Companies Can Build AI Demos. The Hard Part Is Making Them Work in the Real World.

A BearingPoint study found that nearly three-quarters of surveyed organisations with implemented AI reported measurable financial impact, yet only 13% had scaled their AI initiatives completely in line with the original business case.

Legacy-system integration and regulatory complexity are among the barriers to scaling.

The engineering lesson is important:

Prototype → Existing Systems → Data → Security → Deployment → Monitoring → Business Outcome

Building an impressive AI prototype is only one part of creating a production system.

Students interested in AI engineering therefore benefit from learning software engineering, APIs, databases, cloud, security and deployment alongside AI.

Takeaway: The difficult part of enterprise AI increasingly begins after the demo works.