The common belief is that AI decisions are driven by compute hardware. However, NetApp's Keith Norbie argues the critical success factor is the underlying data platform. Since most enterprise data already resides on platforms like NetApp, preparing this data structure for training and deployment is more crucial than the choice of server.
In a confusing and rapidly evolving AI landscape, the most effective partners don't just implement solutions; they provide clarity. Their primary role is to help customers understand what is possible, bridging the gap between current business problems and potential AI-driven outcomes, thus solving problems before any technology is deployed.
Instead of pursuing complex, open-ended consulting projects, partners can scale more effectively by creating productized, "turnkey AI" offerings for specific business units like legal or marketing. This approach lowers the adoption barrier for customers by delivering predictable results for a defined use case, making it easier to sell into departments or smaller businesses.
Similar to how "born in the cloud" MSPs disrupted the channel ecosystem, a new category of "born in AI" partners is now emerging. These specialized firms are built from the ground up to deliver AI solutions. Legacy partners must adapt by building or acquiring AI practices to compete with these new, highly focused players.
For companies given a broad "AI mandate," the most tactical and immediate starting point is to create a private, internalized version of a large language model like ChatGPT. This provides a quick win by enabling employees to leverage generative AI for productivity without exposing sensitive intellectual property or code to public models.