From Model T to Large Language Models

Business in the Age of AI

In 1913, Henry Ford’s moving assembly line revolutionized manufacturing, slashing production times and reshaping modern business. Critics called it a dehumanizing fad, but it became the cornerstone of industrial progress. Today, artificial intelligence (AI) and large language models (LLMs) are at a similar crossroads—poised to redefine industries, despite skepticism and unease. As per a McKinsey study, AI could add up to 25 trillion dollars in economic value by 2030. So the stakes couldn’t be higher for CEOs and founders: adapt to this transformation or risk irrelevance.

AI Is Redefining Business Models

AI is not just a tool; it’s a paradigm shift. Like Ford’s assembly line, which reimagined production, AI is automating workflows, uncovering efficiencies, and enabling new business models. For example, Amazon uses AI for supply chain optimization to forecast the demand for over 400 million products each day. This has resulted in a 15-fold increase in their forecast accuracy, enabling Amazon to offer a wider selection of products and fulfill deliveries faster. Given the direction in which AI is headed, leaders who fail to integrate AI risk being outpaced by competitors who embrace its potential.

Sharper Decision-Making

AI’s ability to process vast datasets in seconds is a game-changer for decision-making. Predictive analytics powered by LLMs can identify trends, mitigate risks, and uncover opportunities faster than any human team. This precision mirrors the way Ford’s innovations enabled better resource allocation and production planning—only now, the scale is global and the speed exponential.

The New Frontier of Personalization

AI’s capacity for personalization is unprecedented. By analyzing customer behavior in real time, businesses can deliver tailored experiences at scale. This isn’t just about improving service—it’s about redefining customer relationships. Much like Ford democratized car ownership, AI is democratizing access to highly customized products and services.

Ethical Challenges and Workforce Shifts (Future of Work)

But progress comes with challenges. AI raises urgent questions about bias, data privacy, and accountability. Depending on the sector, domain and context, companies can adopt frameworks and standards for the ethical implementation of AI developed by various organizations and institutions. On one hand, we have UNESCO’s framework for responsible AI development with a specific focus on human and environmental rights. On the other hand, IBM has built AI Explainability 360, an open source toolkit that allows developers to understand how machine learning models predict labels, this enables developers to detect and correct biases and other errors.

Competitive Advantage Through Innovation

Companies that embrace AI strategically will dominate their industries. The technology offers not just efficiency but also the ability to innovate faster than ever before. Just as Ford’s assembly line forced competitors to modernize or fail, AI will separate forward-thinking leaders from those clinging to outdated practices.

Specialized LLMs: The Next Phase

The future of LLMs lies in specialization. Industry-specific models and AI Agents will deliver even greater value by addressing niche needs with precision—whether in healthcare compliance or financial forecasting. For instance, LLMs trained on real-life data can aid in timely diagnoses of diseases which can improve patient outcomes; and in the financial sector, banks are deploying custom LLMs to improve fraud detection and forensic traceability for economic crimes. Businesses that customize these tools will gain an edge in productivity and innovation.

Ford’s assembly line wasn’t just about building cars; it was about reimagining what was possible in business. AI offers the same opportunity today—a chance to rethink how we work, compete, and grow. And If you are embarking on your AI transformation journey now, assessing your data maturity and identifying key areas ripe for automation would be a good place to start.