Data ownership will be the technological battle of 2025
By: Kevin Smith, Partner, Wipfli
Whenever you step into an elevator, check your medical records or track your fitness, that’s data being created, and it could be worth millions. In 2025, the question arises: Who’s profiting from all the data points you’re creating?
A decade ago, there was fierce competition among technology companies to capture your attention. But in recent years, the focus has shifted toward vying for your engagement. Currently, the battle has escalated to a new level as these companies strive to collect your data exhaust, which is the digital footprint you leave behind by simply living in today’s world.
And it’s possible for a single piece of data to be applicable to multiple parties. For example, if an MRI machine is able to enhance its diagnostic capabilities by analyzing thousands of patients, these improvements could be attributed to the hospital, the manufacturer of the device, the AI company responsible for processing the data or even the patients themselves.
As private equity firms hold large sums of uninvested money and AI businesses demand extremely high valuations, the response to our previous inquiry carries immense value. The upcoming wave of technology success will not be determined by those who accumulate the most data, but by those who can identify the true owners of it.
The second mouse gets the cheese
Investors in the technology industry were quick to jump on generative artificial intelligence between 2021 and 2023. However, smart players are now setting their sights on a new goal.
In industries like healthcare and financial services, traditional software-as-a-service companies are discreetly integrating AI into their current products instead of creating showy new tools. They recognize that AI applications that are not tailored to a specific industry are becoming standardized, and the true worth lies in specialized solutions for that particular field.
The private equity industry has experienced a significant increase in “dry powder” reserves. In 2023, the global dry powder in private equity reached an all-time high of $2.59 trillion. While firms have successfully raised large amounts of capital, they have been cautious in investing it due to adjustments in valuations after 2021.
With the convergence of seller and investor expectations, we are reaching a critical turning point for making deals. While there will be an influx of funding for emerging AI startups, seasoned investors are also seeking out companies that have the capability to address genuine business challenges, specifically those related to data privacy and security.
Private equity companies have a particular focus on businesses that have well-defined methods for generating revenue from their data assets. This differs greatly from the previous mindset of prioritizing growth at any expense. Investors are looking for strategies that demonstrate how companies intend to safeguard and capitalize on their data resources while keeping up with changing regulatory demands.
Going from oil wells to data wells
Imagine data as a reserve of oil hidden underground. In the past, corporations would dig deep in a certain location, anticipating a lucrative discovery. However, with advancements in technology, they are now able to extract smaller quantities of data from larger areas — a process more like fracking than conventional drilling.
A company specializing in medical devices could gather diagnostic information from a large number of MRI machines. Similarly, a manufacturer of elevators keeps track of the movements of their products all over the world. A fitness application collects health data from millions of individuals. While each individual data point may not hold much significance, when analyzed together by artificial intelligence, these datasets can uncover patterns such as potential signs of equipment malfunction, previously unnoticed correlations in health or opportunities for predictive maintenance that could lead to cost-saving repairs.
The transition from centralized data collection to decentralized “data fracking” raises new concerns. Who should reap the benefits of an AI system that becomes more proficient in identifying illnesses by examining vast amounts of anonymous patient data? Should it be the hospital that gathered the data, the technology company that developed the model or the patients whose records were used to enable this advancement?
Forward-thinking companies are taking a different approach from relying on massive language models such as GPT-4 to address these inquiries. Instead, they are creating small language models (SLMs) that are trained on exclusive, customized datasets. These specialized artificial intelligence systems may not possess the ability to compose poems or participate in philosophical discussions, but they excel in performing specific tasks within their specific field.
The utilization of specialized artificial intelligence goes beyond improving performance; it also provides a sense of control. By training SLMs on their own data, companies can avoid the risk of their competitive edge being compromised by widely available models. For example, healthcare providers are currently looking into SLMs trained solely on patient data to enhance the precision of diagnoses and treatment suggestions.
SLMs will present a fresh set of cybersecurity concerns to be mindful of. Safeguarding your data becomes critical when it becomes your main source of competitive edge. The traditional approach to cybersecurity mainly focuses on preventing the theft of personal information or financial data. However, businesses must also prioritize safeguarding the distinct datasets that drive their AI systems.
The current state of data rights
The regulations for data ownership are currently not unified. While GDPR is applicable in Europe and there are privacy laws in California, there is still a lack of well-defined structures for profiting from data. For instance, a telecommunications company may collect customer location data. Although the movements of individuals seems insignificant, when the data is anonymized and combined, it becomes extremely valuable for targeted marketing. In case the carrier sells this location data to enhance targeted marketing, who should receive the revenue? Should it be the telecom company that provided the service, the customers whose movements generated the data, or the marketing firms that add value through analysis?
We may not have the answers yet, but savvy businesses are already:
- Conducting audits on data assets in order to gain a comprehensive understanding of their collection methods, sources and ownership.
- Establishing systems to trace the origins and ownership of data.
- Formulating transparent frameworks for monetization that consider the interests of all parties involved.
- Devising effective protocols for anonymizing data to balance its value and safeguard privacy.
- Implementing clear policies regarding the use and monetization of customer data.
In today’s world, technology is constantly evolving, but this does not mean that we cannot identify those who have the ability to transform data rights challenges into advantageous situations. Certain businesses will be able to generate significant profits by establishing data relationships based on trust. However, other companies may suffer as their business strategies crumble due to the loss of data ownership rights and the ability to monetize data.
By 2025, let’s shift our focus from just technology innovation and instead, envision a new concept of fair and ethical data ownership and its practical implementation.
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