As AI tools have had the time to be fully implemented and iterated across industries, we’re noticing a shift in the conversation around the technology and how it’s deployed and used.
The first thing is to clearly define the problem being solved by your AI tools. Buying AI without a clear purpose is risky at best and a loss at worst. Unless the goal is to make money, save money, or ensure compliance in a very specific way, purchasing AI can be completely ineffective.
Second, we’re seeing companies discover that AI implementations greatly benefit from careful planning. Regardless of what you hear, there are simply no great “out-of-the-box” deployments. Successful integration requires treating AI as a component within a portfolio of methods and processes, not a replacement for them. Without this thoughtful application, organizations risk wasting time and expensive resources.
Taxonomy construction, training, and support can make all the difference in these projects. The conclusions experts are drawing lead us directly to solutions like working on taxonomy architecture and governance.
Does your organization need help with planning an AI implementation? Reach out, and let us know what you’re facing.