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Increased efficiency and even higher cybersecurity risks
AI for organizations: opportunities, risks, and secure local AI
Generative AI offers organizations new opportunities to work more efficiently, find knowledge faster, and improve processes. At the same time, new risks arise regarding privacy, cybersecurity, shadow AI, and control over corporate data.
That is why AI requires not only adoption but also a secure implementation. Especially when employees work with internal documents, customer data, knowledge bases, or other sensitive information.
72% of organizations have implemented AI in at least one business function.
This rapid adoption is driven by the promise of improved efficiency and productivity.
56% of organizations expect significant boost in efficiency and productivity from Gen AI.
This rapid adoption is driven by the promise of improved efficiency and productivity.
50% of executives are very concerned about AI driven phishing and malware.
Generative AI contributes to increasing cyber threats through misuse of tools.
Are organizations sufficiently aware of the downside?
While AI increases efficiency, it is essential to also address the associated cybersecurity risks to ensure secure and sustainable implementation. Many organizations initially focus on privacy risks and data outflows, such as unauthorized access or loss of sensitive information. While this is important, other less visible dangers often remain underexposed. Consider indirect prompt injection, where malicious actors can force harmful results through subtle manipulations, or shadow AI – uncontrolled implementations of AI within an organization that fall outside standard security protocols.
In addition, it fundamentally changes the way organizations handle information: questions replace searches and answers replace search results. Generative AI promises to increase efficiency, for example, in front-line support where the same questions are asked over and over again. Yet using public generative AI solutions brings new challenges. One of the most pressing is the issue of privacy and data security. Cloud-based solutions often enrich their models with the data that organizations input, posing risks to confidential information. Other obstacles, such as hallucinations (AI answers that are incorrect or made up) and opaque pricing models, add complexity.
To deploy AI responsibly and effectively, it is critical to understand and manage both the visible and hidden risks. Curious to learn more about the risks of generative AI and how your organization can prepare for them?
Secure AI starts with control over data
Many organizations primarily look at productivity when it comes to AI. The most important question often comes later: which data is being used, where is that data processed, and who maintains control over access, rights, and output?
With public AI tools, sensitive information can end up outside your own environment. This makes AI not just a question of innovation, but also one of cybersecurity, compliance, and digital sovereignty.
Local AI without cloud dependency
Silent AI is a secure, off-cloud AI appliance that runs entirely locally. This allows organizations to use generative AI with their own data without sending sensitive information to public AI services.
The solution combines local processing, integrated rights management, and an energy-efficient architecture. As a result, you maintain control over data, access, costs, and compliance.
Frequently asked questions about AI and data
What are the risks of generative AI for organizations?
Generative AI can cause risks regarding privacy, data leaks, shadow AI, prompt injection, hallucinations, and unclear costs. Control over processing and access is especially important with sensitive corporate data.
Why is local AI interesting for organizations?
Local AI is interesting when organizations want to work with their own documents, knowledge bases, or internal systems without sending data to public AI services.
How does Silent AI help with secure AI usage?
Silent AI runs locally, works with your own data sources, and takes existing rights management into account. This ensures sensitive information remains within your own environment.
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