The Last Mile of AI: Deployment
We’re already seeing waves of this from certain vendors, but the idea of helping organizations through that last mile of the AI lifecycle—deploying a model into production—will become a focal point for customers and vendors alike in 2020. Here are a few recently collected data points that emphasize the importance of vendors helping customers to operationalize AI:
72% of organizations with AI initiatives do not yet have AI in production.
44% of organizations investing in specialized infrastructure to support AI initiatives do not expect to see value in their investments for at least ten months.
Nearly one in four organizations (23%) cite model deployment as the phase of the AI/ML data pipeline that creates the greatest challenge.1
Why would an organization invest hundreds of thousands of dollars to not see a return on the investment for over a year? Why would businesses waste the time, effort, and money to make it 80% of the way to leveraging AI, and then fall short at the end? Simply put, they won’t. They’ll turn to prebuilt tools, solutions, or applications that embed AI and say, “it’s good enough.” In the short term, that may work, but in the long term, they’ll need to figure out how to better customize AI to their specific business and use case. And to get there, they’ll need to solve the AI deployment challenge.
1. Source: ESG Master Survey Results, Artificial Intelligence and Machine Learning: Gauging the Value of Infrastructure, March 2019.