BPM in an AI-first era: Start now, think big, go fast

Business process management (BPM) is back in the spotlight, ushering in a new golden age not witnessed since the 1990s digitization boom triggered by enterprise resource planning (ERP) deployments. Two key factors are driving this resurgence. First, businesses are prioritizing performance and efficiency over unsustainable, unchecked growth and, second, the growing influence of generative AI has expedited its adoption as corporations seek market advantages.

The critical role of process transformation in AI success

Despite the long-standing existence of AI and machine learning solutions, their implementation has been generally sluggish. The rapid emergence of generative AI sparked a shift, causing businesses to aspire to become AI-first, a transition easier in theory than execution. While 63 percent of executives rate the implementation of generative AI a high priority, McKinsey reports that only 11 percent of businesses have adopted the technology at scale. Surprisingly, 72 percent of executives are intentionally cautious regarding their investments in generative AI.

The challenge isn’t rooted in technological difficulties. ABBYY’s AI Trust Barometer revealed a high trust level (84 percent) in AI tools. Even more, decision-makers considered small language models (SLMs) or purpose-built AI (90 percent) the most reliable. Over half (54 percent) already use purpose-built AI tools, such as intelligent document processing (IDP). The real challenge lies in operationalizing and scaling AI programs.

The most effective model or intricate prompt is unproductive in isolation. As a result, BPM is once again in the limelight. AI’s imminent influence on almost all enterprise workflows makes process discovery, analysis and redesign fundamental for operationalizing any program, let alone scaling it. This predicament mirrors the challenges previous digital transformation efforts faced, which suffered poor success rates due to excessive technology focus while neglecting human or process considerations.

AI’s value addition to the BPM stack

While operationalizing and scaling AI mandates process excellence, this is a two-way street. AI has infused BPM technologies with new capabilities in recent years, delivering more organizational value than earlier BPM tools. This progress permeates the entire BPM landscape.

• Discovery: AI has revolutionized process discovery by automating the identification of workflows through process and task mining. The technology swiftly analyzes system logs, automating the mapping of processes, which traditionally required substantial manual effort.
• Analysis: Incorporating process mining, AI identifies complex patterns within large data volumes, enhancing accuracy. It predicts future process behaviors based on historical data, enabling proactive issue management. With machine learning, AI-enabled systems continually learn and improve, optimizing process and analysis.
• Modernization: Redesigning processes by leveraging intelligent automation (IA), IDP, natural language processing (NLP), computer vision (CV) and other emerging technologies is at the heart of incorporating AI into modern BPM.
• Simulation: AI has significantly enhanced process simulation. Accurately modeling and predicting process behavior based on large amounts of data provides a more precise and detailed simulation at much less cost and effort. This enables businesses to test various scenarios and anticipate the potential impact of process changes.
• Compliance: AI aids in process compliance by automating monitoring and enforcing regulations within business processes. It can scan and analyze vast amounts of data to identify non-compliance issues or potential risks. This ensures regulatory adherence, saves time and reduces costs associated with manual compliance checks.

Financial services firm mines $6 million in savings

Illustrating the influence of AI on BPM, executives in a Fortune 100 financial services firm had questions about the cost-efficiency of processes involved in managing a high volume of transactions across hundreds of internal systems, ranging from customer interactions to back-office workflows.

ABBYY Timeline aggregated event data from two million transactions daily across enterprise-wide systems into a live data stream. Analysts could finally follow a transaction’s execution progress from beginning to end. The platform revealed transaction paths where manual handling significantly delayed distributions, providing an opportunity for US$3.6 million in savings through automation. Process intelligence also helped analysts find a specific type of transaction with higher delay and market exposure, resulting in $2.4 million in expenses that could have been avoided. 

AI-Driven process technologies: Pathway to the autonomous enterprise

The advancement in AI-enabled process technologies is steering businesses towards highly streamlined and efficient operations, reducing manual intervention and enhancing decision-making. As routine tasks are automated and complex tasks simplified, employees can focus on strategic and innovative initiatives. This shift will yield significant cost savings, increase productivity and improve customer satisfaction.

AI’s data learning capabilities make continuous process improvement at scale possible and manageable. The ability of machine learning algorithms to learn from historical data and continually adjust business processes promises self-optimizing systems that continuously improve efficiency and effectiveness.

Despite the challenges, such as data security and privacy, managing AI’s ethical implications and upskilling employees, the integration of BPM and AI can transform businesses, making them more efficient, agile and competitive in the digital age.

Act now to harness AI’s BPM potential

Companies are reevaluating their strategies and investing more in technology in response to AI’s market promise and business opportunities. Nevertheless, AI cannot measurably impact performance until it is deployed and operating at scale. This is where the next generation of BPM tools, combined with AI powers, can make the process more efficient, accurate and cost-effective. These capabilities are available today and will only improve, so the time to start gaining competitive advantage is now.