The AI disruption: From global business to your breakfast table

Artificial intelligence is no longer just a boardroom buzzword. It is fundamentally transforming global business, workforce dynamics and regulatory landscapes and its ripple effects now reach the breakfast table. AI’s impact is no longer confined to executives or technologists; it touches every consumer, worker and policymaker.

As a data professional, I see firsthand how challenging it is to keep pace with these changes. AI’s effects are far-reaching, spanning employment, education, wealth, health and daily living. Yet, understanding the full scope of these impacts is daunting. In an age when information is curated by algorithms, the true breadth of AI’s influence is often obscured. 

Consider this: the rising cost of eggs in the U.S. is, in part, an AI story. While this may seem far-fetched, the connection is real and understanding it is crucial for business leaders as you prioritize AI investments and validate which investments will result in the most positive outcomes for your business, e.g., profitability, sustainability, consumer impact, efficiency, etc.

The global AI shift: A business earthquake 

AI is transforming industries at an unprecedented pace. It is disrupting outsourcing, supply chains and energy consumption, just to name a few. For U.S. businesses operating globally, this is not just an upgrade; it’s an upheaval. The traditional outsourcing model is being upended as AI-driven automation replaces low-cost labor, forcing countries that once thrived on outsourced jobs to reposition themselves as innovation hubs or risk losing business. 

Meanwhile, companies must navigate a fragmented regulatory environment, where data sovereignty laws, AI ethics and sector-specific rules vary widely across the US, EU, China and emerging economies.

The winners in this new landscape are countries like India, Brazil and Singapore, who are investing in AI skills, automation and regulatory flexibility. The losers are those relying solely on low-cost labor, without integrating AI into their economies. 

This shift is causing a fundamental change in employability: Jobs are being replaced by automation, and demand is rising for new skills in the AI-enabled workplace.

Education: The hidden bottleneck 

As AI reshapes the workforce, a widening skills gap is emerging. Routine tasks are increasingly automated, and workers must now develop complementary skills such as problem-solving, critical thinking and emotional intelligence to remain relevant. Employers are seeking these skills at a much faster rate in AI-exposed roles, with skill requirements in these jobs changing 66% faster than in other occupations. Yet, the pace of upskilling is not keeping up with technological change, and many organizations report persistent gaps between the skills employees have and those needed to leverage AI effectively.

One key reason for this gap is that much of AI education is shaped by the very companies developing the technology. This has led to inconsistent, biased and often regionally irrelevant curricula. As UNESCO’s global guidance notes, “The rapid pervasion of GenAI in technologically advanced countries and regions…has intensified the concentration of AI wealth in the Global North. As an immediate consequence, the data-poor regions have been further excluded and put at long-term risk of being colonized by the standards embedded in the GPT models.” Many AI education initiatives are driven more by technological potential than by the needs of educators or learners, often neglecting ethical principles.

The dominance of Global North Countries’ access to AI education is further demonstrated by TIME/Statista’s 2025 ranking of EdTech companies, which shows that most influential AI education providers are concentrated in the US, China and India, each shaping curricula by local government priorities and tech company strategies. For example, China introduces AI curricula as early as age six, while other countries focus mainly on adult upskilling. UNESCO’s 2023 report found that only seven countries had developed AI frameworks or programs for teachers, and just 15 included objectives on AI training in their national curricula.

This lack of standardization leads to limited access to AI training in local languages, a shortage of qualified educators and a growing mismatch between job requirements and the skills available as AI becomes more integrated into company operations. For U.S. businesses, these challenges translate into higher training costs and greater compliance risks as they struggle to find AI-ready talent both domestically and abroad.

The AI-egg price connection: A subtle domino effect 

How does all this connect to the rising cost of eggs? The answer lies in the complex ripple effects of AI on agriculture and food supply chains.

AI is optimizing food distribution by reducing costs, improving forecasting, enhancing product quality and minimizing waste. But these advances come with hidden costs that ultimately reach the consumer.

Energy consumption

AI-driven automation requires massive computing power. Data centers powering AI are projected to account for nearly half of the growth in US electricity demand by 2030. According to the International Energy Agency, by 2030, US data centers will consume more electricity for processing data than for manufacturing all energy-intensive goods combined, including aluminum, steel, cement and chemicals. This surge in demand raises electricity costs for farms and food production facilities, which in turn are passed on to consumers in the form of higher food prices, including eggs.

Commodity trading and feed costs

AI models are now widely used in commodity trading, directly influencing the prices of corn and soybeans, key ingredients in poultry feed. A comprehensive literature review by Malátková & Gangur (2024) found that the integration of artificial intelligence and machine learning in commodity markets has significantly improved the accuracy of forecasts and market analysis, enabling traders to make faster and more informed decisions.

However, this increased speed and sophistication come with new risks. According to the International Monetary Fund (IMF), “prices may react much more quickly in an AI-driven market”. Park (2025) supports this view, noting that “by reacting to rapidly changing market signals immediately, multiple algorithms generate sharp price swings that lead to short-term volatility.” The Bank of England has also warned that widespread use of AI in trading can amplify market volatility, especially during periods of stress, as algorithms may drive firms to act in a “herding” manner, potentially exacerbating sudden market drops.

Industry analysis confirms that AI-driven algorithms process vast amounts of market data, weather patterns and geopolitical events in real time, amplifying the speed and magnitude of price movements in commodities like corn and soybeans. When AI-powered trading triggers rapid price swings in these essential inputs, feed costs for poultry producers rise, ultimately increasing egg production costs.

What’s next? Adapt or be disrupted 

AI is not a distant prospect; it is the single biggest force reshaping the global economy, workforce and business landscape today. Although businesses already have to contend with real-world shocks, such as in the case of the poultry business which has to be prepared for external threats such as avian flu outbreaks, grain shortages or climate-driven disruptions, companies that fail to invest in AI-ready talent and navigate regulatory uncertainty are at additional risk of losing their competitive advantage if they do not invest strategically in AI. At the same time, AI’s hidden ripple effects, from increased energy costs to goods prices, remind us that this transformation is not happening in isolation. Every industry, every market and yes, even your breakfast, is feeling the impact. 

The question is not if AI will disrupt your business or your life. The question is, are you ready for it?

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