The AI Transformation Score: Tracking the Journey to Market Leadership

At Sprinklenet, we’ve seen it up close. AI transformation isn’t some passing fad; it’s a journey that splits tomorrow’s winners from those who might struggle to keep up.

We’re developing something we call the AI Transformation Score.

The score will track how public companies adopt AI and reveal who is positioned to thrive.

This score aims to measure how effectively companies are adopting AI to secure their future.

I’m Jamie Thompson and I believe companies that adopt AI quickly and decisively have the best shot at market leadership.

Fall short on this, or move too slow, and you’ll face a steep disadvantage.

Let’s dig into it.

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Every public company, from tech giants to retailers, needs to transform how they operate, innovate, and compete.

The thesis is simple. Those that start now, with urgency and ambition, will be more valuable in the long run. It’s not about your sector; it’s about your speed and adaptability.

Companies that can quickly integrate AI into their operations and adapt to new technologies will have a significant advantage.

The market leaders of the future will be the ones leaning into AI today.

But how do we know who’s ahead? Earnings reports hint at investments, and press releases tout big plans, but there’s no clear picture yet.

That’s why I’m considering a tool to help glean insights into public companies AI transformations: the AI Transformation Score. It’s a concept for a way to measure a company’s AI journey and spotlight the ones built for the next decade.

To track AI transformation, we need a framework. We’ll call it the AI Transformation Matrix. It’s a set of key areas that show how deeply a company is embedding AI.

Here’s what I’m thinking, based on our work helping enterprises navigate this shift:

And let’s add a few more, because transformation touches every corner:

Each area gets a score, weighted by its impact. For example, legacy integration might be 20% of the total, while experimentation could be 10%.

Together, they form a snapshot of a company’s AI progress.

Here are this week’s must-read AI stories:

Public companies give us plenty to work with. Earnings reports, public statements, and clues about vendor partnerships. Here’s how we’d pull it together:

- Earnings Reports: Look for AI mentions. Spending, projects, results. Hard numbers tell a story.

- Public Statements: CEOs love to talk strategy. We’d analyze speeches and releases for AI focus and tone.

- Vendor Relationships: Who’s the company working with? Deals with AI vendors signal serious intent.

We’d crunch this data into an AI Transformation Score. Think of it as a rating system. A company scoring high isn’t just talking about AI; they’re doing it. And since this is public data, it’s perfect for tracking listed firms. (Private companies? That’s trickier, but the principles still apply.)

Think AI is just for tech firms? Think again.

Walmart, a retail giant, is using AI to optimize supply chains and personalize customer experiences. They’re not just selling products; they’re predicting demand, cutting waste, and driving loyalty.

It’s a lesson for all: even traditional companies can leverage AI to stay ahead.

A high AI Transformation Score could predict real value. Higher stock prices, bigger market share, and stronger growth. Picture this: a retailer uses AI to streamline supply chains and upsell customers, while a competitor stalls. Who wins? The data backs our hunch—early AI adopters are already pulling ahead.

For us at Sprinklenet, this tool isn’t just analysis—it’s a guide. We help companies boost their scores, whether it’s upskilling staff or integrating systems. Investors can use it to spot opportunities.

Executives can see where they stack up.

We’re still refining this. How do we weight the matrix?

How do we handle spotty data? We’re considering a dashboard that ranks companies, tracks trends, and links scores to stock performance. Imagine linking scores to stock performance to prove the payoff.

It’s a work in progress, but the vision is clear: measure AI transformation, and you’ll see the future of business.

Imagine this tool existed—how do you think your company would score?

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Today’s coding soundtrack: my custom 'Julio con Julio' playlist, featuring Julio Iglesias’ classics on repeat. It’s the perfect July (Julio en español) backdrop for powering through code reviews, PRDs, client updates and team coordination.