Innovation Answered

Cloud computing continues to defy the life cycle of typical technology trends. Nearly two decades into mainstream adoption, the cloud remains central to innovation — helping to power everything from artificial intelligence to quantum breakthroughs and edge devices.¹ As demand continues to grow, so too can the opportunity for forward-looking companies and investors.

According to Synergy Research Group,² enterprise spending on cloud infrastructure services topped $91 billion in Q4 2024, a 22% increase over the previous year. Overall, cloud spending in 2024 hit $330 billion, a year-over-year increase of $60 billion.

To stay current with — and ahead of — cloud computing’s ever-evolving landscape, investors and innovators are keeping a close watch on three ongoing developments:

Few technological developments have captured the public’s attention and imagination like artificial intelligence (AI). Its impact on business, culture and daily life is only just beginning to be understood. But AI is always hungry — for more electricity, more computing power, more data.

To keep the algorithms well-fed, some developers are building their own server farms — enormous facilities packed with tens of thousands of dedicated graphics processing units (GPUs). Others are turning to enterprise cloud platforms to host their AI applications.

According to Synergy Research Group,² generative AI has driven at least half of all cloud service revenue over the past two years. The “big three” providers — Amazon, Microsoft Azure and Google Cloud — command over 60% of the global market, with Amazon Web Services alone holding a 30% total market share.

To deliver the speed, scale and storage that are required, these cloud networks need the fastest, most powerful hardware available. Semiconductor giants like Advanced Micro Devices and NVIDIA have seen heightened demand for their GPUs.^3,4 NVIDIA’s recently released Blackwell platform can run real-time generative AI for up to 1/25th of the financial cost and energy consumption of its predecessor. Amazon, Microsoft and Google were named among the expected adopters.⁵

Cloud providers are also integrating AI and machine learning into their platforms. Amazon’s SageMaker offers developers a fully managed cloud-based service for building and deploying machine learning models.⁶ Microsoft’s Azure AI Foundry provides tools for creating enterprise-grade AI agents.⁷ Google Cloud, through its Gemini 2.0 models, provides a suite of AI-driven development tools.⁸

Finally, countless applications, platforms and service providers sit on top of third-party artificial intelligence, may create an additional layer of value for enterprise and consumer clients. For these developers, the cloud plays a crucial role in facilitating access to AI. Rovo, for example, is Atlassian's enterprise AI solution embedded within their existing cloud products, including Jira and Confluence.⁹

Starting in the 1970s, a number of physicists began theorizing that computers might have their customary 1s and 0s replaced with so-called quantum bits, or qubits, to solve complex problems. A few decades later, quantum computers are a reality, thanks in great part to advances by Microsoft, Intel and others.

Though the technology remains new, quantum computers already demonstrate performance at speeds that far exceed classical systems. Many believe that in a short time, quantum computing will sit at the center of the next technological revolution.

However, cost remains a barrier — top-end systems run over $50 million,¹⁰ and blue-sky projects, which require extensive R&D and focus on long-term potential, are estimated in the billions.¹¹ That’s where the cloud is useful.

Just as it helped to democratize access to traditional high-performance computing, the cloud is enabling developers to work with quantum systems virtually. Amazon’s Braket offers access to various types of quantum hardware,¹² while Microsoft’s Azure Quantum connects users with leading third-party quantum technology. Microsoft also introduced its first in-house quantum chip, Majorana 1, in February 2025.¹³

The cloud might dominate modern IT infrastructure, but edge computing is bringing power back to the device level — right where the data is generated.

By performing computation closer to the source, edge computing reduces latency, bandwidth use and downtime, while increasing security. Still, the cloud remains vitally important. Modern edge computing does not work without access to a high-speed, scalable network.

Qualcomm, a leader in mobile technology, is pushing the frontier with AI-enabled smartphones, smart cars and other edge devices. At the same time, it has invested in start-ups that facilitate easier cloud-based app deployment. This aligns with the company’s broader efforts to advance both cloud-native technologies and capabilities at the edge.¹⁴

Likewise, Cisco Systems, one of the world’s largest suppliers of network hardware, is building bridges. Their hybrid cloud approach allows for high-speed, on-premises computing to connect with high-performance, low-latency networks. For example, Internet of Things (IoT)¹⁵ sensors and other edge devices can collect and even analyze data independently, on-site. The data is synchronized with other nodes and networks, facilitating real-time decision-making and data flow between the edge and the cloud.

From AI and quantum computing to edge integration, the cloud remains a foundation for tomorrow’s technology. For investors, further developments could present both opportunity and urgency. The companies driving these innovations — whether through chips, platforms or partnerships — are helping to shape the technology landscape and, in turn, the future of global enterprise and beyond.