From AI curious to AI ready

What does it mean to be ready for AI?

The last few years have shown just how much AI has in store for innovative companies. Think digital twins that help jet engine components last up to 70 percent longer. Predictive maintenance software that boosts manufacturing capacity by 4,000 hours across multiple plants. A search tool for internal biopharma data that shaves weeks off the regulatory submission process.

These are all real AI tools. And the companies that use them see enormous gains in efficiency, productivity, and cost savings—just to name a few benefits. At the root of it all: a rock-solid data foundation.

In a literal sense, you need data to train and refine AI models. But the quality of that data matters a lot. It’s the difference between putting regular or premium fuel into a Rolls-Royce. Your models might scrape by with low-quality data. But they probably won’t help you make accurate maintenance predictions or identify supply chain disruptions in real time.

Your team also has to know how to manage your data, interpret data-driven insights, and make ongoing updates. Without that knowledge, your AI could see low adoption or poor performance—and result in a steep error cost.

Not sure if your organization is quite ready for AI? Read on for tips to help you assess.?

How to assess your data readiness for AI

If you want to embrace AI, it helps to know whether your org’s data is in good shape. We recommend setting aside some time to…

• Inspect your data infrastructure: Make sure your data is accurate, complete, and consistent. Check with your team to see whether it’s easy to find and use. Evaluate your governance practices, too—they’re key to maintaining your data’s integrity and your org’s regulatory compliance.
• Analyze your team's capabilities: Does your team understand how to leverage data and check AI outputs for errors? Do you have a strategy to ease AI into employees’ workflows? Do you have training resources to upskill folks if needed?

A thorough assessment won’t happen overnight. But you can kick-start the process with an AI readiness survey. You’ll get a holistic view of where your data stands and the steps you need to take to realize your AI potential. If you have five minutes to spare, we’ve got one you can take.?

3 strategies to make the leap from AI ready to AI enabled

AI-ready organizations are in an excellent position to reap the biggest benefits of AI. To capitalize on that opportunity, consider applying these three practical strategies:

1. Develop an AI center of excellence: This is a dedicated team or hub within your org that helps identify AI best practices and share knowledge with employees. It’s a great way to drive org-wide adoption.
2. Explore emerging AI use cases: Stay abreast of the most exciting AI use cases in your industry to discover new opportunities for your org. Then, gauge whether they’re likely to create value—and consider working with an innovation partner to build, test, and validate potential solutions.
3. Conduct regular AI ethics audits: Questions about ethical AI use have mounted in recent years, especially since the rise of generative AI. Regular ethics audits can help you pinpoint glaring issues with data privacy, transparency, and bias. This way, you can maintain the trust of employees and customers.

With a pragmatic and proactive approach, you can smooth out your transition from AI ready to AI enabled.

For your ears

If you’ve ever received an Amazon package in under 48 hours, you’ve seen the value of an AI-enabled org firsthand. Want a peek under the hood? In the latest episode of The Modern Industrialist Podcast, Jason Hehman takes a look at the tech Amazon uses to make the magic happen.