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The $9.2 Million Warning

The $9.2 Million Warning: Why 2025 Will Punish Companies That Ignore AI Governance

By R. Skeeter Wesinger
(Inventor & Systems Architect | 33 U.S. Patents | MA)

November 3, 2025

When artificial intelligence began sweeping through boardrooms in the early 2020s, it was sold as the ultimate accelerator. Every company wanted in. Chatbots turned into assistants, copilots wrote code, and predictive models started making calls that once required senior analysts. The pace was breathtaking. The oversight, however, was not.

Now, in 2025, the consequences of that imbalance are becoming painfully clear. Across the Fortune 1000, AI-related compliance and security failures are costing an average of $9.2 million per incident—money spent on fines, investigations, recovery, and rebuilding trust. It’s a staggering number that reveals an uncomfortable truth: the age of ungoverned AI is ending, and the regulators have arrived.

For years, companies treated AI governance as a future concern, a conversation for ethics committees and think tanks. But the future showed up early. The European Union’s AI Act has set the global tone, requiring documentation, transparency, and human oversight for high-risk systems. In the United States, the Federal Trade Commission, the Securities and Exchange Commission, and several state legislatures are following suit, with fines that can reach a million dollars per violation.

The problem is not simply regulation—it’s the absence of internal discipline. IBM’s 2025 Cost of a Data Breach Report found that 13 percent of organizations had already experienced a breach involving AI systems. Of those, 97 percent lacked proper access controls. That means almost every AI-related breach could have been prevented with basic governance.

The most common culprit is what security professionals call “shadow AI”: unapproved, unsupervised models or tools running inside companies without formal review. An analyst feeding customer data into an online chatbot, a developer fine-tuning an open-source model on sensitive code, a marketing team using third-party APIs to segment clients—each one introduces unseen risk. When something goes wrong, the result isn’t just a data spill but a governance black hole. Nobody knows what model was used, what data it touched, or who had access.

IBM’s data shows that organizations hit by shadow-AI incidents paid roughly $670,000 more per breach than those with well-managed systems. The real cost, though, is the time lost to confusion: recreating logs, explaining decisions, and attempting to reconstruct the chain of events. By the time the lawyers and auditors are done, an eight-figure price tag no longer looks far-fetched.

The rise in financial exposure has forced executives to rethink the purpose of governance itself. It’s not red tape; it’s architecture. A strong AI governance framework lays out clear policies for data use, accountability, and human oversight. It inventories every model in production, documents who owns it, and tracks how it learns. It defines testing, access, and audit trails, so that when the inevitable questions come—Why did the model do this? Who approved it?—the answers already exist.

This kind of structure doesn’t slow innovation; it enables it. In finance, healthcare, and defense—the sectors most familiar to me—AI governance is quickly becoming a competitive advantage. Banks that can demonstrate model transparency get regulatory clearance faster. Hospitals that audit their algorithms for bias build stronger patient trust. Defense contractors who can trace training data back to source win contracts others can’t even bid for. Governance, in other words, isn’t the opposite of agility; it’s how agility survives scale.

History offers a pattern. Every transformative technology—railroads, electricity, the internet—has moved through the same cycle: unrestrained expansion followed by an era of rules and standards. The organizations that thrive through that correction are always the ones that built internal discipline before it was enforced from outside. AI is no different. What we’re witnessing now is the transition from freedom to accountability, and the market will reward those who adapt early.

The $9.2 million statistic is less a headline than a warning. It tells us that AI is no longer a side project or a pilot experiment—it’s a liability vector, one that demands the same rigor as financial reporting or cybersecurity. The companies that understand this will govern their algorithms as seriously as they govern their balance sheets. The ones that don’t will find governance arriving in the form of subpoenas and settlements.

The lesson is as old as engineering itself: systems fail not from lack of power, but from lack of control. AI governance is that control. It’s the difference between a tool that scales and a crisis that compounds. In 2025, the smartest move any enterprise can make is to bring its intelligence systems under the same discipline that made its business succeed in the first place. Govern your AI—before it governs you.

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DeepSeek’s Mind-Blowing AI Solution Caught in a Cover-Up?

DeepSeek, a rising CCP AI company, was under siege. The company’s official statement, issued in careful, bureaucratic phrasing, spoke of an orchestrated “distributed denial-of-service (DDoS) attack” aimed at crippling its systems. A grave and urgent matter, to be sure. Yet, for those who had followed the firm’s meteoric rise, there was reason for skepticism

DeepSeek had, until this moment, presented itself as a leader in artificial intelligence, one of the few entities capable of standing alongside Western firms in the increasingly cutthroat race for dominance in machine learning. It was a firm backed, either openly or in whispered speculation, by the unseen hand of the Chinese state. The company’s servers, housed in mainland China, were reportedly fueled by NVIDIA H800 GPUs, their interconnections optimized through NVLink and InfiniBand. A formidable setup, at least on paper

But then came the curious measures. Whole swaths of IP addresses, particularly from the United States, were unceremoniously blocked. The platform’s registration doors were slammed shut. And in the vague, elliptical style of official Chinese pronouncements, the public was assured that these were emergency steps to preserve service stability. What the company did not say—what they could not say—was that these actions bore all the hallmarks of a hasty retreat, rather than a tactical defense

For a true DDoS attack—one launched by sophisticated adversaries—there were measures to mitigate it. Content delivery networks. Traffic filtering. Rate-limiting techniques refined over decades by those who had fought in the trenches of cybersecurity. Yet DeepSeek’s response was not one of resilience, but of restriction. They were not filtering the bad actors; they were sealing themselves off from the world

A theory began to take shape among industry watchers. If DeepSeek had overestimated its own technological prowess, if its infrastructure was ill-prepared for rapid growth, the sudden influx of new users might have looked, to their own internal systems, like an attack. And if the company was not merely a commercial enterprise but an entity with deeper ties—perhaps to sectors of the Chinese government—it would not do to admit such failings publicly. To confess that their AI could not scale, that their systems could not bear the weight of global interest, would be an unpardonable humiliation.

The consequences of such a revelation would be severe. The markets had already felt the tremors of cyberattacks; the global economy had bled $1.5 trillion due to disruptions of this nature. If DeepSeek, a firm hailed as the vanguard of China’s AI ambitions, was faltering under its own weight, the financial and political repercussions would extend far beyond the walls of its server farms. The illusion of invulnerability had to be maintained

Thus, the narrative of a “DDoS attack” was not merely convenient—it was necessary. It allowed DeepSeek to take drastic action while obscuring the truth. Blocking foreign IPs? A countermeasure against cyber threats. Suspending new users? A precaution against infiltration. A firm whose technological backbone was more fragile than its reputation suggested had suddenly found an excuse to withdraw from scrutiny under the guise of self-defense

It is in such moments that history leaves its telltale fingerprints. The annals of technological development are filled with entities that stumbled not due to sabotage, but due to their own shortcomings, concealed under layers of propaganda and misdirection. One wonders if, years from now, when the documents are unsealed and the real story emerges, historians will look back at DeepSeek’s so-called DDoS crisis not as an act of foreign aggression—but as a moment of revelation, when the cracks in the edifice became too great to hide

Also, the DeepSeek app has been removed from both Apple’s App Store and Google’s Play Store in Italy. This action occurred after Italy’s data protection authority, known as the Garante, requested information from DeepSeek regarding its handling of personal data. Users attempting to access the app in Italy received messages indicating that it was “currently not available in the country or area you are in” on Apple’s App Store and that the download “was not supported” on Google’s platform. As reported by REUTERS.CO

Regarding Ireland, the Irish Data Protection Commission has also reached out to DeepSeek, seeking details about how it processes data related to Irish users. However, as of now, there is no confirmation that the app has been removed from app stores in Ireland. As reported by THEGUARDIAN.COM

Currently there is no publicly available information indicating that DeepSeek has specifically blocked access from Apple, Google, or individual reporters’ servers. It’s possible that access issues could be related to the broader measures DeepSeek has implemented in response to recent events, but without specific details, it’s difficult to determine the exact cause.

For now, the truth remains elusive, hidden behind digital firewalls and the careful hand of censorship. But as in all such cases, history is patient. It waits for those who will dig deeper, who will look beyond the official statements and ask: Was it an attack? Or was it something else entirely?

Story By Skeeter Wesinger

January 30, 2025

 

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Chinese-Made Air Fryers Raise Alarms Over User Data Collection

Recent investigations have raised concerns about certain Chinese-made smart devices, including air fryers, collecting excessive user data without clear justification. A report by the UK consumer group Which? found that smart air fryers from brands like Xiaomi and Aigostar request permissions to access users’ precise locations and record audio via their associated smartphone apps. Additionally, these devices may transmit personal data to servers in China and connect to advertising trackers from platforms such as Facebook and TikTok’s ad network, Pangle.

These findings suggest that the data collected could be shared with third parties for marketing purposes, often without sufficient transparency or user consent. The UK’s Information Commissioner’s Office (ICO) plans to introduce new guidelines in spring 2025 to enhance data transparency and protection for consumers.

In response to these concerns, Xiaomi stated that it adheres to all UK data protection laws and does not sell personal information to third parties. The company also mentioned that certain app permissions, such as audio recording, are not applicable to their smart air fryer, which does not operate through voice commands.

These revelations highlight the importance of consumers being vigilant about the data permissions they grant to smart devices and the potential privacy implications associated with their use. While companies like Huawei and others are facing scrutiny over data privacy concerns, they have consistently defended their practices by emphasizing their adherence to local and international regulations. General Data Protection Regulation (GDPR): In the EU, Huawei highlights compliance with GDPR standards, which are among the most stringent globally. Huawei asserts adherence to national laws and specific security frameworks.

By Skeeter Wesinger

December 16, 2024

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Dominion Voting Systems and the DVSorder Affair A Saga in American Election Security

In early 2024, a team of researchers at the University of Michigan and Auburn University stumbled upon an overlooked flaw in Dominion’s Democracy Suite voting system. The flaw, astonishing in its simplicity, harked back to the 1970s: a rudimentary linear congruential generator for creating random numbers, a method already marked as insecure half a century ago. Yet there it lay, embedded in the heart of America’s election machinery. This flaw, known as DVSorder, allowed the order of ballots to be exposed, violating a voter’s sacred right to secrecy without needing inside access or privileged software.

Dominion Voting Systems responded, as companies often do, with carefully measured words—a single-page advisory noting that “best practices” and “legal advisors” could mitigate the flaw. A software update, Democracy Suite 5.17, was eventually rolled out, claiming to resolve the vulnerability. Yet this patch, touted as a “solution,” seemed only to deepen the questions surrounding Dominion’s response. Was it a fix, or merely a stopgap?

A Bureaucratic Response: The Slow March of Democracy Suite 5.17

The U.S. Election Assistance Commission granted its stamp of approval to Democracy Suite 5.17 in March 2023, seemingly content with its certification. But the rollout that followed revealed the entrenched and fragmented nature of America’s election infrastructure. Election officials, bound by local constraints, cited logistical challenges, costs, and the impending presidential election as reasons to delay. In the absence of federal urgency or clear guidance from the Cybersecurity and Infrastructure Security Agency (CISA), the vulnerability remained in effect, a silent threat from Georgia to California.

Even as researchers watched from the sidelines, Dominion and federal agencies moved cautiously, with state adoption of Democracy Suite 5.17 proceeding at a glacial pace. Some states, like Michigan and Minnesota, made efforts to upgrade, but others deferred, considering the patch a burden best shouldered after the election. Thus, the DVSorder vulnerability persisted, largely unresolved in precincts where patching was deemed too disruptive.

The Patchwork of Democracy Suite 5.17: A System in Pieces

As expected, Democracy Suite 5.17 encountered obstacles in deployment, emblematic of the fractured approach to American election security. States such as Michigan tried to sanitize data to safeguard voter privacy, but the result was incomplete; others attempted to shuffle ballots, a solution whose effectiveness remained dubious. The whole exercise appeared as a microcosm of America’s approach to its electoral machinery: decentralized, hesitant, and all too often compromised by cost and convenience.

A Sobering Reminder for Democracy’s Future

The DVSorder affair serves as a reminder that elections, despite their image of order, depend on fallible human governance and systems. In this case, a mere oversight in programming triggered a vulnerability that risked eroding voter privacy, a cornerstone of democracy itself. Dominion’s response, slow and bureaucratic, reveals the unsettling reality that our reliance on technology in elections opens doors to errors whose repercussions may be profound.

The researchers who exposed this flaw were not saboteurs but, in a sense, stewards of public trust. They brought to light a sobering truth: that in the age of digital democracy, even the smallest vulnerability can ripple outward, potentially undermining the promises of privacy and integrity on which the system stands.

As the dust settles, DVSorder may join the list of vulnerabilities patched and closed, yet a shadow lingers. With each election cycle, new threats and oversights emerge, casting a faint but persistent question over the future of American democracy. One wonders—will we be ready for the next vulnerability that arises? Who knows.

By Skeeter Wesinger

November 4, 2024

 

https://www.linkedin.com/pulse/dominion-voting-systems-dvsorder-affair-saga-american-wesinger-i4qoe

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