Scaling value is about understanding how to move from pilot to production; getting your data strategy in place to drive real-time strategic actions; and establishing the right talent mix, operating model and governance framework. Those who succeed will reap the rewards. And those who fail may find their businesses fall by the wayside (75 percent of executives believe they will be out of business in five years if they cannot scale AI effectively).
There’s a lot to think about—and a strong business case to get started quickly. In this primer, we have asked some questions and provided some insights on what it takes to scale AI effectively and move beyond proofs of concept to production. But how does it all come together in practice—and what concrete steps can you take to realize value quickly?
We invite you to go through our roadmap and evaluate how you’re approaching your AI projects. Stop at each checkpoint and ask yourself the flagged questions to make sure you're setting yourself up for success—with your data, your people, your infrastructure and your organization at large. Whether you’ve been in proofs of concept or are already starting to scale AI, be assured that there are concrete steps you can take to realize even more value from your AI initiatives
To scale effectively, run an unbreakable thread that traces the critical path to production through all of these highly connected elements. Only then can you amplify value.