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Article written by Kaladhar Voruganti , Sr Business Development Technologist, Equinix & Jon Duren, Global Solutions & Architecture - Practice Manager, WWT.  

While artificial intelligence (AI) is not new, the growing popularity of generative AI (GenAI) tools such as ChatGPT have sparked a fire for AI adoption in the last 18 months. Enterprises are exploring new use cases for both traditional AI and GenAI, with workloads spanning across machine learning, computer vision, natural language processing, recommendation systems and beyond. According to a recent Boston Consulting Group report, 89% of executives rank AI and GenAI as a top-three tech priority for 2024, and IBM has found 59% of enterprises already working with AI intend to accelerate and increase investment in the technology.

In this maturing world of AI, getting the most from workloads and achieving competitive differentiation requires customization. Whether creating custom models or tailoring commercial models, inclusion of proprietary data on public cloud AI instances introduces risk and complexity. Ensuring data privacy and compliance becomes a challenge. Shared resources may compromise scalability and performance. Questions arise surrounding AI model lineage. Costs and performance become unpredictable.  

For many, the solution is Private AI. By keeping models and data private, your organization can capitalize on AI potential while maintaining greater control and protection. By using only private, dedicated network connections to move data, information is not exposed to the internet. With a dedicated GPU cluster, you can bring the model to your data, even with inputs located across multiple cloud and SaaS sources, while maintaining control and transparency surrounding model lineage. Dedicated resources also offer the scalability and performance you need to deploy more AI projects across your organization. 

While Private AI can help offer the ideal scenario of privacy, transparency, and scale, it also requires skillsets and resources that are increasingly difficult to secure. People are in high demand: one-in-three IT leaders are struggling with finding qualified AI and ML talent. The explosion of AI has meant long wait lists for necessary chipsets. And as AI workloads grow and become increasingly power hungry, often requiring 40kWh or more, providing the proper energy supply and next generation cooling technologies in private data centers can be difficult. Uptime Institute predicts AI will rocket from just 2% of global data center power footprint 2023 to 10% of the sector's global power use by 2025.

But there's a direct path to the best of Private AI: Equinix + World Wide Technology (WWT). 

Your "easy button" for AI 

Together, Equinix and WWT make it simple to deploy Private AI for a cloud-like experience, at a more predictable price with better performance. All while meeting your privacy and data sovereignty requirements. 

Equinix is strategically located at the intersection of the data needed for your AI from edge to cloud, connected to an ecosystem of more than 10,000 enterprises, including over 2,000 networks and 3,000+ cloud and IT service providers. Most network carriers bring their traffic from the edge via Equinix as it moves to clouds and other network carriers. Because Equinix data centers are adjacent to your organization's various cloud providers, you can egress data from your clouds in a more secure, performant, and cost-effective manner than possible via public Internet). Increasingly, as organizations deploy production grade AI solutions, they're realizing that they need to consider more than just AI compute clusters. They also need a high-performant, secure, and cost-optimized network for bringing data from multiple external sources, across clouds, data brokers, other enterprises and beyond. In today's collaborative and data-driven environment, access data across internal and external sources is critical to improving the accuracy of organizations' AI models. Deploying AI stacks at network interconnection hubs like Equinix offer significant advantages. 

Equinix has data centers in 70+ metros. As the size of multi-modal datasets (e.g., video, audio) increase, enterprises can process these datasets in metro-level data centers, close to where information is originating, in order to reduce data backhaul costs. Equinix also has data centers in 30+ countries, offering the global coverage needed to address country- and/or region-specific regulatory and compliance requirements. 

With Equinix, you can have a ready-to-run AI development platform hosted and managed by on your behalf, making it quicker and easier to get the advanced AI infrastructure your organization needs, packaged with the required colocation, networking and managed services to host and operate that infrastructure. 

Meanwhile, WWT can offer the expertise needed to design and execute the full spectrum of AI workloads. WWT has more than 10 years of market-tested experience in AI and nearly 300 practitioners with the skills and infrastructure knowledge to help you optimize your projects from the start. At the same time, WWT also has a breadth of experience across other facets relevant to success, including data visualization, automation, and digital transformation, helping deliver the best end-to-end experience for your business and drive meaningful impact. In fact, you can see it all in action. With AI Proving Ground labs that include Equinix facilities, WWT can help you pilot new AI initiatives and experience the true project impact. 

We know AI does not happen in isolation. Together, Equinix + WWT offer the breadth of knowledge your organization needs to ensure you have the right components in place for your project needs. Through this collaboration, you'll have access to deep partnerships with storage, networking, hardware providers, and more to ensure you're positioned for success. 

A foundation for long-term and collective success with more sustainable AI 

But true success for AI initiatives is about more than "will it work?" Without proper planning and consideration, the massive power requirements of AI can create a spike within your carbon footprint and compromise your organization's sustainability goals. Partnering with WWT and Equinix together allows for right-sized AI solution development on a sustainable digital platform. 

 Equinix is a recognized industry leader in sustainable data centers, achieving 96% renewable energy coverage across its data centers globally (with 100% renewable energy coverage in the Americas and EMEA). Equinix also continues to make meaningful progress toward its long-term goal of decarbonization – on track to achieve 100% renewable energy coverage globally by 2030. Equinix is likewise investing in the efficiency of its data centers, dedicating $77.5 million toward energy efficiency projects in 2023 alone, reducing annual energy consumption by 66,862 MWh and helping to lower global average PUE to 1.42. Offering enterprise-ready specialized air cooling and direct-to-chip liquid cooling technologies, Equinix is further optimizing operating temperature ranges, reducing cooling energy consumption, and supporting increased server density.  

Understanding the impact of AI on your carbon footprint and pinpointing contributing factors within your specific environment is easy with the streamlined and detailed energy and emissions reporting available to Equinix customers. Expertise available from WWT can help build upon this detailed Equinix carbon reporting. WWT solutions and services are available to help streamline the end-to-end processes for your IT organization's Environmental, Social, and Governance (ESG) reporting, as well as help facilitate more effective evaluation surrounding the carbon impact of technology choices. 

Your partners in more sustainable private AI 

The Equinix + WWT partnership offers an easy way to fast-track your AI initiatives and scale for greater impact across your organization, all while delivering AI more securely, reliably, and sustainably. 


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