The rise of AI in global markets
Thirty years ago, “artificial intelligence” meant the Pokémon opponent finally using something smarter than “Tackle.”
Today, we ask ChatGPT for life advice, design ideas, and even therapy sessions. Somewhere between 2010 and 2025, AI quietly stopped being a buzzword and became the invisible engine behind everything we use.
As shown in the first chart, global AI spending is projected to reach 1.8 trillion dollars by 2030, growing at an annual rate of around 35.9%. What was once an experimental field has become one of the defining economic forces of the decade.
The everyday AI economy
AI is now embedded in daily life. It curates playlists, optimizes commutes, screens job applications, and fine-tunes investment portfolios. Every digital interaction is processed by models trained on data sets larger than anything a human could manage.
Companies use AI to automate workflows and create new revenue streams. Consumers simply experience it as convenience. The truth is that AI is no longer a tech niche. It underpins nearly every industry, from logistics to entertainment.
The Hardware Core
Every digital leap depends on physical power. Behind every model and every chatbot lies a dense web of silicon, circuits, and manufacturing precision. The surge in AI has turned semiconductor firms into the new infrastructure providers of the data economy. GPUs, TPUs, and energy-efficient processors now enable the immense computational load that makes generative models possible.
Companies such as NVIDIA and AMD dominate the GPU market, powering everything from AI training clusters to autonomous vehicles. Taiwan Semiconductor Manufacturing Company (TSMC) and ASML provide the manufacturing precision and lithography tools that make these chips possible. Meanwhile, Broadcom, Micron Technology, and Samsung Electronics supply the connectivity and memory solutions that allow AI systems to operate at scale.
For investors, this shift marks a quiet revaluation. The algorithms may run in the cloud, but the value is grounded in silicon.
The Platform Layer
Beyond hardware, a new competition is unfolding in software and platforms.
Cloud providers are embedding AI directly into their ecosystems, giving enterprises scalable access to tools that once required specialized teams. Model builders and API developers have effectively become the new operating system for entire industries.
Microsoft, through its partnership with OpenAI, integrates generative models into Office, Azure, and enterprise workflows. Alphabet embeds AI across its entire Google Cloud portfolio, from data analytics to advertising optimization. Amazon Web Services (AWS) remains the backbone for AI infrastructure, offering pre-trained models and scalable computing for developers worldwide. Emerging players such as Anthropic, Cohere, and Hugging Face are defining the developer layer of the AI stack, while Salesforce and Adobe are infusing AI into customer and creative platforms.
This consolidation of intelligence into a small group of dominant ecosystems creates durable business models, network effects, and recurring revenue streams that are increasingly attractive to long-term investors.
AI across industries
The second chart highlights how deeply AI has entered the global economy. Around 78% of companies already use AI in at least one business function, yet only 35% have fully implemented it across operations. While adoption is high, scaling remains a hurdle, with 74% of organizations struggling to translate pilot success into enterprise-wide value.
This uneven progress creates both opportunity and transformation across sectors. In healthcare, companies such as Siemens Healthineers, Intuitive Surgical and Moderna use AI to improve diagnostics, enhance imaging accuracy and accelerate drug discovery. In manufacturing, leaders like Siemens, ABB and Honeywell rely on predictive maintenance and robotics to minimize downtime and boost efficiency. The financial sector, represented by firms such as JPMorgan Chase, Visa and PayPal, applies AI to detect fraud, manage risk and automate transactions.
Private investment continues to surge, with 109 billion dollars projected in the United States alone for 2024. This reflects a growing belief that AI is not merely a technological innovation but an economic foundation.
Each successful application expands the total addressable market and attracts both new entrants and established corporations to the AI economy. With a market size expected to reach 1.8 trillion dollars by 2030, AI is no longer confined to the technology sector. It is redefining how businesses across every industry create value and compete.
Why it matters for investors
AI does not merely create new categories of products. It improves efficiency, lifts margins, and accelerates innovation across existing industries.
Companies that integrate AI effectively are rewarded with higher valuations and faster growth, while those that fail to adapt risk falling behind.
For investors, this is less about a single trend and more about a structural redefinition of value creation.
Outlook
AI is not a temporary boom. It is a permanent feature of global productivity.
As models become more capable, infrastructure scales, and adoption broadens, AI will increasingly determine which companies lead and which ones lag.
For investors, the takeaway is clear. AI exposure is no longer speculative. It is strategic. The next decade of market leadership will belong to those who understand not just how AI works, but where its value truly compounds.
