Machine learning: Accessing tomorrow’s tech

Key takeaways:

• Machine learning (ML) is now embedded in industries beyond tech, with real-world impact in healthcare, finance, cybersecurity, and retail.
• Some Nasdaq-100 companies have helped drive ML innovation at scale, from cloud infrastructure and GPUs to enterprise AI applications.
• Invesco QQQ offers exposure to leaders shaping the future of machine learning through the Nasdaq-100 Index.

Machine learning, the development of algorithms that learn from data and perform tasks without explicit instructions, is no longer confined to labs or future forecasts—it’s driving real-time innovation across nearly every industry. In the past year alone, advances in generative Artificial Intelligence (AI), large language models (LLMs), and cloud-powered infrastructure have modified the way that businesses operate and consumers engage with technology. And many of the companies leading this shift are part of the Nasdaq-100 Index, tracked by Invesco QQQ.

The global machine learning market size was estimated at about $51.5 billion in 2023 and it is projected to rise to over $1.4 trillion by 2034.¹

From virtual assistants and autonomous vehicles to fraud detection and AI copilots, machine learning has become one of the most dynamic and widely adopted technologies of the modern era. Let’s take a closer look at where ML is headed, and how investors are gaining exposure through QQQ.

From niche to everywhere: Real-world ML in 2025

While machine learning has long been associated with the tech sector, its impact now stretches across industries:

• Healthcare: ML algorithms are helping researchers accelerate drug discovery, personalize treatment plans, and power diagnostic imaging tools that detect diseases earlier and more accurately.
• Retail and e-commerce: ML is fueling personalized product recommendations, dynamic pricing models, and inventory optimization—helping companies deliver smarter, more responsive services.
• Cybersecurity: As threats grow more complex, AI-powered tools are enabling real-time monitoring and faster breach detection, helping improve digital defenses at enterprise scale.

These use cases aren’t projections—they’re active applications helping to shape some of today’s growing industries.

The AI boom: Powered by infrastructure

Behind every ML model lies a complex web of infrastructure—cloud platforms, graphics processing units (GPUs), high-speed memory, and vast storage capacity. These technologies help make it possible to train, scale, and deploy AI across organizations of every size.

Companies in the Nasdaq-100 are providing the tools and architecture that helped fuel this growth:

• NVIDIA: A global leader in GPUs, NVIDIA powers AI training and inference workloads across many verticals.
• Microsoft: Through Azure AI and its partnership with OpenAI, Microsoft is embedding machine learning into productivity tools and cloud solutions used across the globe.
• Amazon: AWS offers a full suite of machine learning services and custom chips designed to accelerate AI adoption across startups and Fortune 500 companies.
• Alphabet: With innovations from DeepMind and Google Cloud’s TPUs, Alphabet remains at the forefront of ML performance and accessibility.
• Meta Platforms: Meta continues to invest heavily in open-source ML (including the Llama model family), while integrating AI into content recommendations, virtual reality, and its own cloud infrastructure.

Even companies like Tesla and Palantir are deploying machine learning at scale, whether in autonomous driving or large-scale enterprise analytics.

Growth, investment, and the future of ML

The machine learning market has grown at a rapid clip. Global AI investment exceeded $200 billion in 2024, with enterprise adoption reaching all-time highs across sectors.² At the same time, monetization strategies are becoming clearer: companies are embedding ML directly into consumer products, enterprise software, and digital platforms—working to hopefully turn innovation into revenue.

As adoption expands, so do opportunities for investors. ML innovation isn’t just coming from pure-play AI firms—it’s being driven by established leaders with deep R&D pipelines, platform ecosystems, and the scale to turn breakthroughs into real-world impact.

Exposure through QQQ

Invesco QQQ provides access to the Nasdaq-100 Index, which includes many of the companies powering and applying machine learning at scale. From hardware and infrastructure to cloud platforms and enterprise AI tools, QQQ investors are gaining exposure to the backbone of tomorrow’s technology—today.