Simple, scalable, and sustainable: A methodical approach to AI adoption (sponsored by Accenture)

After crossing the first AI implementation milestone, leaders often ask, "Whats next?" Based on experience implementing AI-led automation for more than 100 clients, Accenture has developed an easy-to-use methodology for scaling and sustaining reliable AI solutions. Rajendra Prasad (RP) explains how leaders and change makers in large enterprises can make AI adoption successful.

After crossing the first AI implementation milestone, CIOs and CTOs often ask, “What’s next?” AI engineering best practices don’t exist yet, making scaling and sustaining these solutions a challenge. Accenture has developed an easy-to-use methodology for achieving predictable high-speed production releases and sustaining reliable AI solutions, based on experience implementing AI-led automation for more than 100 clients. Accenture’s approach helps align AI and business needs and benefits and establish a well-defined methodology for the entire AI engineering lifecycle, from data engineering (ingesting, cleansing, normalizing, and optimizing) to selecting the right AI models. It also helps identify key change management actions for people, processes, and technology. Rajendra Prasad (RP) explains how leaders and change makers in large enterprises can make AI adoption successful.