Stop Wasting AI Spend: Start with Process Intelligence

Despite massive investments, 40% of AI budgets are wasted due to inefficient processes . The problem isn’t the technology itself—it’s the underlying activities to which it’s applied. AI is a powerful enabler, but without a clear understanding of your current operations, even the flashiest solutions can’t overcome suboptimal workflows.

At the core of every successful AI-driven transformation lies one often-overlooked element that determines success or failure: process intelligence (PI).

Michael Porter highlighted this challenge in his 1985 book Competitive Advantage: “A systematic way of examining all activities a firm performs and how they interact is necessary for analyzing the source of competitive advantage.” This insight remains as relevant today as it was then. Without a deep understanding of their processes and the root causes of problems, businesses can’t expect AI to fix what’s broken.

Barriers preventing AI at scale

Most organizations today focus their AI investments on personal productivity, deploying AI chatbots and copilots that have only a marginal impact on critical business outcomes. To unlock the full potential of AI, leading organizations are shifting their investments toward automating and scaling operations. This approach drives faster turnarounds, expands capacity, outpaces competitors, and boosts the bottom line

However, achieving this is challenging in today’s complex technology ecosystems. Modern organizations juggle over 1,000 applications to support operations, but instead of enhancing efficiency, this vast array of tools often creates chaos. Employees switch between applications more than 1,200 times a day on average, disrupting focus, fragmenting workflows, and scattering valuable data across siloed systems.

For AI initiatives—which depend on seamless data access and streamlined operations—this fragmented environment creates significant roadblocks. When silos and technological disarray dominate, AI projects stall, failing to deliver the strategic insights and automation they promise. Addressing these inefficiencies with a unified, integrated approach is essential to drive productivity and ensure AI success.

Disorganized, siloed, and inaccessible data further challenge organizations striving for clarity and efficiency. Without data-driven systems to uncover workflows and analyze key processes, businesses are left operating in the dark, relying on intuition instead of actionable insights. This lack of transparency undermines strategic decision-making, leaving organizations vulnerable to inefficiencies and missed opportunities.

Beyond clean data, AI—especially emerging agentic technologies—requires cohesive and accurate context to build reliable operational blueprints. When fed incomplete or fragmented data, these systems falter, delivering limited analysis and ineffective automation. To overcome these challenges, organizations must prioritize robust process intelligence and operational excellence, laying a clear foundation for immediate improvements and long-term AI success.

Success criteria for AI ROI

Achieving a return on AI investments isn’t magic. Success is a methodical process that requires focus, strategy, and precision. To unlock AI’s transformative value, businesses must prioritize three critical outcomes enabled by process intelligence: identifying opportunities, accelerating improvements, and monitoring results.

1. Identify opportunities and predict impact
   AI delivers the greatest value when applied to specific inefficiencies. This starts with a deep understanding of existing workflows and processes. By leveraging process intelligence tools, businesses can analyze operations, pinpoint pain points, and uncover areas for improvement. These insights not only forecast the potential impact of AI but also help prioritize efforts that yield the highest value. Skipping this foundational step risks misaligned initiatives, wasted resources, and missed opportunities.
2. Accelerate improvements
   Once opportunities are identified, the focus shifts to redesigning processes and building automation using clean, reliable data and trusted AI systems. The synergy between process precision and AI’s computational power enables rapid implementation and measurable results. Whether it’s streamlining operations, cutting costs, or enhancing customer experiences, this step ensures AI becomes a practical driver of tangible outcomes—not just a theoretical tool.
3. Monitor and drive results
   The journey doesn’t end with implementation. Continuous monitoring ensures AI delivers sustained value. Real-time tracking allows businesses to maintain productivity, adapt to changes, and address issues proactively. This approach safeguards the initial investment. By consistently measuring performance and making data-driven adjustments, organizations can keep AI initiatives aligned with goals and evolving needs.

In summary, achieving ROI from AI requires a deliberate focus on identifying opportunities with process intelligence, accelerating improvements, and monitoring results to unlock AI’s full potential and drive meaningful transformation.

Context is king: the five tenets of Process AI

You’ve likely heard the phrase, “No AI without PI.” But what does it mean? Simply put, you can’t unlock AI’s full potential without first addressing the core processes that drive business workflows. As May Habib, CEO of Writer.com, aptly put it: “You get transformational results from AI when you understand the processes driving the big core workflows that underpin your business.”

 

 

To put this concept into practice, you must focus on the five critical tenets of Process AI:

1. Process discovery:
   Automatically map workflows using event logs and system data to uncover inefficiencies and redundancies. This provides a clear view of current operations, laying the foundation for meaningful improvements.
2. Process analytics:
   Turn raw data into actionable insights with advanced metrics like flow efficiency and cycle times. Go beyond surface-level KPIs to pinpoint priority areas for impactful change.
3. Process monitoring:
   TStay proactive with real-time tracking and alerts. Monitor workflows to ensure compliance, prevent issues, and maintain smooth operations.
4. Process prediction:
   Leverage AI-driven insights to forecast trends, identify risks, and preempt bottlenecks. This enables faster, smarter decisions for sustained competitive advantage.
5. Process simulation:
   Experiment with new ideas in a digital twin of your workflows. Test changes risk-free to refine processes and ensure seamless implementation.

Together, these five capabilities form the ultimate toolkit for delivering process intelligence. When these capabilities work in harmony, businesses maximize efficiency, minimize risks, and drive long-term success.

Avoiding “pilot purgatory” and cracking the code

Effectively scaling AI requires more than incremental implementations—it demands a deep understanding of processes to ensure consistency and adaptability across the enterprise. Establishing robust process frameworks is essential for achieving clear, measurable outcomes.

Efficient processes allow organizations to confidently demonstrate the business value of AI, avoiding the all-too-common trap of "pilot purgatory," where 87% of AI projects stall . Agile processes also enhance operational resilience, enabling enterprises to overcome challenges while continuing to expand their AI capabilities.

Optimized workflows drive sustainable innovation by freeing employees to focus on higher-value tasks that foster creativity and adaptability in fast-changing markets. Yet, many organizations fall into the trap of prioritizing technology-first solutions, neglecting the critical need for operational clarity. Without it, no AI system can deliver the efficiency, insights, or competitive edge businesses seek.

For organizations aiming to scale AI successfully, understanding and refining processes is an urgent priority.

Start setting yourself up for success

The journey to AI transformation starts with a simple truth: Tomorrow's success depends on understanding today’s processes. Process intelligence is the foundational framework that enables AI to deliver the transformative results businesses aspire to achieve.

Organizations looking to eliminate inefficiencies and achieve meaningful results must start the process-investment conversation now. Begin by assessing your current workflows and adopting tools that help visualize, optimize, and monitor operations with a process-first mindset.

Turn inefficiencies into opportunities. Use process intelligence to lay the groundwork for AI success today to secure tomorrow’s competitive edge.