AI adoption: How to move fast without building on unstable ground

[PODCAST]AI project Joseph Aoun x Margot Bletterie 2
Joseph Aoun - Data and AI solutions Director (UAE)

By Joseph Aoun - Data and AI solutions Director (UAE)

In 8 August 2025

As organizations race to adopt AI, many face the same dilemma:

How do you deliver quick wins without compromising the foundations your AI strategy depends on?

This tension — between speed and sustainability — is something we explore in detail in our latest episode featuring Joe AOUN, Data & AI Solutions Director, and Margot Bletterie.

Here are a few key takeaways from the conversation.

 

1. Solid data foundations still matter — but timing is key

Clean data, proper governance, and a scalable architecture are essential for long-term AI success. But in today’s fast-paced environment, building everything before delivering any value isn’t always realistic.

The priority becomes:

➡️ What do we need to build to unlock the next use case?

➡️ How can early wins help justify further investment in the foundation?

It’s not about skipping steps — it’s about sequencing them right.

 

2. Use cases first. Technology second.

Many teams start with tools — not problems. But the risk of “AI for the sake of AI” is real.

Instead, the most successful approaches we see are rooted in clearly defined use cases:

  • Is there a business pain point AI can help solve?
  • Is the data available (or accessible enough) to support it?
  • Can we test it on a small scale first?

Starting small with targeted pilots helps reduce risk and build trust across teams.

 

3. Build for momentum, not just perfection

A strong AI strategy doesn’t require a 12-month build before anything goes live.

Teams can:

  • Start with MVP-level data models and iterate
  • Prove both technical feasibility and business value step-by-step
  • Reinvest early wins into strengthening the platform over time

Joe put it well in the episode: “Start small, think big.”

This approach helps avoid the trap of endless pilots that never scale — and ensures that what’s being built responds to real needs.

 

4. Align on the “why” — across business and tech

AI is as much about people and change management as it is about data and models. Governance, transparency, and internal education matter.

Make sure:

  • Executives understand the risks and opportunities
  • Business teams are involved early
  • Users see real benefits, not just new tools to adopt

Sustainable adoption requires cross-functional alignment — and ongoing collaboration between business and data teams.

 

Conclusion: Pragmatism over perfection

There’s no single “right” way to adopt AI — but one thing is clear: real value comes when strategy and execution work hand in hand.

Build what you need to move forward. Deliver results that build credibility. And keep investing in the foundations that will support you at scale.

[PODCAST] Joseph Aoun x Margot Bletterie 3

PODCAST

#3 Joseph Aoun - Is your company ready for AI?

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