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April 2, 2025
Businesses have long relied on AI toย automate specific tasksโfrom predictive maintenance in manufacturing to customer service chatbots. These systems have streamlined processes, reduced costs, and improved efficiency. But despite these advancements, automation remainsย limited:
This is whereย agentic AIย marks a fundamental shift. Unlike traditional automation,ย AI agents donโt just assist humansโthey make autonomous, cross-functional decisions. For enterprises, the challenge isnโt just implementing AI, but ensuring AI operationalizes the functions required to enable business capabilities.
For enterprises to truly harness AIโs potential, they must embedย agentic AI into their business capability models (BCMs), ensuring AI systems can self-optimize and drive transformation at scale.
This blog explores:
Aย Business Capability Model (BCM)ย defines the core functions that an enterprise needs to deliver value. Instead of focusing on isolated processes, BCMs map how capabilitiesโsuch as supply chain, manufacturing, and customer engagementโinterconnect.
By integratingย AI agentsย into BCMs, businesses can automate decision-making, improve operational efficiency, and enable real-time responsiveness.
To understand how AI maturity impacts business functions, consider theย industrial machinery manufacturing sector, where companies likeย Caterpillar, John Deere, Komatsu, and Siemenshave long used AI to optimize operations. These organizations rely on AI for many operational capabilities like supply chain and logistics execution, manufacturing operations, and quality and compliance management. But until now, most AI applications have been process-level enhancements requiring human intervention โnot full-scale intelligence embedded into the enterprise.
To truly transform business operations, organizations must move beyond process-level automation to Agentic AI, where AI systems can autonomously execute cross-functional tasks, optimize processes in real-time, and make data-driven decisions without human oversight. This transition enables seamless integration across business functions, allowing enterprises to anticipate disruptions, self-adapt to new challenges, and drive continuous optimization.
By embedding AI agents in workflows and processes within these capabilities they can:
The table below examines how AI maturity transformsย core business capabilitiesย in manufacturing.
AI transformation is a gradual process. To ensure success, businesses must:
For businesses to fully integrate Agentic AI, they must align AI with their Enterprise Architecture (EA)โa structured framework for managing business functions, data, applications, and technology. This means embedding AI at every level of architectural layer to ensure business functions, applications, data, and infrastructure work together seamlessly and autonomously:
By embedding AI intoย every layer, organizations create anย intelligent, self-learning enterpriseย that continuously adapts and improves. Organizations that successfully integrate AI into their Enterprise Architecture are able to:
Neudesic helps enterprises move beyond automation by embedding AI into business capability models. This approach ensures AI isnโt just a toolโit becomes a strategic driver of transformation.
Neudesicโs approach includes:
By embedding AI intoย Business Capability Models, Neudesic helps enterprisesย move beyond automationย andย develop intelligent, self-adaptive business functionsย that enhance efficiency, agility, and decision-making.
The shift fromย AI automation to agentic AIย represents aย fundamental transformationย in how organizations become intelligent businesses. Companies that successfully integrateย AI-driven intelligence and autonomous execution are able to compete in an AI-first ecosystem, gain aย competitive advantage, and unlock efficiency, agility, and innovation at scale.
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Sarrah Shah
Vice President Growth & Expansion Strategy
Sarrah.Shah@neudesic.com
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