Artificial Intelligence and the New Rules of Business Data Sharing
The development of artificial intelligence (AI) has radically shifted how the software market approaches customer data. While programs once simply processed information, they now learn from it. This evolution forces companies to confront a difficult question: is it ethical to use insights derived from one client's data to improve products for others, including their direct competitors?
The Legacy of Data Cooperatives
During the 1990s, the retail sector relied on so-called data cooperatives. Companies shared transaction histories to better identify potential buyers. The integrity of this system rested on strict rules: those who shared data gained benefits, while those who stopped contributing automatically lost access to the collective database. Today’s AI services often attempt to implement similar principles, yet frequently do so with opaque rules.
The HubSpot Lesson and Customer Backlash
HubSpot recently attempted to introduce a model where client data would be automatically aggregated across the platform to improve prospecting tools. Although the company held the legal right to do so, customers reacted with intense protest. Businesses did not want their hard-earned, curated data used for free to strengthen their own competitors. Consequently, HubSpot retreated, announcing that such features would only be activated with explicit user consent (opt-in).
Why This Remains a Problem
According to a 2026 McKinsey study, only 30% of organizations have established AI strategies and control mechanisms. Many software companies are inadvertently becoming "data companies." When one client’s data trains an AI model, that information becomes an inseparable part of the model. Even if a client terminates their contract and deletes their records, the model—refined by that data—continues to function.
What Awaits the Market?
In the future, customers and their procurement departments will impose stricter requirements on vendors. The primary question is no longer just "where is the data stored," but rather "what benefit do I receive if I allow my data to be used for model training?" In the near term, contracts that clearly define the data economy will become standard: specifying what data is used, what results the model produces, and what compensation or benefit the data provider receives.
For companies operating in Georgia that utilize global SaaS platforms, it is essential to carefully review terms of service. Businesses that regulate data exchange transparently and fairly will gain a competitive advantage, as trust is becoming the most valuable currency in the era of artificial intelligence.