These trends outline the convergence of cutting-edge technologies such as AI, machine learning, and real-time data platforms with process optimisation to redefine enterprise operations.
“Process intelligence is essential to any enterprise AI strategy because it gives AI the context it needs to understand how businesses operate,” he says.
“Processes make the world go round. When processes work, everything works better as companies become more productive, more efficient, and more sustainable. They’re able to collaborate effectively internally and with other companies, make the best decisions, and accelerate progress with minimal effort and waste.
“And the planet thrives as we cut down waste, emissions and drive innovation in pursuit of long-term sustainable growth.”
The top 10 trends for Process Intelligence in 2025 are:
1. Process Intelligence is the foundation of all Enterprise AI: Foundational AI models are powerful, but they lack the contextual understanding of business processes, workflows, and operational metrics. Process Intelligence fills this gap by providing a living digital twin of operations, enabling AI to deliver actionable insights and automations tailored to each organisation's unique needs. By doing so, it transforms AI from a generic capability into a strategic asset.
2. Collaborate Networks will breakdown old barriers and redefine industries: Traditional methods of sharing and managing data across value chains are slow and error prone. Collaborative networks provide a shared platform for data and insights, enabling faster, more informed decisions. Businesses will increasingly adopt collaborative process networks to enhance transparency and optimise cross-company operations.
3. Digital Twins will evolve into Process Intelligence Platforms: Digital twins will evolve into dynamic, intelligence-driven platforms that provide a real-time, end-to-end view of enterprise operations, powered by AI and enriched business context. The shift from static digital models to active, living process twins ensures enterprises can adapt swiftly to market changes, reduce operational silos, and drive continuous improvements. They are pivotal for making AI strategies actionable at scale.
4. Process Intelligence will unlock new levels of predictive analytics: The fusion of Process Intelligence with artificial intelligence (AI) and machine learning (ML) is driving the development of predictive analytics within enterprises and enabling them to move from reactive to proactive operations. Predictive analytics powered by PI allows organisations to foresee disruptions, adjust in real-time, and optimise outcomes based on data-driven foresight. By combining historical process data with AI-powered forecasting, companies can predict bottlenecks, forecast demand, and proactively address inefficiencies.
5. Command Centre platforms will eliminate silos and change how enterprise teams collaborate: Command Centre platforms, leveraging unified data systems are poised to be the cornerstone of collaboration in the next year, particularly within supply chain operations. Ensuring supply chain teams have unified and contextualised data from across an enterprise will allow those teams to align around shared metrics and data sources, fostering more effective collaboration both across different functions as well as from the executive and operational levels.
6. Agentic AI will redefine efficiency through autonomous process optimisation: The future of enterprise AI is moving toward autonomous, agent-based systems that can independently execute tasks and optimise workflows in real time. As these AI agents continue to evolve, they are transforming business operations by reducing manual interventions, accelerating responsiveness, and unlocking new levels of efficiency across the organisation. Businesses should invest in adaptive AI technologies, identify key processes for automation and build governance structures to establish clear guidelines for AI autonomy.
7. Process Intelligence will emerge as the critical foundation for all Enterprise decision making: Traditional process mining has evolved into Process Intelligence, which includes object-centric event data, powerful object-centric process mining capabilities, business context defining key-performance indicators and normative process models, and predictive and generative AI capabilities. This makes it possible to create a "living digital twin" of operations, integrating data across systems, processes, and contexts.
8. Transformation at scale will require agile process optimisation: Agile: iterative approaches to process optimisation will become the norm for large-scale transformation initiatives. Traditional, one-off optimisation efforts are no longer sufficient in today’s dynamic business environment. Companies need to continuously adapt their processes to new technologies, market conditions, and operational goals. Process intelligence empowers organisations to do this by providing real-time insights into inefficiencies and opportunities.
9. New compliance frameworks: AI in the spotlight: Given how global regulations on Artificial Intelligence, such as the EU AII Act, are unfolding, it’s clear that companies face heightened expectations for managing and protecting user data.
10. Integrated and Real-time regulatory compliance tracking will become essential for ESG: As governments and regulatory bodies intensify their focus on sustainability, companies will face stricter reporting requirements and compliance standards in 2025. The increased pressure will require organisations to stay agile in responding to frequent regulatory changes, and to understand and leverage synergies between various regulatory requirements. Companies will need to establish systems that can monitor, adapt, and report on sustainability efforts in real time to ensure compliance and avoid potentially costly penalties - at the speed of business operations.
