On-Premises AI in Enterprises: Control, Costs, and Business Opportunities from a Management Perspective
Companies are increasingly using AI solutions. As a result, it is becoming an increasingly important management issue to determine where corporate data is stored, who has access to it, how much it costs to operate AI, and to what extent the company becomes dependent on external service providers.
Gloster Local AI offers a possible solution to this: by deliberately combining on-premises and cloud-based AI models, companies can gain greater control over their data, access, and AI usage.
In our webinar, we’ll use practical examples to show when it’s worth considering implementing your own enterprise AI, what business opportunities it offers, and how Gloster Local AI works in practice.
AI creates real business value when it is able to work with a company’s own data, documents, and internal knowledge. However, this often requires making sensitive business information available to AI systems.
What the company doesn’t allow, employees often do through their personal AI accounts. This is “shadow AI”: you can’t see what corporate data is being transferred to external systems, you can’t log its use, and you may even lose control over information that has already been shared.
The unit cost of AI has fallen by 93% over the past two years, yet corporate bills have more than tripled. Usage-based pricing and increasingly complex, agent-based AI tasks could drive costs even higher. How can costs be kept under control, and when is it worth investing in your own AI infrastructure?
Source: [SOURCE FOR THE 93% / 3× DATA]
The pricing, models, and terms of external AI service providers are constantly changing. Others decide when to replace or discontinue a model, even though a company’s business processes are already built around it. How can we preserve our freedom to make decisions and avoid excessive technological dependence?
You don’t have to pay for an expensive cloud-based model for every task. Gloster Local AI chooses between on-premises and cloud-based AI models based on corporate policies. Sensitive data can remain within the corporate environment, while external models can be used for approved, more complex tasks.
In this webinar, we’ll use practical examples to demonstrate the business opportunities, costs, and secure operation of in-house AI, as well as the key capabilities of Gloster Local AI.
For what types of tasks can an on-premises AI model be used, and when is it appropriate to use cloud services? We’ll examine the business needs, usage volumes, and data security requirements under which having your own AI infrastructure can be advantageous.
A comparison of the costs of on-premises and cloud-based AI. We’ll show you how to track AI usage costs by user and by organizational unit, and how to reduce external model calls by processing routine tasks on-premises.
How can AI work with internal policies, financial reports, and project documentation, including source citations? We’ll show you the possibilities of AI in relation to dynamically updated corporate knowledge bases, HR, sales, and financial assistants, as well as existing corporate systems.
Enterprise access management, protection of confidential information, regulation of data flow, and logging of AI usage.
We’ll show you how Gloster Local AI’s router decides whether to use the on-premises or cloud-based model based on the complexity of the task, the sensitivity of the data, costs, and corporate policies.
Online professional webinar with a live Q&A session. We will send you the link to join the webinar in the confirmation email.
We recommend this webinar primarily to senior executives and business and technology decision-makers at medium and large companies who are responsible for the business application, secure implementation, and operation of AI.
Those who want to understand the business benefits of in-house AI, when the investment will pay off, and how to reduce dependence on external technology providers.
Those who want to build a secure, scalable, and controllable AI environment tailored to their existing corporate infrastructure and data security requirements.
Those who want to use AI in specific business processes expect measurable results from its implementation, and predictability of costs is important to them.
President of HUNBA, IT entrepreneur, and angel investor. Starting in March 2026, he will serve as CEO of Gloster, where he will lead international expansion and the company’s focus on AI. He will open the evening and then continue the discussion as a participant in the executive roundtable.
Responsible for technical implementation: team leadership, architectural decisions, and project delivery in a large-enterprise environment. He has firsthand knowledge of where the roadmap diverges from what actually happens in production.
Gloster has been developing, modernizing, and operating enterprise IT systems for more than two decades, while serving as the local enterprise partner for the world’s leading cloud, security, and AI companies. As a partner of Anthropic, we have an inside look at how AI works within enterprise systems.
In addition to designing and operating enterprise Microsoft environments, we also work with leading vendor partners in the areas of cloud, networking, and security.
The starting point is a business decision, not a technology. We’re exploring how enterprise AI stays under your control:
Fill out the form, and we will confirm your registration via email within 48 hours and send you the information you need to participate.
