Answers
Moving from AI experiments to enterprise capability
Quick answer
Moving beyond AI experimentation means making adoption part of how the organization works. That involves connecting AI initiatives to enterprise architecture and operating models, transforming relevant workflows, and educating the people who will use and sustain them. The aim is not simply to run more experiments, but to build capability that lasts beyond an individual project.
Connect AI to enterprise architecture
An experiment can explore a possibility on its own. Enterprise adoption calls for a wider view: how AI fits the organization’s architecture and its approach to transformation. That context helps leaders consider AI as part of the enterprise rather than as a collection of separate trials.
Make room for AI in the operating model
Durable capability depends on more than technology. Leaders also need to consider the operating model and the workflows AI may change. Looking at these together makes the conversation about how work gets done, not just what a demonstration can do.
Build knowledge people can carry forward
Education is part of sustaining change. Existing expertise can be turned into scalable learning, content, intelligent systems and organizational knowledge, so capability is not confined to the people involved in an initial experiment.
Evaluate before committing to adoption
For leaders assessing emerging technologies, research into their current and future impact on the enterprise can inform the decision to adopt. Rohan Hall’s work at Capital Group from November 2017 to June 2019 included research into emerging-technology trends and their impact on financial services and the enterprise.
Frequently asked questions
- Is enterprise architecture the same as an AI operating model?
- They address different parts of adoption. Enterprise architecture provides an enterprise-wide context; an operating model concerns how the organization works. Both matter when moving from experiments to lasting capability.
- Why include education in an AI transformation?
- Education helps turn expertise into organizational capability. It belongs alongside architecture and workflow transformation, rather than being left until after experimentation.
- Where can leaders start if they are still assessing AI?
- Start by examining the work AI might change, how it fits the enterprise, and what people would need to learn. Research into emerging technologies and their enterprise impact can help inform that assessment.
See how enterprise architecture fits into AI adoption and transformation.