Cloud providers and enterprises are embedding artificial intelligence into infrastructure and services to drive automation, re-imagine workflows and accelerate innovation.

The age of AI-first cloud services

The cloud has long been about scalable compute, elastic storage and simplified infrastructure. But as we head further into 2025, a new paradigm has emerged: AI-powered cloud services. According to one major vendor, “AI-enabling cloud services is poised to revolutionize IT operations, embedding AI as a fundamental element across everything from infrastructure management to application deployment.” 
This shift means that rather than simply lifting workloads to the cloud, enterprises are adopting cloud platforms that actively use AI to optimise operations: auto-scaling, predictive analytics, self-healing networks, intelligent automation, AI-driven data pipelines and more.

What’s driving the change

Several converging forces are driving this move:

• AI demand explosion – Organisations are generating, ingesting and analysing more data than ever; cloud platforms provide the scale and global footprint needed to fuel advanced AI models.

• Infrastructure-as-code evolution – Cloud infrastructure is becoming more programmable and more intelligent, enabling AI to manage cloud operations (so-called “AIOps”).

• Service model innovation – Providers are packaging AI models as services (e.g., machine-learning platforms, agentic AI agents) and combining them with infrastructure to deliver higher-level value. For example, one firm announced “agentic AI” capabilities on cloud infrastructure.

• Scale, speed, and delivery – With large scale GPU clusters, global cloud networks and broad ecosystem partnerships, cloud providers can now deliver AI services quickly and globally. This enables rapid enterprise adoption.

Key service categories and capabilities

In practical terms, enterprises are seeing cloud-AI services manifest in several ways:

• Intelligent infrastructure operations (AIOps): Using AI to monitor, predict and automate infrastructure health, capacity planning, incident response.

• Embedded application intelligence: Applications delivered from the cloud now increasingly include AI capabilities (recommendation engines, chatbots, agent assistants, anomaly detection).

• Cloud-native agentic platforms: Some providers now offer tools enabling creation of “AI agents” that can carry out workflows, integrate with enterprise systems, and drive automation — built on the cloud platform.

• Data- and insight-driven services: Cloud platforms are offering managed data services that include AI-enabled analytics, data pipelines, data quality, and data-driven automation. For example, one company announced AI-powered cloud data-management platform capabilities.

Business impact and use-cases

The business impact of AI-powered cloud services is multifold:

• Operational efficiency – Automation of repetitive tasks, improved monitoring, and forecasting reduces overhead and incident cost.

• Faster innovation – Developers can leverage AI-enabled services rather than build everything from scratch, thereby accelerating time-to-market.

• Improved customer experience – AI services provide more responsive, personalised experiences (chatbots, agents, recommendation engines).

• Better decision-making – Managed data services with embedded AI enable real-time insights, predictive analytics and intelligent workflows across business functions.

• Competitive differentiation – Organizations leveraging AI-enabled services can outpace peers who still rely on legacy manual processes or basic cloud lift-and-shift models.

Challenges and considerations

While the promise is strong, there are practical challenges:

• Data quality and governance – AI services are only as good as the data they consume. Ensuring data is clean, secure, and appropriately governed is essential.

• Cost management – AI workloads (especially large models) consume significant resources. Transparent cost-monitoring and governance are needed.

• Skill gaps – Organisations need talent and tooling to integrate and operationalise AI services.

• Security and compliance – AI introduces new risks: model bias, drift, explainability, regulatory compliance, and data privacy concerns.

• Vendor lock-in risk – As more value gets embedded in provider-specific AI services, firms must still manage portability and negotiate strong contracts.

Looking ahead: The cloud becomes the AI engine room

In the near term, we can expect:

• More cloud platforms to integrate AI throughout their infrastructure stacks (from networking to storage to compute to applications).

• Growth in agentic AI — cloud platforms enabling the creation and orchestration of AI “agents” that automate business flows.

• A shift in developer practices: Instead of just “deploy to cloud”, developers will increasingly “build on cloud-AI services”.

• Increased focus on explainability, ethics, trust, and hardware acceleration (GPUs/TPUs) embedded in cloud services to serve AI workloads.

For example: The collaboration between a data-security company and a hardware/AI chip provider to deliver “confidential computing” for regulated industries shows how hardware + cloud + AI converge.

Closing Thoughts

AI-powered cloud services mark a fundamental shift in how enterprises consume infrastructure and innovation. Instead of merely migrating to the cloud, organisations are now building on cloud platforms that embed intelligence, automation and agility. The winners will be those who align strategy, data practices, talent and tooling to exploit this shift — not simply lift legacy applications into the cloud.

Author: Serge Boudreaux – AI Hardware Technologies, Montreal, Quebec
Co-Editor: Peter Jonathan Wilcheck – Miami, Florida

References

1. “AI-enabling cloud services are the future of cloud – Gartner”, Gartner press release. https://www.gartner.com/en/newsroom/press-releases/2025-09-24-ai-enabling-cloud-services-are-the-future-of-cloud

2. “AWS launches agentic AI tools and major cloud service upgrades”, About Amazon. https://www.aboutamazon.com/news/aws/aws-summit-agentic-ai-innovations-2025

3. “Accenture and AWS Accelerate AI-Powered Reinvention and Cloud Modernization for Public Service Organizations”, Accenture Newsroom. https://newsroom.accenture.com/news/2025/accenture-and-aws-accelerate-ai-powered-reinvention-and-cloud-modernization-for-public-service-organizations

4. “Informatica Unveils Agentic AI Offerings on Industry’s First AI-Powered Cloud Data Management Platform”, Informatica. https://www.informatica.com/about-us/news/news-releases/2025/05/20250514-informatica-unveils-agentic-ai-offerings-on-industrys-first-ai-powered-cloud-data-management-platform.html

5. “The Cloud: AI’s New Engine Room”, Forbes. https://www.forbes.com/councils/forbestechcouncil/2025/06/04/the-new-cloud-rush-how-ai-is-reshaping-everything/