Why APIs and API management are fundamental prerequisites for success in artificial intelligence (AI) applications.
As AI projects move from proof-of-concept to production, there is a growing need for closer collaboration between platform and API teams.
Many APAC organizations already possess the capabilities needed for AI within their existing platforms, but success depends on using them effectively and having the right internal processes in place.
DigiconAsia recently caught up with Markus Mueller, Global Field CTO for API Management, Boomi, to find out more about the importance of API management and API governance in the age of business AI adoption.
In your conversations with customers, do you see AI being viewed as an integral part of their digital transformation journey now?
Markus Mueller (MM): AI is currently seen as an additional component in most enterprises, as they remain in the experimentation phase—testing agent frameworks, evaluating feasibility across departments, and identifying responsible use cases. As organizations transition from isolated projects to broader adoption, they are turning to platform teams and trusted vendors to help integrate these initiatives into the core business, navigating both technical and change management challenges.
Organizations need to ensure that they are reducing friction and technical limitations in their projects through platform capabilities and tooling, ensuring that no organization is held back from progressing on their AI journey.
APIs already present certain challenges on their own. With AI now being added into the mix, what additional challenges are organizations facing?
MM: The introduction of AI amplifies existing API challenges. While many organizations have already adopted an API-first mindset, they now face difficulties in managing and governing a growing number of APIs, often referred to as “API sprawl.”
A key issue is that not all existing APIs are suitable for AI use; agents require APIs that are specific and unambiguous to function effectively, which may lead to the creation of even more narrowly tailored APIs. Unlike humans, AI agents cannot infer missing information, making high-quality documentation, clear descriptions, and detailed input/output examples essential for API usability.
Therefore, governance becomes even more critical. Organizations must ensure proper access controls for agents and maintain oversight of which APIs are in use and how. These challenges are no longer optional to address; there is now a direct link between API quality, agent performance, and business outcomes such as revenue and productivity. As a result, it is driving a new sense of urgency among organizations.
