AI Is Boosting Revenue, But Data Problems Are Holding Companies Back

(What you need to know about getting ready for AI)

Here’s the reality:

AI is changing how companies grow, but many are not ready to use it to its full potential. According to a survey by Accenture, companies that use AI well are seeing higher revenue and better productivity. Yet, many businesses still struggle because their data and systems aren’t prepared.

The problem is clear:

AI is only as good as the data it’s given. If your data is messy or hard to access, your AI projects won’t work. Nearly one-third of AI projects will be abandoned by 2025 because companies are not ready. The issue isn’t the AI itself—it’s the lack of preparation.

Why Some Companies Are Succeeding (And Why Others Are Not)

The companies that are winning with AI have a clear strategy and strong data systems in place. They know that having good data and a solid plan is what sets them apart. According to Accenture’s Arundhati Chakraborty, for AI to work, you need a strong digital base and a clear roadmap.

1?? Is Your Data Ready for AI? (Here’s Why It Must Be)

Your AI is only as good as the data it’s using. Companies with scattered or incomplete data often struggle to see results from their AI projects. Without clean, centralized, and accessible data, AI efforts will fail before they even start.

What You Can Do Now:

• Clean up your data by investing in data governance that ensures consistency.
• Build a central data platform where all information is easily accessible for AI processing.

?? Ask yourself: Is your data structured and secure enough to drive your AI initiatives?

2?? How Strong Is Your AI Strategy? (Here’s Why You Need a Roadmap)

Without a clear AI strategy, even the best technology can fail. Companies that have a well-defined roadmap for AI projects are already seeing better revenue growth and higher scalability. The rest? They’re burning through money with little to show for it.

What You Can Do Now:

• Develop a clear AI roadmap that aligns with your core business goals.
• Measure success early by connecting AI projects to revenue, customer satisfaction, and operational efficiency.

?? Think about this: Do your AI projects have clear goals, or are you jumping in without a plan?

3?? Close the Skills Gap Before AI Leaves You Behind

AI is more than just machines—it’s about people. Many companies lack the internal skills needed to successfully manage AI projects, which creates roadblocks. The faster you bridge this gap, the quicker your business can scale AI initiatives.

What You Can Do Now:

• Upskill your workforce by offering training in AI, data science, and cybersecurity.
• Hire AI experts who can guide your business through complex AI implementations.

?? Consider this: Do your teams have the skills needed to fully leverage AI, or is a lack of expertise holding you back?

4?? Are You Tracking AI Success? (Stop Chasing Short-Term ROI)

Measuring AI’s success goes beyond cost-cutting. It’s about creating lasting impact—whether that’s increasing revenue, improving customer experiences, or driving efficiency. Companies that focus only on short-term ROI often miss the bigger picture.

What You Can Do Now:

• Define key performance indicators (KPIs) that track long-term business outcomes, not just immediate savings.
• Evaluate how AI projects contribute to your company’s revenue and customer satisfaction over time.

?? Ask yourself: Are you measuring AI's true impact, or just focusing on immediate ROI?

Take Action Now: Don’t Let Data and Strategy Hold You Back

Generative AI is a powerful tool for growth, but only if your company is ready. Companies that are leading in AI have already taken steps to ensure their data is prepared, their people are skilled, and their strategy is clear.

But here’s the hard truth: Companies that wait too long to get ready will be left behind.

Will you be among the AI leaders, or are you risking falling behind?