What 6 Corporate Scandals Reveal About Enterprise Governance

Technology can generate huge value but only if its claims, controls and risks are properly verified and tested. In some of the most infamous corporate failures, ambitious promises were too easily embraced, warning signs were overlooked, and accountability weakened under pressure to grow quickly.

For enterprise technology leaders, these risks are becoming harder to manage as technological change accelerates. AI systems, cloud platforms and outsourced software introduce dependencies that can be difficult to assess, challenge or replace when problems arise. A system may appear to be performing well while concealing unreliable data, weak controls, supplier instability or failure modes that only become apparent when the damage has already been done.

Regulation is also increasingly reflecting this reality. The EU AI Act (which determines the requirements for certain AI systems), the NIS2 Directive and the Digital Operational Resilience Act (DORA) all reinforce the importance of proper risk assessment, accountability, cybersecurity and operational resilience. Adhering to compliance requirements on its own can’t prevent every failure, but it can still help organisations ask better questions before problems become embedded in the company culture.

The following cases, from Theranos, Enron and Boeing to FTX, Post Office Horizon and Builder.ai, show how unchecked ambition and weak governance can turn normally manageable risks into major failures. More importantly, they all reveal practical lessons for organisations looking to test technology claims, challenge decisions, strengthen governance practices and respond effectively when systems or suppliers fall short. 

1. Theranos: When the Promise Outruns the Technology

Health technology company Theranos, founded in 2003 by Stanford University dropout Elizabeth Holmes, promised to change blood testing in its traditional form. With proprietary devices (nicknamed ‘Edisons’), they would be able to run numerous tests using only a few drops of blood instead of full vials.

The carefully cultivated image of Theranos extended to Holmes herself. She became known for her stark black turtlenecks, deliberately echoing the style of Apple's Steve Jobs, and her unusually deep speaking voice. There’s speculation that she deliberately lowered her voice to appear more authoritative, which may have helped her be more convincing to investors.

Her look and confident demeanour helped position her as a visionary who could change healthcare as a whole. But the public narrative of the company was light years ahead of what the technology could reliably do.

Holmes attracted high-profile investors, including Rupert Murdoch and Henry Kissinger, and secured a partnership with pharmacy chain Walgreens. However, Theranos struggled to deliver on its promises. Despite claims that its technology could perform a wide range of tests using just a few drops of blood, the company continued to rely on conventional laboratory analysers for many tests.

The contrast between Theranos’s public claims and its actual capabilities came into focus during a 2015 visit by then-US Vice President Joe Biden. Holmes showed him the company’s manufacturing and testing facilities, describing them as a “laboratory of the future”. Former employees later alleged that the tour was staged, with some devices displaying videos rather than conducting actual tests.

In 2018, the US Securities and Exchange Commission (SEC) filed fraud charges against Theranos, Holmes and former president Ramesh “Sunny” Balwani for making misleading statements about the company's technology and business operations. Holmes was later convicted of investor-related fraud offences and, as of 2026, she is still incarcerated. She is even the topic of a highly praised documentary, “You Can See Everything”, that followed Holmes and her husband in the days leading up to her going to prison.

What Theranos teaches enterprises

1. Test technology at scale

New technologies need to be proven independently in real-world conditions. No amount of demonstrations and high-flying promises can replace proven performance.

2. Reputation is no proof

Boards, investors and technology buyers must question claims, not take them at face value because of a founder's credibility or a company's reputation.

3. Defend those who voice concerns

Employees with inside knowledge need safe ways to report problems, especially when those problems involve senior and influential leaders or strategically important projects.

Innovation needs to be proven. Extraordinary claims require extraordinary evidence, as Carl Sagan famously said.

2. Enron: When Financial Complexity Hides The Truth

Enron, an energy, commodities and services company, was once the seventh-largest company in the United States and named the most innovative company six years running by Fortune magazine. It was a giant in the industry, generating billions in yearly revenue prior to its fall from grace.

Behind its strong reputation, Enron used complex accounting methods and transactions with related companies to hide debt and make its finances look healthier than they were. Its auditor, Arthur Andersen LLP, also faced criticism for its role in the scandal.

As Enron’s finances became harder to understand, its reputation for innovation helped maintain investor confidence. Many saw the company’s complex business dealings as a sign of sophistication rather than a reason to question its financial health.

When Enron filed for bankruptcy in December 2001, shareholders lost billions, while employees lost their jobs and much of their retirement savings. The collapse was a major impetus for changes to US corporate reporting and audit requirements, including the Sarbanes-Oxley Act of 2002. The troubled company's collapse shows how a strong reputation can hide serious problems. Its apparent success could not make up for inaccurate financial reporting and weak internal controls.

What Enron teaches enterprises

1. Be transparent about complexities

Enterprise leaders should be able to explain financial exposures, technological dependencies and operational risks in terms that make it easy for independent reviewers to scrutinise.

2. Keep independent oversight

Boards, auditors and risk teams need the know-how, access and authority to question management without there being a conflict of interest.

3. Move beyond headline metrics

Don’t just place the spotlight exclusively on revenue growth and profitability but also look at liabilities, cash flow and the assumptions behind the numbers.

If leaders aren’t able to clearly articulate the organisation’s financial position or risks, that lack of visibility should warn of a governance problem.

3. FTX: When a Charismatic Founder Becomes the Control System

FTX was a major cryptocurrency exchange co-founded by Sam Bankman-Fried and Gary Wang that attracted big investment and customers before it collapsed in November 2022, just 3 years after the company was founded.

The collapse revealed serious governance failures and the misuse of customer funds. In 2024, a U.S. federal court ordered $12.7 billion in monetary relief against FTX and Alameda Research in a lawsuit filed by the Commodity Futures Trading Commission.

Bankman-Fried’s casual style and oddball attitude helped differentiate him from your average finance exec. He was apparently playing the game League of Legends on a fundraising video call with venture capital firm Sequoia Capital while simultaneously pitching FTX's ambitious vision. The anecdote, which appeared in Sequoia’s own profile of the founder, demonstrates how his unconventional personality became part of the appeal of the company.

But this appeal was coupled with serious weaknesses in financial controls. Incoming CEO John Ray III said the collapse of FTX revealed extraordinary failures in corporate controls and reliable information about its finances.

What FTX teaches enterprises

1. Don’t let a single person become the point of failure

Important decisions and controls shouldn’t depend on only the judgement or goodwill of a founder or CEO.

2. Trust needs operational controls

Access to customer data, funds and critical systems should be governed by clear permissions, audit trails and independent checks.

3. Change governance with the business

Finance, compliance, cybersecurity and internal audit should evolve with commercial growth, not in reaction to problems.

The controls shouldn’t be attached to leadership, and shouldn’t substitute trust in individuals.

4. Boeing 737 MAX: When Commercial Pressures Trump Safety

Two Boeing 737 MAX aircraft crashed in 2018 and 2019, killing 346 people. Investigations identified serious problems with the aircraft’s Manoeuvring Characteristics Augmentation System (MCAS), which was designed to activate during manual flight to push the aircraft’s nose down.

However, the system initially relied on a single angle-of-attack sensor. That sensor began giving incorrect readings, so MCAS would activate again and again. This would automatically push the aircraft’s nose down, making it difficult for pilots to maintain control.

A 2020 US House investigation found that commercial pressures, flawed assumptions about MCAS’ abilities and poor communication all played a major role in the crisis. Boeing had tried to reduce the need for additional simulator training for pilots transitioning from older 737 models and had failed to adequately inform pilots about MCAS and its operation.

The probe also uncovered lapses in Boeing’s communications with regulators and questions about the process to certify the plane. Together, these findings illustrated how commercial pressures and inadequate technical oversight can compromise safety.

What Boeing teaches enterprises

1. Define stop conditions

There should be the ability to stop or halt projects when critical risks remain unresolved, even when deadlines or revenue targets are looming.

2. Question technical assumptions

AI and automation in particular should be tested for potential faulty inputs, unexpected interactions and situations in which human operators need to intervene.

3. Go beyond minimum compliance

Meeting a formal compliance requirement doesn’t automatically mean a system is safe, resilient or well-understood by the people using it regularly.

The focus on delivery targets should never outweigh the need to understand and manage the risks of a system.

5. Post Office Horizon: When Software Output Is Treated as the Truth

The UK Post Office Horizon scandal shows what can happen when an organisation treats software-generated figures as unquestionable evidence. The Horizon accounting system, developed by ICL and later acquired by Fujitsu, produced apparent shortfalls in some branch accounts.

Sub-postmasters, self-employed individuals who ran local branches, were held responsible for discrepancies they couldn’t explain away. As a result, some were dismissed from their jobs, criminally prosecuted or wrongfully convicted.

The Criminal Cases Review Commission reported that Horizon had significant problems that could cause it to misreport accounts, while sub-postmasters lacked access to the information needed to challenge the software’s outputs.

The scandal was not simply a software defect. It also involved disclosure failures alongside investigation and institutional accountability. The UK’s statutory inquiry continues to examine the system’s failures and their consequences.

Trust in software should never outweigh the need to question its outputs, investigate discrepancies and hold organisations accountable for decisions.

What Post Office Horizon teaches enterprises

1. Keep a route open to challenge system outputs

Users need to have access to a documented process to dispute errors and escalate cases where the system’s results don’t match reality.

2. Maintain evidence and audit trails

Logs, version histories, incident records and access to technical expertise are essential when a system’s output is questioned.

3. Don’t shift system risk onto users

Organisations ultimately remain responsible for understanding the limitations of the software they develop and deploy as well as the decisions they make using its outputs.

6. Builder.ai: When AI Promise Exceeds Delivery

Builder.ai marketed itself as a technology platform that made it easier for businesses to build their own software. However, in early 2025, the company started facing growing financial difficulties. In February, founder Sachin Dev Duggal stepped down as CEO, and the company began reviewing its financial reporting.

By May, its previously reported 2024 revenue had been revised from $220 million to $55 million. After lenders called in defaulted and seized funds, Builder.ai announced on 20 May 2025 that it would enter insolvency proceedings.

The Financial Times reported that an internal investigation had raised concerns about the validity of previously recorded sales. In addition, Moody’s Ratings, one of the big three credit rating agencies, also described concerns about transactions and the inflation of revenue.

The lesson isn’t to avoid AI-powered software, but to verify what the technology can do, how it works in practice and whether the supplier can reliably support the business in the long term.

What Builder.ai teaches enterprises

1. Separate product claims from proof

Ask vendors to demonstrate capabilities against your use cases, and define what’s automated, manual or dependent on third parties.

2. Evaluate supplier resilience

Focus on financial stability for the future, sub-contractors, data handling, exit arrangements and continuity plans rather than just product features.

3. Embed ongoing verification

Continually re-evaluate vendors, as their products, ownership, finances and dependencies change.

What Governance Blind Spots Do These Cases Share?

The details may differ when it comes to the details but they all show the same recurring weaknesses:

• Evidence is outweighed by ambition: Organisations support a vision before they have demonstrated that they can deliver on their claims.
• Weak oversight: Governance structures exist but are not independent or knowledgeable enough to hold the leadership to account.
• Employees hesitate to raise concerns: Employees, customers and users all struggle to question leaders or software outputs safely or in a regulated way.
• Incentives distort decision-making: Growth, financial performance or delivery targets trump safety, accuracy and responsible conduct.

These are not only compliance-related problems. They affect whether an organisation can properly understand its collection of technological assets, manage third-party dependencies, respond to critical incidents and justify decisions made using data or automation.

A Practical Check for CIOs, CISOs and Data Leaders

When conducting a review of the technology, supplier or AI governance process, look closely at the following:

• Evidence: What independent evidence is there to support the vendor’s technical, security and performance claims?
• Visibility: Do we understand the system’s data sources, dependencies, limitations and failure modes? In other words, is there transparency?
• Accountability: Who takes ownership of risks and who has been given the authority to pause deployment or escalate concerns?
• Challenge: Can employees, customers and operators dispute an output or report a problem without retaliation?
• Resilience: Are there audit trails, incident response plans, fallback arrangements and an exit route in place if the supplier fails to deliver?
• Review: What changes in performance, ownership, regulation or incidents would trigger a fresh assessment of circumstances?

These questions should form part of routine governance rather than being reserved for post-incident reviews. They also give organisations a practical way to connect governance structures and regulations to everyday decisions.

The Best Lesson Is to Challenge Success, Too

Theranos, Enron, FTX, Boeing, Post Office Horizon, and Builder.ai all show how different pressures can undermine technology, financial controls, safety, and organisational culture.

The greatest risks can emerge even when a company appears to be immensely successful, its leaders are celebrated, and its strategy seems to be working. By the time the warning signs become undeniable, the consequences may already be too late to mitigate.

For enterprises investing in innovation and growth, the answer isn’t to avoid being ambitious. It’s to support ambitious endeavours through independent verification, transparent reporting, effective governance and a culture that welcomes difficult questions.

The strongest enterprises aren’t those that never encounter problems, but those that identify, challenge and correct them before they become systemic failures.

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