How to leverage process intelligence to holistically optimize processes in the Intelligent Age

Processes are the fabric of our world. When processes work, everything works. People are more fulfilled and less frustrated. Companies become more productive, more efficient and more sustainable. And, we can reduce waste and drive innovation, benefiting the planet. But, making processes work is easier said than done, especially in the 'Intelligent Age,' when many processes run across organizational boundaries and are increasingly disrupted by AI.

To make processes work, we need AI powered by process intelligence, which provides a shared understanding of how our businesses and organizations run and how to make them run better. We also need to extend the power of process intelligence by connecting people, teams and even companies, enabling better collaboration.

AI adoption has surged in recent years. Businesses around the world and across industries are turning to the technology to improve productivity, drive innovation, reduce costs, increase revenue, enhance customer relationships and achieve sustainable growth. According to the McKinsey Global Survey on AI, AI adoption has risen from 50% in 2020 to 72% in early 2024. Generative AI saw an even more dramatic jump, going from 33% adoption in 2023 to 65% adoption in 2024. Now, AI agents, with their ability to autonomously reason and automate decisions, are receiving a lot of attention. Forrester referred to agents as “perhaps the most exciting development” on its 2024 list of top emerging technologies.

Yet, despite its rapid growth in popularity, many businesses continue to face challenges in extracting meaningful value from their AI investments. Boston Consulting Group (BCG) found that “74% of companies struggle to achieve and scale value” with AI. In the Q2 edition of Deloitte’s 2024 The State of Generative AI in the Enterprise series, researchers reported that only 18%–36% of 1,900+ business leaders said their generative AI initiatives were delivering the expected benefits to a “large” or “very large” extent. In the Q3 edition of the series, Deloitte reported that 68% of respondents have “moved 30% or fewer of their Generative AI experiments fully into production.”

There’s clearly a gap between AI’s promise and its ability to deliver tangible results for the enterprise. Process intelligence helps close this gap. To reach its full potential, AI needs to speak the language of business; it needs to understand how work flows; it needs process intelligence.

Consumer AI works because it has extensive data and contextual references, like Wikipedia, to make sense of it. In contrast, enterprise systems lack such a unifying framework despite having abundant raw data. Process intelligence bridges this gap by providing the context necessary for AI to understand the business (i.e., a company’s policies, business rules, KPI definitions roles and responsibilities). For example, foundational large language models are good at understanding natural languages, but when fueled with business context, they can also understand business process details, like how to determine a company’s 'excess stock' KPI. Equipped with this understanding, AI agents can drive the right actions and outcomes.

Leading companies are already using AI agents, assistants and copilots powered by process intelligence to drive business transformation and generate true value, for example:

• Cosentino – This manufacturer of design and architectural surfaces uses an AI assistant to handle blocked sales orders, enabling it to process up to five times more orders without additional risk.

• European packaging company – This business has a co-pilot that shows plant technicians the spare part levels at surrounding facilities, letting it use stock transfers, rather than ordering from suppliers if equipment breaks down.

• Global consumer goods company – This company uses an AI agent to extract payment terms from its contracts and compares the information to the terms in its master data, PO and invoices. The agent then recommends actions to the company’s accounts payable clerks to address inconsistencies.

• Global vehicle manufacturer – This firm automatically generates email replies to supplier inquiries with an AI agent.

Given these real-world results, it’s no wonder that a 2024 report from Accenture showed that organizations with fully modernized, AI-led processes achieved 2.5x higher revenue growth and 2.4x greater productivity than their peers.

The power of process intelligence goes beyond a single team or a single company. Business collaboration networks create a new level of shared process transparency beyond the boundaries of a single organization, so that every process, within and across companies, can be optimized. This advancement is particularly beneficial in supply chain operations, where effective coordination between suppliers and customers is essential for a seamless end-to-end process.

Traditional data exchange technologies, like electronic data interchange, APIs and email, primarily focus on transactional data. In contrast, collaboration networks deliver continuous fresh process insights, enabling businesses to collaboratively identify and fix cross-company process breakdowns, streamline operations and minimize risk.

Conrad Electronic, for example, a European B2B sourcing platform for technical business supplies, and Schukat electronic and TD SYNNEX, two of its suppliers, are already using networks to create transparency in their shared order management and procurement processes. By automatically sharing approximately 5,000 order updates daily in real time these companies have achieved greater transparency and efficiency. This collaborative data sharing has reduced manual interventions and expedited response times, highlighting the potential of business collaboration networks to revolutionize cross-company process optimization.

In the Intelligent Age, where processes cross boundaries and face AI-driven disruptions, process intelligence emerges as the key to unlocking AI's true potential. By providing the unique class of data and business context that AI needs to understand business operations, process intelligence bridges the gap between AI's promise and its impact. Leading companies are already leveraging this combination to achieve transformative results, while collaboration networks extend their power across organizational borders, enabling unprecedented transparency and efficiency. As businesses embrace AI fueled by process intelligence, they drive innovation and growth and create sustainable, interconnected ecosystems poised to thrive in a dynamic future.