Somewhere across the flip of the century, and the many years following, the smokestack economic system turn out to be the related economic system.
Connected autos, industrial tools and warehouse units right this moment generate steady streams of behavioral, operational and site information. That info can help subscription companies, predictive upkeep, product growth and new business 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 site info with information brokers, nonetheless, exhibits how that very same connectivity may also create liabilities that outlast the income these preparations generate.
Following the information of the settlement, on Monday (Nov. 2), Ford Motor Company launched a brand new firm Privacy Promise, pledging to not promote prospects’ driving-behavior information to brokers and offering clearer details about how automobile information is collected, used and managed.
Together, the developments increase a query for manufacturing CFOs properly past the automotive sector: What occurs to the economics of related merchandise when the knowledge they generate turns into costlier to monetize than to gather?
Read extra: CFOs Become the Source of Truth as Data Sprawls Across B2B
Accounting for the Hidden Liabilities in Recurring Data Revenue
Catherine Tucker, professor of administration at MIT Sloan, shared with Competition Policy International (CPI), a PYMNTS firm, in a recent interview how privateness guidelines will assist form the AI trade.
But the manufacturing trade is already being formed by these guidelines, in addition to the arrival of AI. GM’s settlement illustrates how rapidly a connected-service enterprise mannequin can purchase liabilities exterior its unique monetary assumptions.
The controversy is centered on driving info collected by means of GM’s Smart Driver program and subsequently shared with information brokers, together with corporations that equipped info to insurers. The situation was not merely that automobile information had business worth. It was that info collected by means of a consumer-facing service may in the end affect monetary selections affecting those self same shoppers.
A related product might generate info at comparatively little incremental price. But each extra middleman introduces questions on consent, permitted use, contractual duty and downstream accountability. In an period of porous cyber perimeters, CFOs can now not afford to deal with operational and third-party information alike as an IT silo.
And in contrast to a faulty bodily element, problematic information practices can have an effect on tens of millions of consumers concurrently, doubtlessly extending throughout jurisdictions and business relationships.
“In 2021, there were 400 data breach lawsuits filed,” Philip Yannella, co-chair of the privateness, safety and information safety observe at Blank Rome and the creator of “Cyber Litigation: Data Breach, Data Privacy & Digital Rights,” 2025 edition, told PYMNTS. “Last year, there were over 2,000.”
See additionally: Small Businesses Skip the Cross-Border Plumbing Big Companies Can’t Escape
The Next Data Valuation Problem for the Connected Economy
The implications lengthen past vehicles. Industrial equipment generates operational info helpful to upkeep suppliers, insurers and tools financiers. Smart home equipment produce consumption information which will curiosity utilities and retailers. Connected medical and agricultural tools can create commercially priceless insights lengthy after the unique sale.
Ford’s pledge isn’t proof that privateness restraint produces superior monetary returns. GM’s settlement doesn’t imply third-party information partnerships are inherently uneconomic. But the power to gather information now not ensures the power to revenue from it, simply as the power to promote info doesn’t set up that doing so represents its highest-value use.
Manufacturers have spent years attempting to increase the revenue-generating lifetime of bodily merchandise. The subsequent problem is making certain these recurring income streams don’t carry liabilities that outlive their profitability.
For CFOs, crucial query might now not be how a lot buyer information their merchandise generate. It is how a lot financial worth the enterprise can retain with out surrendering management of what occurs to that information subsequent.
Finance leaders may also look at how a lot projected income will depend on permissions that prospects can revoke, intermediaries the producer can’t totally supervise or information makes use of weak to regulatory restrictions.
As for AI, the expertise has expanded what groups can develop internally and not using a third get together, Boost Payment Solutions Founder and CEO Dean M. Leavitt wrote in a brand 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,” revealed in August, discovered that corporations within the monetary companies, healthcare and media sectors price AI successful and have pushed payback expectations out 5 to 6 years.
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