Somewhere around the turn of the century, and the decades following, the smokestack economy become the connected economy.
Connected vehicles, industrial equipment and warehouse devices today generate continuous streams of behavioral, operational and location data. That information can support subscription services, predictive maintenance, product development and new commercial partnerships.
The Thursday (Oct. 29) announcement that General Motors has agreed to pay $220 million to settle allegations from 36 state-level jurisdictions that it improperly shared drivers’ behavioral and location information with data brokers, however, shows how that same connectivity can also create liabilities that outlast the revenue those arrangements generate.
Following the news of the settlement, on Monday (Nov. 2), Ford Motor Company introduced a new company Privacy Promise, pledging not to sell customers’ driving-behavior data to brokers and providing clearer information about how vehicle data is collected, used and controlled.
Together, the developments raise a question for manufacturing CFOs well beyond the automotive sector: What happens to the economics of connected products when the information they generate becomes more expensive to monetize than to collect?
Read more: CFOs Become the Source of Truth as Data Sprawls Across B2B
Accounting for the Hidden Liabilities in Recurring Data Revenue
Catherine Tucker, professor of management at MIT Sloan, shared with Competition Policy International (CPI), a PYMNTS company, in a recent interview how privacy rules will help shape the AI industry.
But the manufacturing industry is already being shaped by those rules, as well as the advent of AI. GM’s settlement illustrates how quickly a connected-service business model can acquire liabilities outside its original financial assumptions.
The controversy is centered on driving information collected through GM’s Smart Driver program and subsequently shared with data brokers, including companies that supplied information to insurers. The issue was not simply that vehicle data had commercial value. It was that information collected through a consumer-facing service could ultimately influence financial decisions affecting those same consumers.
A connected product may generate information at relatively little incremental cost. But every additional intermediary introduces questions about consent, permitted use, contractual responsibility and downstream accountability. In an era of porous cyber perimeters, CFOs can no longer afford to treat operational and third-party data alike as an IT silo.
And unlike a defective physical component, problematic data practices can affect millions of customers simultaneously, potentially extending across jurisdictions and commercial relationships.
“In 2021, there were 400 data breach lawsuits filed,” Philip Yannella, co-chair of the privacy, security and data protection practice at Blank Rome and the author of “Cyber Litigation: Data Breach, Data Privacy & Digital Rights,” 2025 edition, told PYMNTS. “Last year, there were over 2,000.”
See also: Small Businesses Skip the Cross-Border Plumbing Big Companies Can’t Escape
The Next Data Valuation Problem for the Connected Economy
The implications extend beyond automobiles. Industrial machinery generates operational information useful to maintenance providers, insurers and equipment financiers. Smart appliances produce consumption data that may interest utilities and retailers. Connected medical and agricultural equipment can create commercially valuable insights long after the original sale.
Ford’s pledge is not proof that privacy restraint produces superior financial returns. GM’s settlement does not mean third-party data partnerships are inherently uneconomic. But the ability to collect data no longer guarantees the ability to profit from it, just as the ability to sell information does not establish that doing so represents its highest-value use.
Manufacturers have spent years trying to extend the revenue-generating life of physical products. The next challenge is ensuring those recurring revenue streams do not carry liabilities that outlive their profitability.
For CFOs, the most important question may no longer be how much customer data their products generate. It is how much economic value the business can retain without surrendering control of what happens to that data next.
Finance leaders can also examine how much projected revenue depends on permissions that customers can revoke, intermediaries the manufacturer cannot fully supervise or data uses vulnerable to regulatory restrictions.
As for AI, the technology has expanded what teams can develop internally without a third party, Boost Payment Solutions Founder and CEO Dean M. Leavitt wrote in a new PYMNTS eBook, “Payments Leaders Rethink What Works in 2026.”
The PYMNTS Intelligence report “The Enterprise AI Payback Curve: Adoption Accelerates as Returns Take Shape,” published in August, found that firms in the financial services, healthcare and media sectors rate AI a success and have pushed payback expectations out five to six years.
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