The real market potential of AI is estimated at $1.5 trillion, with the greatest opportunities lying in applying AI to solve tangible problems across various industries, prompting a reallocation of capital towards application-driven sectors.

While risks such as data privacy, regulation, and workforce displacement exist, companies with strong governance and compliance strategies, like IBM, are better positioned to navigate these challenges.

A McKinsey survey shows that 78% of organizations now use AI in at least one business function, with adoption of generative AI rising to 71%, although most have yet to see significant financial returns.

Industries including healthcare, finance, manufacturing, and retail are increasingly adopting AI for applications like drug discovery, personalized treatments, fraud detection, and predictive maintenance, demonstrating tangible benefits such as increased conversion rates.

AI infrastructure has become more affordable and scalable, with inference costs dropping over 280-fold since 2022 and hardware costs decreasing by 30% annually, making AI solutions accessible for mid-sized companies.

Although fundamental AI research continues, the pace of breakthroughs has slowed, shifting industry focus toward applying existing AI infrastructure to transform sectors, similar to the evolution of the internet from network development to application deployment in the late 1990s.

Investors are encouraged to target sectors where AI is already delivering measurable ROI, such as healthcare diagnostics, industrial automation, financial services, and e-commerce, rather than chasing speculative model innovations.

The AI industry is shifting focus from developing new models to building robust infrastructure that enables practical, real-world applications, unlocking significant investment opportunities.