How smart executives approach Enterprise AI
Artificial intelligence is at the leading edge of business transformation, much like electricity was, offering seemingly infinite implementations. If you’re an executive feeling overwhelmed by choice and endless possibility with your enterprise AI initiatives, we can help. Based on Noodle.ai’s work incorporating enterprise AI into complex operations on both the supply and demand side of businesses and the hundreds of C-level executives we have talked to over the past few years, we understand how to help you overcome three recurring roadblocks to C-suite enterprise AI initiatives.
Ignore the media hype: focus on how AI can go to work for you today
Media tends to play up the extremes on the positive (“AI will help cure cancer”) as well as the negative (“AI will lead to millions of lost jobs.”) Smart C-level executives ignore the hype and hyperbole and take a pragmatic approach. Instead of chasing some future AI nirvana, they focus on where and how AI might be able to help them improve their operations today. For example, focus on solving challenges like: “If our demand forecast can be made 10% more accurate with the help of AI, how will that enable us to manage our inventory and working capital better?”
Not humans or AI: humans and AI
Framing the situation between humans and AI as a zero-sum game blinds executives to superior outcomes that can be accomplished when humans and AI work together. Smart executives understand that, for most jobs, there is value in figuring out how the human doing the job could have decision-making ‘super powers’ at their disposal using AI. For example, smart executives intuitively understand that an operator in charge of maintenance at a complex industrial plant can be much more effective at their job if their experiential knowledge and heuristics are complemented with AI models that can help predict failures in equipment well before they happen.
Learn from your pilots, then follow through
Smart executives know that initiating an enterprise AI pilot to tackle a complex operational problem is not merely an IT project, but the start of a business transformation. Each aspect of this transformation has the potential to teach you quite a bit along the way. Use your pilots to discover how to improve existing data infrastructure, availability and readiness of data to build AI models to solve operational problems, and how to best adapt work processes to incorporate insights from AI. Savvy executives know ‘learning by doing’ trumps waiting for published case studies to be available every time. At the same time, these executives also understand that they must start pilots with a dual intent: to learn then roll out successful pilots into at-scale deployments.
- Why ServiceNow and Honeywell Invested in Noodle.ai To Solve the Global Supply Chain Crisis
- Beyond Control Towers – Supply Chain Command Centers
- How AI Helps Supply Chain Leaders Navigate a Turbulent New World: 3 Experts, 3 Perspectives
- Supernovae to Customer Success: A Data Science Journey
- How to Get Actionable Answers to Yield and Defective Production Issues Finally — and for Real