By Technology

The Enterprise AI Platform Landscape: Where to Start (and Why It’s So Hard)

AI is out of the bag and advancing at an extraordinary pace; and though clear, measurable ROI remains elusive for many organizations, it would be unwise to “wait and see” about AI.   At the same time, the AI market landscape is rapidly shifting. New tools, new versions of tools, new frameworks, and frequent acquisitions can reshape roadmaps almost overnight. Meanwhile, AI initiatives are often fragmented across departments and persistent challenges like data debt and talent gaps can slow efforts.  The pressure is on to build AI-ready infrastructure and start experimenting now, but how? For technology leaders tasked with deploying AI across a 50,000-person organization, where do you actually start? Choosing the Right Approach: Build, Buy, or Platform? One of the first strategic decisions is whether to build internally, buy a platform, or adopt a hybrid approach to AI–a choice that’s often less about technology than organizational readiness.  Build: Control & Responsible AI Building a custom AI stack offers the highest level of control and customization, but it’s expensive, time-consuming, and requires adequate expertise.   Companies like Uber and Netflix have built internal AI ecosystems by combining open-source tools, proprietary models, and cloud infrastructure. This approach is best suited for organizations with […]

6 min read