Reimagining business processes with AI

Artificial intelligence has clearly emerged as the latest digital frontier in the enterprise with most technology-led transformations inclusive of AI capabilities offered by all major cloud and on-premise platforms. These first-generation AI-driven applications and cloud-based services deliver significant enhancements in the accuracy and efficiency of activities and decisions made in the enterprise. The first generation of AI capabilities include intelligent data aggregation and correlation, conversational agents, computer vision, natural language processing and robotics. We are seeing adoption of these capabilities in business functions like marketing, customer service, operations, back-office tasks, logistics and ITSM.

Adopting AI top-down from business processes
While the adoption of AI is delivering point efficiencies in specific activities and decisions, enterprises still struggle to create enterprise-wide business outcomes with AI at the aspirational scale of an Amazon or Google. Business outcomes are generated by business processes that form higher layers of abstraction across business functions to drive consistency and predictability over activities and decisions made. Business processes rely on systems for single sources of truth about the enterprise, and synchronize the activities and decisions led by people, applications and, more recently, virtual agents. The need to drive consistency across business functions and activities creates complexity in the structure of business processes that makes them inherently less flexible and resistant to change.

The rigidity of business processes comes in the way of delivering enterprise-wide outcomes from the adoption of AI, as it severely localizes the value of AI adoption to point activities and decisions. For instance, an implementation of AI for dynamic customer segmentation is of limited value if the order management business process is too rigid to adapt the customer’s experience based on the segmentation inferred. Hence, the enterprise struggles to show growth in revenue and customer satisfaction as a result of the adoption of AI. Therefore, the adoption of AI in the enterprise has to be driven top-down all the way from the business process layer of abstraction.

Reimagining business process lifecycle with AI
The above premise is the foundation for The Hive‘s point of view that the lifecycle of business processes needs to be reimagined with AI. Business processes need to be equipped with the discretion between optimizing for consistency by holding on to the as-is structure vs. flexibility by designing & adopting new customized structures to actively address changing business scenarios. We see this form of self-awareness in action in the way ride sharing services like Uber optimize customer experience across orders and operations. This demands an AI-centric continuous transformation of business processes, where this capability constantly drives change and flexibility in the structure of the process without trading off consistency. Thus, business process transformation turns AI-centric & continuous, from today’s human-centric & retroactive form. This ambition of turning business processes self-aware and closed-loop led to the co-creation of Live Objects.

Introducing Live Objects
Live Objects realizes the “Autonomous Enterprise” vision by its path-breaking application of AI at the business process abstraction for continuous business process optimization. It is the world’s first closed-loop continuous process engineering product built upon its patent-pending technology that has been built from recent advancements in AI primitives across deep neural network, sequence pattern mining and NLP. Live Objects’ closed-loop approach comprises of process discovery, engineering optimal process design and process adaption into the as-is implementation:

  • Process Modeling: Live Objects drives process discovery by modeling activities from unstructured user-behavior manifested in emails, messages, case texts and screen behavior in the context of the current as-in implementation and transactions captured in the business systems. Process mining platforms provide such insights to human consultants for aiding traditional business transformation. However, Live Objects goes beyond process mining to build mathematically rigorous model abstractions for AI-centric closed-loop business transformation.
  • Process Engineering: The new process design is driven by restructuring and re-sequencing business process activities to optimize targeted operational, business and customer experience goals at an end-to-end business process abstraction. These new process structures are built from Live Objects’ advanced AI capabilities of association rule learning, local process optimization and causal network modeling. These structures are generated with well-defined business object associations and business system plug-ins to seamlessly migrate cases from the as-is process implementation and, if required, hand them off back.
  • Process Adaptation: Continuous business transformation inevitably requires continuous assessment of risk and conformance. Live Objects brings pre-built domain-specific risk models and adopts as-is implementations of conformance models to select process designs that successfully clear the risk metrics. These process designs become viable candidates to be brought to the as-is process implementation for production; thus, completing one cycle of business transformation.

Cycles of business transformation on autopilot with Live Objects
Live Objects’ cycles of business transformation are agile, short and customized to fine-grained segments of the enterprise’s business operations. For instance, Live Objects’ order management solution delivers targeted on-demand experiences to specific customer segments inferred in response to changing channel and competitive landscape. These cycles of transformations can occur in windows of fiscal weeks to months – thus delivering business outcomes in the form of number of orders closed at the quarter end and the customized experiences projected to customers & partners. We are also seeing strong demand for Live Objects in e-commerce, process migration & consolidation, procurement and supply-chain management.

Live Objects is laying new rails for an enterprise’s AI-centric digital transformation to own real business outcomes. It is redefining the relationships between processes, systems and people to enable enterprises to achieve actively changing business goals. We look forward to playing an active role in the emerging AI-centric enterprise business ecosystem. The Hive and its community of investors & partners are proud to herald the second-generation of AI adoption in the enterprise with Live Objects.

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