Getting Started with AI: A Practical Roadmap for Enterprise Leaders

I get this question a lot: "How do I get started with AI?" My answer always begins with the same principle—don't use AI as a hammer looking for a nail. Instead, understand what processes would benefit by embedding AI, automation, and technology transformation. It all starts with setting a clear strategy and business goal.

The Five Pillars of AI Implementation 

1. Establish Business Priorities First Start with a clear strategy and business goals. Focus on processes that would genuinely benefit from AI integration rather than implementing AI for its own sake.
2. Focus on Your Data Foundation AI without data is like a car without fuel or a library without books—it simply won't be useful for anybody. You need data that is complete, accurate, and high quality. However, focus on progress over perfection. Don't worry about getting your data to 100% data quality. There are going to be some use cases where 100% data quality is absolutely paramount, but a vast majority of use cases can work with "good enough" data to start iterating.
3. Build a Diverse, Skilled Team Here at Iron Mountain, we came up with an acronym: PAIM—Putting AI in the Hands of Mountaineers. We want the people that do the work on a daily basis and deliver value for customers to understand AI and how to incorporate it responsibly into their work. We provide training on AI so they know how to use, but can also  surface and implement ideas for ways we can use AI. 
4. Start Small and Iterate Don't go for the moonshot. Take baby steps. That's how you're going to learn, build your muscle, and develop muscle memory. Manage the scope of your AI projects, learn from mistakes, and be ready to iterate and adapt. 
5. Establish Your Non-Negotiables You need to establish security and compliance requirements upfront. If you're worried about data residency or data sovereignty, you need a compliance group that advises you on all these things so you can ensure conformance with local laws, rules, and regulations.

The Implementation Philosophy 

When implementing AI, here are some key guidelines:

• Focus on demonstrating return on investment. Have well-defined return on investments so you have organizational buy-in and the right level of support from every part of the company. 
• Start with the process, then back your way into technology rather than starting with technology and figuring out what applications may be best suited for AI. 
• Remember, it takes a village—get everybody involved, get everybody excited. Bring the entire company along with you for the journey. AI isn't just a technology initiative; it's an organizational transformation that requires participation from data privacy, compliance, legal, third-party risk management, and beyond. 

This blog post is based on an original AIIM OnAir podcast. When recording podcasts, AIIM uses AI-enabled transcription in Zoom. We then use that transcription as part of a prompt with Claude Pro, Anthropic’s AI assistant. AIIM staff (aka humans) then edit the output from Claude for accuracy, completeness, and tone. In this way, we use AI to increase the accessibility of our podcast and extend the value of great content.