AI or Data Strategy ?

What comes first??

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Recently had an insightful conversation with colleagues not related to our current workplace, but in general across industries.

The hot topic? GenAI, the consulting firms are after this to make another fortune 💰yet basics are missing in many organizations before they can share the joy of AI.

What’s crucial for any organization to really succeed with Generative AI (GenAI)!!

Does journey begin with quality data or AI can also assist in identifying and correcting data?

We all left the table agreeing with this library 📚 example to simplify the importance of data before AI, else it’s like cart before the horse situation :

It all starts with quality data, the critical lifeline for AI’s to function properly and to weave its magic. Put simply AI needs data that’s findable, accessible, interoperable, and reusable — known as FAIR data. Without it, AI’s ability to learn and improve is severely limited across any application or organization.

Example:

Envision AI as an Intelligent assistant whose intelligence expands with every well-cataloged book it reads from a library.

When the library’s in mess, just like the chaotic bookshops we stumble upon at airports, the assistant struggles.

But with a library where everything is meticulously organized and readily available, our AI assistant learns rapidly, capable of performing faster and better.

With the rising excitement around Generative AI, which can invent new visuals, music, or text, the need for high-quality, FAIR data becomes even more pronounced.

👉And let’s introduce an extra ‘A’ for the ‘Authentic’, or Authenticity, that data producers must guarantee to its consumers.

To unlock AI’s potential as our future problem-solver, our data must be in prime condition. This is a collective mission for anyone, in any field, ELTs and ETLs would not lead us to successful paths but domain oriented authentic data produced by its owners would do.

By committing to FA’A’IR data, we enable AI to evolve from a novel tech phenomenon to a profound force of innovation and companion at our work.

By just putting GenAI on top of cluttered data would remain like garbage in & garbage out!!

So Fix Data, lay down Data Strategy prior to GenAI strategy!!

As per some recent reports (data points):

👉CDOs acknowledge the critical role of data strategy for generative AI success, yet 57% have made no changes to their data to accommodate this, indicating a gap between the importance of data readiness and actual success of AI.

👉 While 80% of CDOs believe generative AI will transform their organizations and 45% foresee widespread adoption, actual preparation is lacking with minimal implementation and a majority only allowing individual experimentation due to lack of quality data.

Q: how do you see Data & AI equilibrium in your organization ??