The AI-Driven Connected Enterprise

AI-driven connected enterprises enhance data integration and streamline workflows using APIs and AI tools.

Successful and innovative enterprises are well connected. They are notably good at preparing and harnessing external data. Artificial intelligence (AI) can enhance sources, processes and workflows, making a well-run enterprise stronger, quicker and more competitive.

Being able to access and use data from customers, suppliers and other stakeholders is a good indicator of an organization’s capacity to make the right decisions. An externally informed mindset, according to the authors of a McKinsey report on innovative companies, is less vulnerable to biases and internal politics and enables rapid course-correction of strategies, R&D priorities and other initiatives.

Applied smartly, information can improve decision-making and erode inefficiencies. The right kind of data infrastructure is what enables a company “to break down (or at least perforate) silos,” as McKinsey puts it. What you need are integrated data connections, more structured data, and a platform or fabric that can unify workflows, tasks and analytics. All can benefit from AI.

Connectors And APIs

Data integration is a complex equation. To start with, enterprises use myriad application programming interfaces (APIs), typically paired with connectors, to link with data sources. Managing these sets is a challenge. One way we do so is through crowdsourcing, enabling the reuse and adaptation of capabilities.

Many of our clients are already familiar with the task-mining capabilities of robotic process automation (RPA) and AI/machine learning (ML) algorithms. But you also can use AI to build and manage your API infrastructure.

An emerging use case for generative AI (GenAI) is developing, optimizing and protecting APIs. (See, for instance, this Google Cloud session.) These kinds of deployments can, in turn, trigger a virtuous cycle: simplifying existing stacks of APIs, which make it easier to adopt more AI. The other prerequisite to using data is making sure that it’s in good order.[…]