Rethinking Legacy Businesses in the Age of AI: Insights from Ritavan

Last week in Munich, I had the chance to meet Ritavan, author of “Data Impact: How Legacy Businesses SAVE, LEVERAGE, ALIGN, SIMPLIFY, OPTIMISE, GROW to WIN.”

His perspective on how traditional industries can transform through data, not just technology, strongly aligns with our mission at DataDrivenAEC: enabling organizations to move from using data to truly empowering with it.

⚙️ Why write a book about data-driven legacy businesses?

Ritavan: I used to work as a trader and later in data-driven strategy roles within large companies. Over time, I realized that while many organizations collect data, very few actually leverage it to transform how they operate. Writing this book was my way to share lessons on how legacy firms can evolve, not just survive, in a data-centric economy.

🤖 Everyone is talking about using AI for efficiency. What is your view?

Ritavan: Using AI can certainly improve efficiency in the short term, but soon that will simply become the industry standard.

The real question is: What comes next?

If every company uses AI, efficiency alone will not differentiate you. To truly capture value, businesses must own proprietary data, rethink their business models, and use data as a strategic asset rather than just a productivity tool.

📊 Which part of your book resonates most with readers?

Ritavan: Readers are most intrigued by the Leverage chapter, which focuses on how to turn data into a competitive advantage. Many legacy businesses know they have valuable data, but they struggle to translate it into business value. I am currently working on a follow-up book that dives deeper into simplifying processes, because complexity often blocks progress.

🏗️ How do you see business models evolving in AEC?

Ritavan: The AEC industry still operates under large, lump-sum contracts that bundle everything together. In the future, I see firms becoming more specialized, each focusing on a distinct part of the process with their own data and expertise. Once that happens, the industry can productize services, trade risk and expertise more transparently, and achieve much higher efficiency, similar to how specialization transformed financial markets.

💡 How do you imagine a good business model for AEC firms?

Ritavan: Projects are the raw material, and products are the compounding engine. Every project generates data and that dataset can power productized services that cut costs, improve predictability, and help win the next project.

It becomes a continuous cycle: project → data → product → cheaper projects → more projects.

Firms that can turn this cycle into a flywheel will grow faster and capture far more value than those who only sell hours or deliverables.

🧩 What about regulation? Will that slow down change?

Ritavan: Regulation always follows value. Once the market recognizes the benefit of exchanging expertise and data, such as trading risk in finance, the rules will evolve. It might take time, but if there is genuine value creation, the system will adapt.

💬 Final thoughts

Ritavan: AEC is a complex field, but that is what makes it exciting. There is so much potential to rethink how we use data, build sustainable systems, and empower people across the value chain.

Ritavan’s book Data Impact offers a powerful framework for reimagining traditional business through data. His focus on ownership, leverage, and simplification reminds us that true transformation does not begin with technology. It begins with how we create and capture value.

Follow Ritavan and his work here: https://slasog.substack.com/

🎓 Upcoming Event: DataDrivenAEC Monthly Standup

AI is flooding the AEC world but do tools actually drive results?
Join our free 60-minute live session to discuss how to cut through the noise and focus on what truly matters.

🗓 Date: Oct 22, 2025
🕔 Time: 5 PM CET / 11 AM ET
🎯 In this session, you’ll learn:

• The essentials of AI and data-driven practice in AEC

• Why adoption alone isn’t enough and why the real edge lies in your data

• A simple framework for augmentation, automation, and analysis you can apply immediately

No technical background required just curiosity and good questions.

Reserve your spot (30 seats only): https://datadrivenaec.com/workshop

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