Enabling ‘smarter’ enterprises with process intelligence and GenAI

Chief technology officers (CTOs) and chief innovation officers (CIOs) face a new reality: traditional process optimization—relying on historical data and rigid templates—no longer aligns to today’s fast-paced, dynamic business environment. Processes were analyzed post-mortem, hindering real-time decision-making or proactive improvements.

But the game has changed. The integration of process intelligence and GenAI is empowering organizations to act in the moment—simulating scenarios, dynamically creating new workflows, and making instant, data-driven decisions. For leaders striving to drive agility, efficiency, and growth and become next-gen process leaders, this transformation is not optional—it’s essential.

From inefficiencies to agility: Real-world industry specific examples of GenAI and process intelligence at work

A US-based retail giant was grappling with inefficiencies in supply chain management. Historically, addressing such inefficiencies required lengthy manual analysis and generic optimization templates. With the combined power of process intelligence and GenAI, the company adjusted inventory replenishment workflows to address real-time demand fluctuations, reducing supply chain disruptions by 40% and saving millions in lost revenue. This showed CTOs and CIOs how leveraging real-time insights and adaptive decision-making can drive operational agility and yield measurable business impacts.

In operational optimization, HFS observed that the true value of GenAI is in amplifying agility within defined processes, making them faster and more adaptive without compromising stability. GenAI’s ability to refine and augment processes supports the development of process-optimized environments, further driving the adoption of process intelligence.

Exhibit 1: The real innovation with GenAI is in enhancing processes with precision and agility

Source: HFS Research, 2025

A few examples of how this combination drives enterprise success:

1. From procurement to precision—accelerating enterprise processes: A global corporation used process intelligence tools (with a process mining partner) to identify bottlenecks in procurement processes and paired it with an LLM-powered GenAI tool along with other in-built automation tools. The GenAI system, trained on historical contracts and compliance data, automated contract creation, flagged supply chain risks, and recommended tailored vendor terms. This combination reduced procurement timelines from weeks to days, improved contract compliance globally, and boosted profit margins by 15% through better vendor terms and faster execution.
2. Transforming healthcare operations: A healthcare organization used process intelligence to identify workflow bottlenecks and integrated GenAI solutions, including LLM-powered platforms, to optimize resource allocation and streamline billing dynamically. This reduced patient wait times, halved billing cycles, increased patient satisfaction by 25%, and improved resource utilization. In healthcare, the ability to autonomously predict and resolve inefficiencies can be transformative with the increase in adoption.

Real-world wins—the multi-industry potential of GenAI and process intelligence Process intelligence and GenAI synergies aren’t confined to specific sectors. Their adaptability helps deliver results across industries, as demonstrated in the following examples:

1. Manufacturing—optimizing the supply chain: A US-based apparel manufacturer used process intelligence to identify supply chain inefficiencies and integrated GenAI to automate replenishment planning and logistics. This increased truck utilization from 32% to 99%, reduced inventory days from 51 to 17, and cut supply chain disruptions by 40%, saving millions in lost revenue.
2. Finance—combatting financial crimes: A leading bank leveraged process intelligence to identify inefficiencies in fraud detection and used GenAI to automate investigations, flagging anomalies and reducing false positives by 70%. This improved fraud detection precision, reduced financial risks, and enhanced compliance with real-time insights.

These examples show how the combination goes beyond traditional approaches, delivering real-time adaptability and measurable impact. As adoption grows, enterprises will increasingly rely on both technologies to fuel their digital transformations, setting benchmarks for agility, scalability, and operational excellence and redefining what it means to operate in a fast-paced, ever-evolving global market.

The key shift—real-time, intelligent optimization

The convergence of process intelligence and GenAI is revolutionizing how enterprises operate (see Exhibit 2), enabling intelligent systems to automate tasks, learn, adapt, and evolve with minimal human intervention. By leveraging real-time insights and decision-making capabilities, businesses can go beyond operational efficiency to create agile, self-sustaining systems that dynamically respond to shifting market demands and disruptions.

Some key expected benefits for enterprises:

• Continuous adaptation: Analyze workflows in real time, adapting to changes and minimizing downtime
• Operational agility: Accelerate time-to-market and keep businesses competitive in dynamic environments
• Scalability: Easily scale across industries, optimize logistics, enable fraud detection, etc.
• Resource efficiency: Reduce waste and improve utilization, resulting in faster billing and better care
• Future-proofing: Anticipate and resolve inefficiencies, ensuring resilience and long-term stability

Exhibit 2: The evolution from static automation to intelligent optimization

Source: HFS Research, 2025

Overcoming barriers to scaling intelligent systems

While the synergy promises transformation, the implementation comes with challenges. Recognizing and mitigating these pitfalls is critical to achieving sustainable success.

1. Data silos and quality issues: Process intelligence and GenAI rely on high-quality, unified data to function effectively. However, many organizations face challenges with siloed, incomplete, or inconsistent datasets. Investing in robust data governance frameworks and integrating disparate data sources are essential for better insights and outcomes.
2. Ethical and regulatory concerns: Industries such as healthcare and finance face strict compliance mandates, making transparency in automated decision-making imperative. Implementing AI accountability frameworks across organizations will ensure better compliance and build stakeholder trust.
3. Change management and workforce resistance: Automation often triggers employee resistance due to fears of redundancy or less familiarity with new technologies. Successful implementation requires a structured change management approach, including workforce training and clear communication on how these technologies will augment rather than replace human roles.
4. Scalability and adaptability: Scaling GenAI solutions across global enterprises with diverse workflows can be complex. These enterprises must build modular, flexible systems to enable tailored solutions without extensive reconfiguration.

The road ahead—self-healing systems and beyond

In enterprise environments powered by process intelligence and GenAI, self-healing systems are critical for proactively monitoring workflows, infrastructure, and operational health in real time. In supply chains, these systems predict disruptions caused by supplier constraints, dynamically reroute logistics, adjust inventory levels, and notify stakeholders—all without manual intervention. Similarly, in IT operations, they detect anomalies, resolve performance bottlenecks, and optimize system functionality to ensure uninterrupted business operations.

These enterprise-focused systems can integrate predictive intelligence, real-time learning, and proactive resolution into core processes while adapting to changing business conditions, helping organizations maintain resilience and agility in dynamic environments. With self-healing capabilities, enterprises can create adaptive ecosystems that scale seamlessly, driving efficiency, operational excellence, and competitive advantage across industries.

The Bottom Line: Integrating process intelligence and GenAI isn’t just a step forward for CTOs and CIOs—it’s the blueprint for agile, intelligent, and self-sustaining enterprises poised to thrive.

Enterprise leaders must embrace this synergy to set the standard for operational excellence in a world that demands real-time adaptability and innovation. This powerful combination catalyzes innovation and transformation, enabling them to redefine operational excellence and gain a competitive edge.