Common Issues and Root Causes
The adoption of automation and AI capabilities can be subject to a variety of obstacles and issues. But, as with both self-service and knowledge management success, it’s important to look beyond the symptoms to understand the root causes.
For instance, you can end up with AI technology complexity, where there are a variety of different AI solutions employed to undertake potentially similar tasks. It’s the result of different teams working in silos rather than participating in an enterprise-wide approach to AI adoption. It wastes IT resources and makes life harder for everyone involved.
Or, you can end up with new AI-enabled capabilities that employees don’t want to use. As with self-service and knowledge management, the new capabilities are created based on
what the technology can do rather than how
people want to work. It might be a case of
technology projects overlooking the need for organizational change management.
Finally, you can be slowed down and potentially defeated by attempting to build AI inhouse. Instead, use best in class third-party, cloud-based AI services, or software that already has AI capabilities built in.
Importantly, don’t waste your IT resources on the
fundamentals of AI. Instead, use these valuable resources and third-party AI capabilities
to create beneficial solutions to business issues, challenges, and opportunities.