The CEO of Edge Platforms, EdgeVerve Systems Limited, emphasizes the importance of connectivity and harnessing external data for successful and innovative enterprises. Artificial intelligence (AI) can significantly enhance sources, processes, and workflows, leading to stronger, quicker, and more competitive organizations. Companies that have an externally informed mindset are less vulnerable to biases and internal politics and can quickly adjust strategies and initiatives.
Data integration is a complex equation for enterprises, requiring the use of application programming interfaces (APIs) and connectors to link with data sources. Enterprises can manage these sets through crowdsourcing, enabling reuse and adaptation of capabilities. Many clients are utilizing task-mining capabilities of robotic process automation (RPA) and AI/machine learning (ML) algorithms, as well as AI to build and manage API infrastructure. GenAI is an emerging use case for developing, optimizing, and protecting APIs, simplifying existing stacks of APIs and making it easier to adopt more AI.
A connected enterprise deals with machine-generated structured data and a larger volume of unstructured data, primarily human-generated. Leveraging raw data requires mining for information, structuring it into usable formats, and utilizing tools like natural language processing (NLP) and AI for transformation. Automated tools can assist in tasks such as entity recognition, part of speech tagging, semantic analysis, keyword extraction, frequency matrices, and sentiment analysis.
Creating data pipelines with RPA, automation scripts, and APIs can lead to straight-through processing, benefiting time-sensitive and high-volume processes. Organizations are turning to data fabrics to integrate data assets, pipelines, and other components, such as data dictionaries, data catalogs, new data architectures, manual processing for quality control, and data engineering. The goal is to have a common platform that brings together task, work, process, document, and insights from underlying and partnered systems.
Companies that efficiently connect with all data sources, make unstructured data more usable, and unify their data infrastructure have advantages such as fewer silos, more flexibility, and greater intelligence. Advanced AI can help deliver these gains, with the possibility of expanding the scope of what is possible. To achieve specific goals in utilizing advanced AI, refining targets, cleaning up connectors, harvesting structured data, and building an enhanced data fabric are essential within a well-connected enterprise. AI can enable gains, supply real-time, relevant data, and provide contextual insights crucial for innovation, agility, and competitive strength.
