How to Get Ready for AI: What Most Organizations Are Missing

Everyone is excited and enamored by artificial intelligence right now, but here’s the hard truth: most organizations simply aren't ready for it. Today, I want to talk about what you need to do to prepare for AI in a way that actually drives value instead of distraction.

I am the CEO of an independent consulting firm ( Third Stage Consulting Group ) that helps clients through their digital transformation and AI journeys. Across the world, we’re working with organizations that are buzzing with excitement about AI. The headlines are everywhere, the hype is contagious — but the operational readiness behind the scenes? It’s sorely lacking in most cases.

Too many organizations think they’re ready for AI when, in reality, they haven’t built the core foundations necessary to make it successful. If we don’t address those foundational steps first, we risk wasting a lot of time, money, and energy chasing shiny objects without delivering real results.

In this article, I want to share a practical roadmap for how you can get truly ready for AI — and why it’s absolutely critical to focus on the basics before you leap into the future. Be sure to also check out my new video on the topic:

AI Is Useless Without Good Data

The first and most important truth to understand is this: AI is completely useless without good data. This has actually been true for decades now — even before AI came into the spotlight.

For years, organizations have struggled to maintain clean, reliable data for basic reporting and business intelligence (BI) purposes. And now, AI is raising the stakes even higher. With traditional reporting, you could sometimes work around messy data. It wasn't ideal, but if your report was missing a few pieces, you could still manually dig around and fill in the blanks.

But with AI, there is no working around bad data.

AI models are only as good as the data you feed them. If your data is inaccurate, inconsistent, or messy, then your AI will produce inaccurate, inconsistent, and misleading outputs. Worse yet, AI will take those inaccuracies and amplify them. You’ll be training your AI models on a foundation of misinformation, creating what the industry calls "delusions" — outputs that look convincing but are dead wrong.

Before you even think about investing in AI solutions or rolling them out across your organization, you must clean up your data. And I’m not just talking about fixing a few typos here and there. You need a thorough cleansing across all categories: transactional data, master data, financial data, general ledger information — everything.

The reality is that most organizations accumulate bad data practices over time. People touch the data. There are no strong guidelines in place. Data degrades. Duplicates appear. Standards drift. Fast forward a few years, and your systems are a complete mess.

If you simply lift and shift that bad data into a new AI-enabled environment, it will sabotage your entire initiative. You’ll be throwing good money after bad, and your AI investments will fail to deliver real value.

Data Governance is the Second Layer of Protection

Cleansing your data is critical. But it’s not enough.

The next step you must take is putting strong data governance in place. Without it, all the hard work you did cleansing your data will be undone faster than you can say "machine learning."

Data governance is about the human side of the equation. It’s about establishing clear operational processes, rules, and ownership structures to protect your data integrity moving forward.

You need to define who owns each type of data. You need strict guidelines for how that data can be entered, edited, and maintained. You need controls to prevent unauthorized changes. You need ongoing data quality audits. Without this structure, people will continue to compromise your data, unintentionally or otherwise, leading right back to the same mess you started with.

A simple example is vendor master data. If everyone in your organization can create and edit vendor records without oversight, you’ll end up with duplicate vendors, inconsistent naming conventions, and a nightmare to manage. Multiply that problem across customer records, product SKUs, employee files, transactional entries — and it becomes a major liability for AI.

Governance ensures that your data stays clean not just today, but tomorrow and every day after that.

Redefining Roles and Responsibilities in an AI World

Beyond data, there’s another major shift you need to manage carefully: your people’s roles and responsibilities.

Rolling out AI isn’t just about deploying new technology. It fundamentally changes how people do their jobs. And if you don't help them navigate that change, you will face massive resistance.

This is different from data governance. Here, I’m talking about the broader operational impact on individuals and teams.

When you introduce AI, you’re introducing tools that can automate or augment large parts of someone’s daily work. That’s exciting — but it’s also terrifying for many employees. Without clear guidance, they will wonder:

• How does this tool affect my job?
• What’s expected of me now?
• Am I still valuable to the company?
• Will I lose my job?

And when people feel threatened or confused, they resist change. They shut down. They look for reasons to dismiss the new tools. They cling to the old ways of doing things.

That’s why it’s absolutely critical to clearly define and communicate new roles and responsibilities. Each person needs to know:

• How AI fits into their workflow
• What tasks will be automated or supported by AI
• What new skills or activities they should focus on
• How their contribution will continue to matter and even grow in importance

You need to paint a positive, empowering vision for your team. Help them see AI as a tool that frees them up to do more meaningful, strategic work — not a threat that makes them obsolete.

If you don’t address this upfront, the best AI tools in the world won’t save you. People will reject them or underutilize them. Change management isn’t optional here. It’s mission-critical.

The Importance of Phase Zero: Planning Before Action

One of the biggest mistakes organizations make when adopting AI is rushing straight into implementation without a solid plan.

At Third Stage Consulting, we call the planning phase "Phase Zero." It’s the blueprint, the architecture, the detailed roadmap that sets you up for success.

Phase Zero is where you define:

• How you’ll cleanse and prepare your data
• What data governance structures you’ll put in place
• How roles and responsibilities will evolve
• What systems will be integrated (and how)
• How you’ll train employees to adopt the new tools
• What your overall AI strategy and timeline will look like

Spending time in Phase Zero isn’t a luxury. It’s a necessity.

If you skip this step, you’re almost guaranteed to waste time, money, and goodwill. You’ll be chasing AI in a reactive, chaotic way, without the structure needed to succeed. The organizations that win with AI aren’t the ones that move the fastest — they’re the ones that prepare the best.

We’ve even created a Phase Zero checklist that you can download for free from our website. Whether you’re deploying AI, ERP, CRM, or any other enterprise technology, this checklist will guide you through the essential planning activities you need to complete before kicking off an implementation.

Be Excited, But Be Smart

Here’s the bottom line: I’m just as excited about AI as you are. We’re living through one of the most transformational technological shifts in history. The possibilities are endless. The future is bright.

But excitement without preparation is a recipe for disaster.

If you want AI to deliver real, sustainable value for your organization, you need to slow down now so you can speed up later. Clean your data. Put governance in place. Redefine roles and responsibilities. Build a solid implementation plan during Phase Zero.

Then — and only then — are you truly ready to start your AI journey.

If you’d like to dive deeper into how to deploy AI successfully, I encourage you to download our free guide to AI strategy and implementation. It’s packed with practical insights, real-world examples, and step-by-step frameworks to help you build the right foundation.

I hope you found this information helpful. It’s an exciting time for all of us, but let’s make sure we build it right.