What Interjet's fall teaches companies in the AI ​​era

Interjet's bankruptcy was one of the most high-profile in Mexico. But beyond the crisis, its fall is a case study in the vulnerabilities that Artificial Intelligence can address today. We analyze five crucial lessons for any company in Latin America.

The collapse of Interjet, which went from being one of Mexico's most important airlines to a bankrupt company with thousands of employees affected and astronomical debt, is a complex story involving multiple factors. It's been discussed: the pandemic, tax debts, mismanagement, and disastrous strategic decisions. However, analyzing its fall solely from a traditional financial perspective misses the most important lesson for the future of business.

The story of Interjet is a clear example of the risks a 21st-century company faces operating with a 20th-century manual. Its main flaws—in strategy, finance, and adaptability—are precisely the areas that Artificial Intelligence (AI) is revolutionizing. This is not an article about the past, but about the future: five lessons that Interjet's fall has taught us and how AI has become the indispensable tool to prevent your company from suffering the same fate.

* Interjet's mistake: One of the most criticized decisions was the acquisition of 22 Russian Sukhoi Superjet 100 aircraft. Although the purchase price was attractive, they soon became a liability. Maintenance problems, a lack of spare parts, and difficulty operating them resulted in grounded aircraft that had to be "cannibalized" (dismantled for parts to be used in other aircraft), generating millions in losses and flight cancellations that eroded customer confidence.

* The AI ​​solution: Today, a decision of this magnitude wouldn't be made blindly. AI-powered predictive analytics and simulation platforms can model an asset's Total Cost of Ownership (TCO) over its entire lifespan. An AI system would have analyzed not only the purchase price but also simulated thousands of scenarios, including:

* Risks in the spare parts supply chain from Russia.

* Projected maintenance costs based on data from similar fleets.

* Impact on flight operability and punctuality.

AI would have raised a red flag, showing with data that the initial "savings" would turn into a financial drain. AI transforms intuition into data-driven foresight.

* Interjet's mistake: The airline accumulated a massive tax debt with the SAT since 2013, in addition to debts to suppliers and creditors, operating with negative cash flow for years. This reactive financial management, which only puts out fires, is unsustainable. The company was, in the words of its own CFO in 2019, "technically bankrupt" long before the pandemic.

* The AI ​​solution: Modern financial management is proactive thanks to AI. AI tools for finance, such as those used for fraud detection or automated advice, can:

* Predict cash flow: Analyze income and expense patterns to warn of future liquidity problems months in advance.

* Optimize expense management: Identify areas of inefficient spending and suggest cuts.

* Automate tax compliance: Minimize the risk of errors and fines.

* Detect fraud: An analysis of Interjet transactions, where possible misappropriations were reported, could have been flagged by an algorithm trained to detect anomalies. AI is the financial watchdog that never sleeps.

* Interjet's mistake: The airline tried to be all things to all people. It offered more space between seats and free snacks (like a traditional airline), but with prices that sought to compete with low-cost carriers, a dilemma that left it without a clear business model. This lack of definition left it caught in the middle, lacking the loyalty of premium customers or the cost efficiency of Volaris or Viva Aerobus, which gained market share.

* The AI ​​solution: Defining a market niche is no longer an art, it's a science. AI can:

* Advanced customer segmentation: Analyze purchasing, browsing, and social media data to identify micro-segments of customers with specific needs (e.g., business travelers who value punctuality above all else).

* Dynamic Pricing: Adjust prices in real time not only based on demand, but also on customer profiles, maximizing revenue per seat.

* Personalization at scale: Automatically offer personalized packages and promotions to each type of traveler, strengthening loyalty. AI tells you exactly who your customer is and what they want.

* Interjet's mistake: The COVID-19 pandemic was the final blow, but the company was already structurally weak. Its inability to quickly adapt to an external shock of that magnitude demonstrated its lack of resilience.

* The AI ​​solution: Business resilience in the 21st century is synonymous with agility. AI fosters it by:

* Model crisis scenarios: What would happen if demand drops by 90%? Or if the price of fuel doubles? AI can simulate these scenarios and help create robust contingency plans, assessing risks that can range from moderate to catastrophic.

* Robotic Process Automation (RPA): In times of crisis, reducing operating costs is vital. AI can automate administrative, accounting, and customer service tasks, allowing the company to operate with a much leaner structure.

* Interjet's mistake: Multiple reports and legal proceedings point to opaque management, possible embezzlement, and a complex network of companies that made it difficult to track funds. This lack of internal and external transparency destroys the trust of investors, employees, and creditors.

* The AI ​​solution: AI can be a powerful corporate governance tool. AI-based audit systems can analyze millions of emails, contracts, and transactions to detect conflicts of interest, patterns of fraud, or policy noncompliance, ensuring a level of oversight that is humanly impossible.

Interjet's downfall isn't just the story of an airline. It's a warning. In a world where AI can predict risks, optimize finances, and understand customers at a granular level, operating based on intuition and outdated processes is too risky a bet. The question for every entrepreneur in Latin America isn't whether they should adopt AI, but how quickly they can do so to build a smarter, more agile, and ultimately future-proof organization.