Artificial intelligence (AI) has become an integral part of modern media workflows, driving efficiency, automation, and content discovery. Despite AI’s growing popularity, there is a common misconception that fully managed, subscription-based AIaaS or SaaS offerings are the only way to get the full value out of AI. Another prevalent misbelief is that leveraging AI requires significant investments in public cloud infrastructure. Because of these misconceptions, decision-makers oftentimes tend to overlook the fact that the goodness of AI is best leveraged from an on-prem infrastructure.
If businesses don’t run AI in their own environments, they may face several drawbacks, including data privacy and security risks, latency issues, unpredictable costs, and vendor lock-in. Running AI on-premises can help overcome these challenges while also providing significant advantages.
In this blog, let’s delve into the reasons why AI is better when run on-prem, and what are the drawbacks of not doing so.
Strong data privacy and security
The biggest hurdle any business faces when trying to adopt AI is data privacy and security risks. Even with purpose-built platforms for business use cases, security teams need employees to exercise caution and not feed any proprietary information to any AI platform. It is no secret that managed AI service providers use customer data to train their own models, raising intellectual property-related concerns. With externally hosted AI models, businesses may not get enough transparency for audit purposes, leading to regulatory risks.
With an AI model that is trained and deployed on your on-prem infrastructure, data privacy and security issues are minimized. You can rest assured knowing that your asset libraries and intellectual properties are not used for the benefit of AI vendors. You can use AI to improve critical business operations even if they involve confidential information.
Predictable and relatively low expenses
The subscription charges of externally hosted and fully managed AI services are typically inclusive of compute, storage, and data transfer costs. In such models, the fees you are required to pay will invariably depend on the volume of workload on which AI capabilities are applied. Such a pay-for-what-you-use model may not be ideal for media and entertainment businesses that are looking to enhance all their libraries of media content.
With an on-prem AI model, such high costs can be avoided. You can even run your entire archive, even if it is of petabyte scale, through an on-prem AI model and enhance its value while only spending a fraction of what you would need to when using an externally hosted offering.
Better suited for real-time applications
The media and entertainment industry has several AI applications like video analytics, streaming optimization, live video compression etc., that require real-time processing. These can suffer from slow response times due to latency, bandwidth, and cloud dependencies. Vendors are also known to limit access to specialized hardware like GPUs and TPUs impacting performance.
An AI model running on-prem can handle such scenarios better. You can optimize the allocation of GPUs or TPUs to meet your needs, as you maintain control over your hardware.
More scope for customization
A business needs to keep their AI model evolving as per their needs and use. Externally hosted AI models have nil to limited scope for customization. On-prem AI offers complete flexibility, allowing businesses to train, modify, and enhance models based on specific requirements. Depending on where they see value, a business can train their models and impart it with new capabilities.
All in all, AI becomes even greater when it is run on on-premises infrastructure.
AI that works for you: Perifery’s AI+
Perifery’s AI+ is one such tool that can deliver the goodness of AI to your on-prem infrastructure. It is designed to boost productivity and unlock the potential of asset libraries. Built from intellectual property developed over years of working with media customers, AI+ automates workflows, generates intelligent metadata, and transforms content discovery.
Combining advanced AI with workflow automation, AI+ enables media workflows to better ingest, preserve, and distribute assets and discover long-forgotten content for reuse and monetization. Our team can work with you to train the AI model as per your needs and deploy it on your on-prem infrastructure.
In this recent webinar, you can see some real-world examples of how media businesses leverage AI+ to enhance the value of their assets and improve their workflows.
If you are interested in learning more about Perifery AI+, download our datasheet.
