AI

The modern creator isn't overwhelmed by a blank page; they're overwhelmed by a bottomless one. AI gives you ever more options, then appoints itself your guide. It tells you it’ll save time, then proceeds to steal it while you’re happily distracted.

Policies and proofs of concept can be useful, but they don’t generate economic value. For generative AI to be truly valuable to companies, they need to customize vendors’ language or image models with their own data, and do the internal work to prepare their data for that integration.

If we want to do AI, we need to build it on concrete, not quicksand. We are getting the process and data supply in good shape. We’re working on a data inventory and catalog, a data fabric with a new data structure and metadata layer, data pipelines, and ad-hoc self-service insights generation. We believe that generative AI will be a key way to

But if genAI is going to transform the organization, it doesn’t make sense to wait to start preparing data. We — and most of the survey respondents — agree that genAI is a transformative capability. The job to make a large organization’s important data ready for AI could easily take several years. The time to start is now.