Pictured: Tomy Han, Partner at Volition Capital
Long term success in AI hinges on one variable: data. As foundational AI models become more accessible and standardized, the key to differentiation will lie in how these models are applied and integrated into specific workflows and industries. Data is not just a resource for powering AI; it is the foundation for refining and optimizing AI’s ability to deliver actionable, context-specific insights.
Physical Data is Challenging
We live in a world where digital data is abundant. We’ve been slicing and dicing it for decades looking for insights and driving predictions. Whether it’d be transaction data to detect fraud or ad spend data for marketing attribution, we’ve been producing and storing a lot of it; and we are only beginning to understand how to fully utilize them in the context of AI.
The story is different when it comes to physical data. Unlike digital data, physical data is not as readily available and is far more challenging to collect. Its capture often requires a complex ecosystem that includes hardware, connectivity, and human involvement, coupled with an infrastructure layer underneath to store and refresh this. This is an expensive and time-consuming task; there’s a reason why the Google Maps street view of your house has not changed in years.
Physical Data is a New Frontier
When founders of Hardware-Enabled SaaS businesses ask, “What’s your perspective on AI in the space?” our response is consistent: it’s all about the data. It represents an untapped frontier where the convergence of hardware, connectivity, and AI can create unparalleled value. As connected hardware becomes easier to develop and deploy, a virtuous cycle emerges: increased adoption of connected hardware leads to more physical data collection, which in turn enables vendors to refine their offerings or act as gateways to this data.
For Hardware-Enabled SaaS businesses, the path to leveraging AI begins with capturing data at scale. The form this data takes, be it video, LIDAR, or sensor readings, requires continual innovation in interpretation and application. Businesses must strategically prioritize retaining and leveraging their data, as it could become their most significant competitive advantage. In the long term, the value of physical data, with its unique insights into the real world, has the potential to surpass that of digital data – and the opportunity is for the taking.
