time. For example, in a supply chain disruption, predictive insights can flag vulnerable subprocesses while simulations help leaders assess alternative routes or resource allocations. In times of talent shortages, it can identify automation opportunities or skill mismatches. Ultimately, process intelligence fosters agility and informed decision-making under pressure.
Why is optimizing end-to-end processes more impactful than simply automating individual tasks, and how can organizations shift their focus accordingly?
Task-level automation delivers incremental gains but often misses systemic inefficiencies. True transformation happens when organizations optimize processes from start to finish—eliminating rework, ensuring compliance, and aligning outcomes with KPIs. Apromore helps organizations achieve this by revealing the complete process landscape, including bottlenecks, deviations, and hidden dependencies. By making these insights accessible through no-code tools and intuitive dashboards, we empower business teams to lead optimization initiatives—not just IT.
How does process intelligence enable real-time governance, continuous auditing, and compliance monitoring at scale?
Apromore’s Compliance Center illustrates how real-time governance is possible. It connects directly to live event data, applying compliance rules continuously to detect violations as they happen. With features like key control testing, near real-time dashboards, and predictive alerts, organizations gain the ability to audit continuously rather than periodically. This proactive posture not only reduces risk but allows compliance teams to shift from reactive firefighting to strategic oversight.
What role does data-driven governance supported by process intelligence play in improving risk management and organizational transparency?
Data-driven governance ensures that decisions are based on factual process data rather than assumptions. Apromore links controls directly to processes, enabling transparent evaluation of rule effectiveness, control gaps, and compliance health. It also makes it easier to trace decision-making logic for regulatory purposes. This level of transparency builds trust across internal stakeholders and regulators while enabling risk teams to focus on systemic issues rather than isolated incidents.
Looking forward, how can organizations best prepare to leverage process intelligence as a strategic lever alongside autonomous AI over the next several years?
To fully realize the synergy between process intelligence and autonomous AI, organizations must invest in foundational capabilities now—such as automated process discovery, simulation, and KPI-based monitoring. Apromore’s roadmap reflects this vision, advancing toward a future where AI doesn’t just react, but anticipates and optimizes based on context. Leaders should develop a Center of Excellence to scale process intelligence, ensure data quality pipelines, and foster collaboration between business, risk, and technology teams.
What key advice would you give to organizations just beginning to integrate process intelligence with autonomous AI to ensure successful and sustainable outcomes?
Start with clarity on the problem you’re solving. Choose a high-impact process and use process intelligence to understand its dynamics before layering in AI. Establish cross-functional ownership early and ensure that business, IT, and compliance champions are aligned internally. Use platforms like Apromore to pilot predictive monitoring or compliance automation, then scale with confidence. The key is to treat process intelligence not as an afterthought to AI, but as a prerequisite for safe, scalable, and strategic automation. AI agents without process intelligence are automation without understanding — fast, but blind. Success will go to those who pair the speed and efficiency that AI agents bring with the transparency, effectiveness and control that process intelligence adds.
Marlon Dumas
Chief Product Officer & Co-Founder of Apromore
Prof. Marlon Dumas is Chief Product Officer & Co-Founder of Apromore and professor of Information Systems at the University of Tartu. For the past two decades, he’s delivered business process management and process mining training and consultancy to 50+ organizations worldwide. As a research team leader, he executed R&D projects funded by the European Research Council, the Australian Research Council, the US Army Research Lab, and multinational companies including SAP, Microsoft, and Swedbank. His research has led to 250+ scientific articles, 10 US and EU patents, and a popular textbook on business process management used in 400+ universities.