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Home Daily News Roundup Keeping AI Costs In Check; Selling Your Data To The Highest Bidder

Daily News Roundup
Keeping AI Costs In Check; Selling Your Data To The Highest Bidder By AdExchanger

Tuesday, September 8th, 2026 – 12:03 am
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Token For A Ride
AI can help cut costs, but only if it has a babysitter. 
Roughly 60% of companies that use AI will incur unexpected charges and/or exceed their allocated budgets due to a lack of human oversight, according to a Gartner survey of 1,300 senior marketers. The survey also found that more than half (56%) of companies that use AI tools implemented them without clear policies. (So much for that whole “human in the loop” thing.)
Rather than risk flushing more money down the toilet, media agencies are developing their own auditing tools to rein in AI token costs, Digiday reports.
PMG, for example, built a tool that lets users limit AI token usage and, based on how often they enforce limits, offers certain recommendations. Another example is Rise, a performance agency that’s part of Quad. Rise uses an audit log feature from the SSP PubMatic that tracks when buying agents drift outside the guidelines they were given. But Rise still has to estimate the costs of its agentic testing itself, including how much of its campaign budgets went toward working media.
It looks like it’ll take some more time before agencies feel they can fully entrust their operations to AI agents in the pursuit of efficiency.
Dangerous Data Deals
Google has a new competitor in the bidding war for Spirit Airlines’ treasure trove of data.
AI startup micro1 says it will pay $12.5 million for the defunct airline’s records, topping Google’s $10 million bid, Bloomberg reports.
Google won Spirit’s data pool – which includes 500 million Microsoft Teams communications, 100 million emails and 16 million customer support chats – in a bankruptcy auction last month. But the deal has faced plenty of criticism from privacy advocates who worry about Google’s plans for the data.
Micro1 says it can scrub identifying information from Spirit’s records. Google similarly promises to strip out personal information tied to Spirit’s customers. But, quibbles over who would be a better steward of the data aside, micro1 faces an uphill battle in getting Google’s already-approved deal overturned.
While the Spirit auction has raised new concerns over what happens to a company’s data once it goes out of business, it’s not the only recent example of the dangers of companies’ hoards of personal data potentially falling into the wrong hands.
The FBI is investigating a dark web service called Nexus that claims to have hacked more than 153 million drivers license scans from ID verification vendor IDScan.net, Krebs on Security reports.
The ID verification business has exploded as global regulators pass laws requiring age verification to access social media and adult content. But, as Gizmodo notes, the Nexus hack “shows the danger of creating honey pots of our most sensitive documents for malicious actors to exploit.”
No Such Thing As An AI-Generated Lunch
Why does AI-generated food tend to look so unappetizing? According to The Verge, it often boils down to the same issue your picky toddler might have with mealtime: textures.
Certain non-repetitive structures that are common in food, such as bubbles, seeds and thin noodles, are difficult for diffusion models to replicate, behavioral scientist Giovanbattista Califano tells The Verge. 
Also, some of the available training data on the internet trends more toward the unusual. As a result, an AI model – which doesn’t know what a plate of shrimp scampi is supposed to look like – might end up generating something uncanny or surreal, like fully circular shrimp.
Which poses a problem for the exact kinds of small and local businesses being courted by the digital advertising industry. Lots of self-serve ad platforms, like MNTN, Streamer.ai and Amazon, offer AI image and video generation tools to businesses that can’t afford to hire their own marketing and design teams. 
But if restaurants don’t feel confident that those AI-generated assets will be of a high enough quality to entice customers – or worse, if they start seeing a downturn in sales after using the “nightmare fuel” imagery in their flyers and Instagram reels anyway – then why use the product at all?
But Wait! There’s More!
Why the Google remedies decision should matter to everybody, not just ad tech insiders. [Tech Policy Press] 
The Trade Desk lays off 15% of its staff following its disappointing Q2 earnings. The company has also been removed from the S&P 500. [PPC Land]
In a major blow to Omnicom, PepsiCo shifts its $1.7 billion global media account to Publicis. Also, Publicis has withdrawn from pursuing Coca-Cola’s global media account, but – for now – it still holds Coke’s $700 million US media business, which it won from WPP last year. [The Drum]
Instagram’s automatic AI detection tool is still kind of a mess. [The Verge]
You’re Hired!
Abi Evans joins Omnicom Advertising to lead growth and new business, leaving her prior role as global chief growth officer at Dentsu Creative. [Ad Age]
KFC hires Amy Ellis Durini as global chief brand officer. [release]

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The landscape of advertising technology is currently grappling with the financial implications and ethical challenges arising from the integration of artificial intelligence and the concentration of personal data. Media agencies are actively developing internal auditing tools to control the escalating costs associated with utilizing AI, recognizing that a significant portion of companies using AI incur unexpected charges due to insufficient human oversight, evidenced by surveys indicating that over half of organizations implemented AI tools without establishing clear policies. This drive for cost control is prompting the creation of solutions; for instance, entities like PMG have developed tools allowing users to limit AI token usage and receive recommendations based on enforcement frequency, while performance agencies such as Rise are utilizing audit logs from supply-side platforms to track deviations from established guidelines, although estimating the costs associated with agentic testing remains a challenge.

Simultaneously, the handling and ownership of vast datasets present significant privacy and security risks. A notable example is the recent auction where Google secured Spirit Airlines’ data pool through a bankruptcy process, which included substantial communications data. While external entities like micro1 bid for this data to compete with Google, concerns persist among privacy advocates regarding the potential misuse of such concentrated personal information. This issue is compounded by broader security vulnerabilities, illustrated by investigations into dark web services that exploit leaked driver’s license scans obtained from ID verification vendors, demonstrating the danger of creating repositories of sensitive documents exploitable by malicious actors.

The quality of AI-generated media also presents a critical commercial hurdle, particularly for businesses in the digital advertising sector. Experts note that current diffusion models struggle to replicate certain physical properties inherent in food imagery, such as textures like bubbles or thin noodles, which can lead to outputs that are uncanny or surreal rather than appetizing. This gap between desired and generated quality poses a risk for small and local businesses seeking to use AI image and video generation tools for marketing materials. If these generated assets fail to entice customers or lead to sales downturns, the utility of the technology is diminished.

Beyond these specific technological concerns, major industry shifts are reshaping the advertising ecosystem. There have been significant financial reorganizations, including The Trade Desk laying off staff following poor earnings and being delisted from the S&P 500, as well as substantial media account shifts, such as PepsiCo moving its global media business to Publicis. These operational changes occur amidst ongoing legal disputes; for example, the Federal Trade Commission’s lawsuit against Amazon highlights the historical opacity within programmatic ad auctions and suggests that the lack of transparency in the system is being further challenged by buy-side experts regarding platform advantages in the advertising technology domain. Furthermore, the proliferation of AI tools deepens broader concerns about data stewardship as companies continue to accumulate personal information across various sectors.