Why Proprietary Data Is the Linchpin of AI Disruption

Why Proprietary Data Is the Linchpin of AI Disruption

‍Vivek Vaidya Writes in Chief Data Officer Magazine:

As AI reshapes the business landscape, the true kingmakers are not the models themselves, but the quality and exclusivity of the data powering them. A tech revolution like AI unleashes rapid change, and not every firm or job will survive.

While the large firms creating massive AI models, such as OpenAI and Anthropic, undoubtedly have a good shot at success, the rest of the businesses that innovate, compete, and profit from this revolution will be the ones with the best data and not the best models.

What defines “better” data? That is entirely subjective. Better data for your company is confidential, copyrighted, personal, or otherwise exclusive and tailored for your industry or use case. We call this “proprietary data,” and it is nothing new.

I’ve been an entrepreneur and CTO since the dotcom era when machine learning (ML) was synonymous with statistics, and proprietary data has always been at the heart of my business models.

One lesson I’ve learned from successfully building multiple data+AI companies is that simply owning a proprietary data asset is not enough. For example, a medical institution may use its proprietary patient data, medical records, and treatment outcomes to build Generative AI applications to assist clinicians. Publishing companies may create personalized learning applications using their proprietary content available in books, articles, and images.

Time and time again, I come back to famed computer scientist Peter Norvig’s axiom: “More data beats better algorithms, but better data beats more data.” It’s time business leaders take this to heart, too.

The most competitive firms in the age of AI will have “better data.” They will understand and segment data by quality before feeding it into a model and evaluate the new model's performance after the fact. Crucially, a collaborative culture will elevate a firm's capacity to fully exploit proprietary data in this evolving landscape of data-centric AI.

Stakeholders must stay aligned toward the business goal while ensuring the AI solution is robust, ethical, and unbiased.

Read the rest of the article in Chief Data Officer Magazine

Learn about MarkovML, a data-centric AI company where Vivek is CEO, here.