In the rush to embrace artificial intelligence (AI), enterprises across industries have encountered a harsh reality: transformation takes more than technology. Two years ago, generative AI captured the imagination of business and technology leaders alike, promising to revolutionize operations and decision-making. Yet today, many organizations find themselves with pilot projects that are failing to scale, and AI investments that are falling short of expectations.
The fundamental issue? AI lacks the operational context to deliver on its potential. Even the most sophisticated models struggle when confronted with the messy, interconnected realities of enterprise processes. This is where Process Intelligence has emerged as a game-changer, turning AI’s potential into strategic impact.
From AI Hype to Meaningful Progress
The past two years have underscored the limitations of deploying AI without a foundational understanding of business operations. Enterprises of all sizes and industries have eagerly adopted large language models (LLMs) and other AI technologies, driven by their impressive capabilities. But without an accurate picture of how their businesses actually function, these efforts often hit roadblocks.
Consider invoice processing. Leaders might imagine a linear workflow—invoice arrives, approval follows, payment is issued. In reality, this process often involves dozens of steps, detours, and manual interventions. Applying AI to such a chaotic environment without clear visibility is like attempting to automate a moving target.
Process Intelligence changes the equation. By mapping workflows in detail, it provides AI with the context needed to operate effectively. It doesn’t just improve AI’s ability to execute tasks, it ensures those tasks align with the broader goals of the business.
The "Digital Twin" Revolution
Process Intelligence acts as the connective tissue of the modern enterprise. It creates a “digital twin” of an organization, offering a real-time view of processes, their interdependencies, and inefficiencies. These models need to be system-agnostic to ensure they can integrate seamlessly with diverse enterprise ecosystems, providing a holistic view across all platforms and tools, including their intersections.
This foundation enables AI to:
- Automate routine tasks: AI agents can take over repetitive decisions, such as flagging invoices for approval, with accuracy and speed.
- Enhance human decision-making: With a human-in-the-loop approach, AI provides data-driven recommendations, learning from user feedback to improve continuously.
- Drive proactive improvements: By analyzing how processes flow, AI identifies opportunities for optimization before problems arise.
The Changing Relationship Between AI and Users
As AI becomes more integrated into the workplace, its interface with users has transformed. Natural language interfaces now allow employees to interact with systems using plain language, democratizing access to AI insights. However, without Process Intelligence, these interfaces risk delivering generic or irrelevant results.
Process Intelligence grounds AI in the specific realities of a business. It ensures that LLMs and other AI tools are fed with accurate, context-rich data, enabling them to provide actionable insights that resonate across departments and roles. This alignment empowers AI to act not just as a tool but as a strategic advisor.
Scaling Efficiency and Sustainability
In a world of geopolitical and economic uncertainty, talent scarcity, and escalating demands for efficiency, the stakes for businesses have never been higher. Process Intelligence offers a path to navigate these challenges, delivering results that go beyond productivity. Some real-world examples include:
- Reducing case backlog by 25% in the Texas Juvenile Justice system, enabling faster resolutions and better outcomes for families.
- Saving The State of Oklahoma $60M in taxpayer funds through optimized procurement processes in public sector organizations.
- Improving Campari Group’s order-to-cash efficiency by 20%, accelerating revenue realization for global businesses.
- Streamlining Ingka Group cash flow processes across 30 countries, enhancing financial operations for Ingka Group.
- Achieving 50% faster order fulfillment for Cosentino through AI-powered business transformation, improving customer satisfaction and operational agility.
Furthermore, by aligning people, processes, and technology, Process Intelligence not only drives efficiency but also advances sustainability goals. Reduced waste and emissions, coupled with smarter resource allocation, position organizations to thrive in a fast-changing world.
Building a World Where Processes Work
The lessons of the past two years are clear: AI alone cannot solve the complexities of enterprise operations. To realize its promise, AI must be underpinned by a deep understanding of how businesses work. Process Intelligence provides that foundation, transforming AI from a hopeful experiment into a powerful engine for innovation.