AI is already changing the way businesses across industries approach their operations today. The future impact of what the technology can do leads forward-thinking businesses to develop new ways to incorporate AI into their work and upend existing processes. However, the risks and challenges of taking advantage of a new technology are real; smart businesses must be aware of the potential pitfalls and prepare appropriately before deploying. As AI gets rolled out in more industries and verticals, seeing how others have used it can help businesses make stronger decisions in the future.
The (Private) AI Advantage
Private AI capabilities allow organizations to harness the power of AI without compromising sensitive information. Consider the following examples of AI adoption across industries, and where private AI capabilities fit in.
Healthcare. Healthcare diagnoses and research rely on access to vast amounts of data. But as healthcare providers increasingly use AI capabilities for imaging classification, biotech research and pharmaceutical development, sensitive patient data must remain private. Private AI capabilities identify and tap into patient health information while still protecting personal patient data to keep healthcare systems secure and compliant.
Australian medical group Harrison.ai uses AI capabilities in chest X-rays and brain-computed tomography scans to avoid inequitable diagnoses and potential treatment issues. This helps clinicians make correct diagnoses faster and treat patients sooner. Tapping into private AI capabilities allowed Harrison.ai to increase the accuracy of radiologists by approximately 45%, and its Annalise chest X-ray technology detects 124 different radiological features within seconds—helping clinicians quickly detect cancer and other critical illnesses.
Transportation. For the transportation industry, AI helps save lives by improving passenger safety and reducing accidents: Vehicles use AI capabilities for lane-departure warnings and to exchange information with urban traffic control systems. Traffic surveillance systems help control congestion and manage traffic speed. AI also reduces costs for automobile manufacturers by streamlining vehicle production. Automated vehicle maintenance notifications save consumers time and money as well.
Of course, the use of AI in transportation creates unique challenges. Latency is an issue, as companies need real-time data access to analyze the information in time to detect and respond to road dangers. Some vehicles use biometrics to identify distracted operators, creating privacy concerns.
Private AI models help address security and privacy concerns associated with gathering this type of information. Air Canada's critical IT systems infrastructure uses AI, machine learning and augmented reality to keep its 120,000 passengers on 1,500 daily flights securely connected. These capabilities allow needed data connectivity with Air Canada's business partners and worldwide governments while still providing a frictionless experience for travelers.
Finance. Banks and financial institutions use AI algorithms to determine consumers' loan eligibility and provide personalized finance options. AI-powered fraud detection systems analyze consumers' buying behavior and trigger alerts when they recognize abnormal spending patterns.
With financial firms using AI tools for loss mitigation and prevention analysis, privacy is a huge concern: AI-powered systems collect vast amounts of individuals' data and put their data at risk for exposure.
Financial institutions that rely on public models and publicly trained data to inform AI development risk data leaks, regulatory fines and reputational damage. Private AI allows finance companies to use models proprietary to their organization and trained exclusively on their organization's data. This helps finance companies control the data and information while avoiding regulatory compliance and reputational damage.
Custom, Managed End-to-End AI for Enterprises
As demonstrated above, several industries use constantly evolving AI capabilities to unlock billions of dollars in value. But with this rising AI investment comes the need to also protect customer information, maintain data trust and navigate privacy concerns.
As industries race to harness the potential of generative AI, enterprises need the right partners and access to the right ecosystem to accelerate the integration of AI development into their business operations. This requires AI-ready infrastructure and secure, seamless connectivity to cloud data—both on-premises and at the edge.
Private AI provides complete control over companies' AI capabilities by building their own AI models, hosting those models on private infrastructure, and using only proprietary datasets to train them.
Equinix recently partnered with leading chip manufacturer Nvidia to develop a fully managed private cloud service. Equinix Private AI with NVIDIA DGX enables enterprises to easily acquire and manage their own NVIDIA DGX AI supercomputing infrastructure for building and running custom generative AI models.
This provides customers with a fast, secure and cost-effective way to adopt advanced AI infrastructure operated and managed by experts worldwide. It also makes the NVIDIA AI Enterprise software platform available for developing and deploying production-grade AI applications. These tailored solutions help enterprises navigate the complexities of AI infrastructure while maintaining control over their data and operations in a non-public but high-speed, low-latency environment.
Enterprises use Equinix to deploy their private AI infrastructure, and service providers use Equinix to provide private AI services for their customers. Both can benefit from Equinix's growing AI ecosystem, which has a concentration of buyers and sellers operating near major cloud on-ramps.
To tap into business benefits such as these, explore Equinix, the world's digital infrastructure company® and the platform for private AI. Learn more at https://www.equinix.com/solutions/private-ai
· IDC Report: Private AI infrastructure solves for privacy and regulatory compliance requirements
· IDC Spotlight: Create exceptional customer experiences with Data, AI and edge
