FIELD

The field relates generally to information processing systems, and more particularly to techniques for process execution using artificial intelligence (AI) capabilities in information processing systems.

BACKGROUND

Information processing systems increasingly utilize reconfigurable virtual resources to meet changing user needs. For example, cloud computing and storage systems implemented using virtual machines have been widely adopted. Such cloud-based systems include, for example, Amazon Web Services (AWS), Google Cloud Platform (GCP), and Microsoft Azure. Despite the widespread availability of these and numerous other private, public and hybrid cloud offerings, there exists a significant problem in conventional practice in that there is no adequate mechanism available for optimizing multi-cloud deployments during run-time utilizing the benefits of artificial intelligence.

SUMMARY

Illustrative embodiments of the present invention provide information processing systems configured to deliver artificial intelligence-enabled enterprise class process execution.

In one embodiment, an apparatus comprises a processing platform that includes a plurality of processing devices each comprising a processor coupled to a memory. The processing platform is configured to implement at least a portion of at least a first cloud-based system. The processing platform further comprises a process modelling language extension module configured to implement multiple artificial intelligence-based decision points into a process flow and compile one or more context attributes associated with the multiple artificial intelligence-based decision points based on data derived from one or more artificial intelligence systems. The processing platform also comprises a process engine configured to convert the multiple artificial intelligence-based decision points and the one or more context attributes to input to a process optimization algorithm, and an optimization engine configured to determine, by applying the process optimization algorithm to the converted input, an overall execution path within the process flow, and output a decision to a first of the multiple artificial intelligence-based decision points based on the determined overall execution path within the process flow.

Illustrative embodiments can provide significant advantages relative to conventional enterprise cloud computing platforms. For example, challenges associated with the limitations of traditional process automation systems are overcome through combining AI systems and automation systems for processes to generate intelligent, automated, and optimized technical and business process execution. One or more embodiments of the invention can include utilizing AI techniques in conjunction with operations research methods to enable optimization and automation in the execution of processes requiring human intervention in traditional systems.

These and other illustrative embodiments described herein include, without limitation, methods, apparatus, systems, and computer program products comprising processor-readable storage media.

