This Forbes article explains how AI is reshaping cloud competition and influencing enterprise cloud strategies. R.B.Hall Associates, LLC helps SMBs turn these shifts into secure, efficient cloud plans that streamline work and support revenue growth.
How is AI changing enterprise cloud competition?
AI is reshaping cloud competition by shifting the focus from basic infrastructure (cost, reliability, storage, compute) to AI capabilities as the main differentiator.
Historically, cloud decisions were mostly about price-performance and service breadth. Those still matter, but now buyers increasingly ask: “What can I actually build with this provider’s AI stack?”
Key shifts highlighted in the source:
- AI-first growth: Generative AI-specific cloud services were reportedly the fastest-growing segment of the overall cloud service market in 2025.
- New competitive angle: Providers are competing on integrated AI tools—like natural language processing, computer vision, and agentic frameworks—rather than just compute and storage.
- Closer link to business strategy: Cloud choices now directly influence how an organization can use AI in its products, services, and internal workflows, not just how it runs IT.
In practice, this means cloud platforms are being reimagined as AI platforms. The winning providers will be those that help enterprises move faster from AI pilots to production, embed AI into customer-facing apps, and manage AI governance and oversight at scale.
What are some real-world examples of AI-first cloud strategies?
Two examples from the source text show how cloud competition is being reshaped around AI:
1. ByteDance and Volcano Engine
- ByteDance, the company behind TikTok, has updated its Volcano Engine cloud infrastructure to focus on AI execution rather than just infrastructure.
- Instead of selling only compute and storage, it sells access to the algorithms and data-driven tools that power its own apps—such as the AI-augmented video editor CapCut.
- Enterprise customers can build services using real-time content analytics, sentiment analysis, deep personalization, and predictive capabilities.
- This approach has helped ByteDance gain traction in AI services, the fastest-growing segment of China’s cloud market.
2. OpenAI and Snowflake
- Snowflake announced a partnership with OpenAI to integrate frontier AI models directly into its cloud data platform.
- This blurs the line between data infrastructure and AI tooling—users can work with data and advanced AI models in one environment.
3. Perplexity and Microsoft Azure
- Search-oriented AI company Perplexity is partnering with Microsoft Azure, another sign of tight collaboration between AI specialists and cloud providers.
Together, these examples show a clear pattern: cloud providers are reshaping their offerings to deliver AI at scale, not just layering AI on top as an add-on. For buyers, this means evaluating clouds based on how well they enable AI-driven products, personalization, and new business models—not just infrastructure metrics.
How should enterprises adapt their cloud strategy for the AI era?
Enterprises need to rethink cloud strategy through an AI-first lens, not just an IT infrastructure lens.
1. Start with AI use cases, not just platforms
- Clarify what your organization is trying to achieve with AI—e.g., personalization, automation, analytics, new digital products.
- Evaluate cloud providers based on how their platform-specific AI offerings help you reach those goals.
2. Assess AI maturity, not only cost and uptime
- Look beyond headline metrics like price and availability.
- Probe areas such as:
- Model selection and oversight capabilities.
- Support for agentic workflows and managed AI services (e.g., NLP, computer vision).
- Governance, monitoring, and responsible AI controls.
3. Involve cross-functional decision-makers
- Cloud decisions can no longer sit solely with IT procurement.
- Input is needed from business leaders, data and AI teams, risk and compliance, and product owners, because cloud choices now shape core workflows and customer experiences.
4. Manage vendor lock-in and roadmap alignment
- AI-rich platforms can increase the risk of vendor lock-in, as critical tools become tightly integrated into operations.
- Leaders should:
- Assess how dependent key workflows will be on a single provider’s AI stack.
- Consider whether a multi-cloud approach makes sense for resilience and flexibility.
- Check how well the provider’s AI roadmap aligns with the organization’s future ambitions.
In short, forward-looking organizations treat cloud platforms less as interchangeable infrastructure and more as strategic tools for how AI will be embedded into their business over the long term.