Artificial intelligence (AI) initiatives often stall because of poor architectural choices, a lack of preparation and the inability to scale. Enterprise architecture and technology innovation leaders can create an AI architect role to help build a robust enterprisewide architecture for AI.
Through 2023, Gartner estimates that 50% of IT leaders will struggle to move their AI projects past the proof of concept (POC) stage into production. To increase the chances of success, organizations can hire an AI architect to help define the architectural strategy, create workflows, identify toolsets and scale artificial intelligence operations.
Who are AI architects?
“AI architects are the curators and owners of the AI architecture strategy. They are the glue between data scientists, data engineers, developers, operations (DevOps, DataOps, MLOps) and business unit leaders to govern and scale the AI initiatives,” says Arun Chandrasekaran, Distinguished VP Analyst at Gartner.
They work closely with enterprise and solution architects, but unlike the enterprise architecture team, which is responsible for a broad set of functions, they are laser-focused on building a robust enterprisewide architecture for AI.
What do AI architects do?
AI has a diverse range of use cases and deployment models, so AI architects need a wide array of capabilities:
What skills do AI architects need?
AI architects need a diverse set of skills that can be difficult to acquire in a short time.
Technical skills include:
Non-technical skills include:
The original article by Arun Chandrasekaran, Gartner's distinguished vice president analyst, is here.
The views and opinions expressed in this article are those of the author and do not necessarily reflect those of CDOTrends. Image credit: iStockphoto/gorodenkoff; chart: Gartner