{"id":207,"date":"2025-03-24T23:55:20","date_gmt":"2025-03-24T22:55:20","guid":{"rendered":"https:\/\/tiwastech.com\/?p=207"},"modified":"2025-03-25T00:05:27","modified_gmt":"2025-03-24T23:05:27","slug":"ai-er-ikke-bare-plug-and-play-saadan-undgaar-du-faldgruberne-naar-du-implementerer-ai","status":"publish","type":"post","link":"https:\/\/tiwastech.com\/en\/ai-er-ikke-bare-plug-and-play-saadan-undgaar-du-faldgruberne-naar-du-implementerer-ai\/","title":{"rendered":"AI is NOT just Plug-and-Play \u2013 How to Avoid the Pitfalls When Implementing AI"},"content":{"rendered":"

Written by Per Gull\u00f8v Lundh Eeg (Head of AI & Digitalisation og Partner i LEAD+)<\/a> and Simon Stubben (Ekspert R\u00e5dgiver & Ejer af TIWAS TECH)<\/a><\/em><\/p>\n\n\n\n

AI is on everyone\u2019s lips, and many companies are eager to jump on the bandwagon. But before you dive into implementing AI in your organisation, it\u2019s important to understand that AI is far from \u201cplug-and-play.\u201d While it\u2019s easy to experiment with external AI services (i.e., those you access online via your browser, such as Chrome or Edge) like ChatGPT or Gemini, the picture becomes far more complex when you want an AI solution that can accurately answer your business-specific questions\u2014while also complying with rules and standards.<\/p>\n\n\n\n

A context-specific language model that needs to handle your company\u2019s data requires solid data governance. If you don\u2019t have control over what is personally sensitive, business confidential, or subject to legislation, you risk leaking information that can damage both your reputation and compliance. So, how do you avoid the pitfalls when getting started with AI? Here\u2019s a guide on how to do it right.<\/p>\n\n\n\n

Bring the large language model into your small organisation<\/strong><\/h2>\n\n\n\n

Leverage an existing large language model, such as Mistral AI (France), ChatGPT (USA), or Deepseek (China), which already has the foundational training in place. By moving it into your own secure environment, you can:<\/p>\n\n\n\n

    \n
  1. Handle personal and business-sensitive data securely<\/li>\n\n\n\n
  2. Reduce hallucinations<\/li>\n\n\n\n
  3. Create dedicated solutions with access to your organisation\u2019s own data<\/li>\n<\/ol>\n\n\n\n

    Without having to train a large language model from scratch.<\/p>\n\n\n\n

    And it\u2019s secure. Not because France, the USA, and China are secure countries (France is probably still quite secure for Danish data), but because you take a language model and move it into your own secure IT environment. <\/p>\n\n\n\n

    A strong foundation is crucial<\/strong><\/h2>\n\n\n\n

    Many companies quickly discover that it\u2019s not just about \u201cgetting an AI.\u201d Often, it\u2019s the strategic approach to AI and control over data that are lacking. Before a company-specific AI can make sense, it\u2019s essential to have a good handle on your IT landscape, your data streams, and the quality of the data you\u2019ll feed your language model. At the same time, you need to incorporate requirements from GDPR and the EU\u2019s AI Act into your strategy. <\/p>\n\n\n\n

    ChatGPT or Gemini can certainly be used for general purposes, but an AI that needs to handle specific business data should live in an environment where the data\u2019s lifecycle is controlled from collection to deletion. This requires technical and organisational maturity, especially if you have a more complex setup with many services and data sources.<\/p>\n\n\n\n

    Integrated into the architecture \u2013 not in silos<\/strong><\/h2>\n\n\n\n

    To optimally utilise an AI solution, it needs access to all relevant parts of the company\u2019s data and context\u2014not just run in isolation in a smaller part of the business. It\u2019s about integrating the AI solution into your IT architecture and data landscape. For example, an IT landscape built on a service- or event-driven architecture can continuously feed language models with data from various systems. This way, you can prevent your AI solution from reinforcing silos. <\/p>\n\n\n\n

    On the way to an AI-driven future<\/strong><\/h2>\n\n\n\n

    AI can be a significant advantage for everything from internal Q&A and document management to automated customer support. But typical mistakes occur when data is not in order, when the AI hasn\u2019t been thoroughly tested in a pilot phase, or when employees aren\u2019t properly trained in using an AI tool. It\u2019s about allocating time and resources to establish a solid knowledge base among both leaders and employees, setting up a data governance model, establishing a permission framework to set boundaries, and monitoring performance with KPIs that measure efficiency, quality, and ROI.<\/p>\n\n\n\n

    To prevent employees from experimenting with external AI tools and risking the sharing of confidential data, you should offer a company-specific AI model. It can be used like any other public AI model to start with, and gradually include data for internal knowledge search, document management, or customer support. This method ensures a controlled and compliant AI solution for your company.<\/p>\n\n\n\n

    If you get off to a good start, AI can become an integrated part of your business processes. In the long run, you can shut down external services that pose a security risk. It\u2019s also crucial to stay updated on legislation, technological possibilities, and best practices. By combining compliance and innovation, you can reap the benefits AI can offer\u2014without taking unnecessary risks or losing control of your data.<\/p>\n\n\n\n

    What to remember when getting started with AI:<\/strong><\/h2>\n\n\n\n
      \n
    1. Build an AI strategy: What does your organisation want to achieve with AI?<\/li>\n\n\n\n
    2. Get control of your data: A solid data strategy and data governance architecture are essential. Without them, you risk building on shaky ground.<\/li>\n\n\n\n
    3. Think compliance from the start: Standards like ISO 27701 (privacy protection) and ISO 42001 (AI implementation) can help meet requirements and regulations from, for example, GDPR, ISO standards, and the EU\u2019s AI Act, and should be an integral part of your AI strategy.<\/li>\n\n\n\n
    4. Integrate AI into your existing IT architecture: Avoid silos and ensure that the AI has access to the right context.<\/li>\n\n\n\n
    5. Test thoroughly in a pilot phase: Before scaling, make sure the AI works as it should.<\/li>\n\n\n\n
    6. Offer an internal AI model: This way, you prevent employees from using external tools that could pose a security risk.<\/li>\n<\/ol>\n\n\n\n

      The future of AI in companies<\/strong><\/h2>\n\n\n\n

      If companies get a handle on the fundamental pitfalls, AI can become a natural and highly significant part of standard processes. We will increasingly see AI agents being used for support, process optimisation, and service operation. And the companies that are most effective and get the most out of their AI model have thought AI into their strategy, trained their employees, and trained their models on their own data, thereby ensuring they are context-specific.<\/p>\n\n\n\n

      AI is a gamechanger for companies, but only if implemented correctly. By avoiding the pitfalls and setting a solid strategy, you can ensure that your organisation is ready to reap the benefits\u2014without losing control.<\/p>\n\n\n\n

      <\/p>","protected":false},"excerpt":{"rendered":"

      AI er p\u00e5 alles l\u00e6ber, og mange virksomheder er ivrige efter at hoppe med p\u00e5 b\u00f8lgen. Men inden du kaster dig ud i at implementere AI i din organisation, er det vigtigt at forst\u00e5, at AI langt fra er “plug-and-play”.<\/p>","protected":false},"author":1,"featured_media":209,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"inline_featured_image":false,"footnotes":""},"categories":[29],"tags":[30,31],"class_list":["post-207","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-ai","tag-ai","tag-genai"],"aioseo_notices":[],"_links":{"self":[{"href":"https:\/\/tiwastech.com\/en\/wp-json\/wp\/v2\/posts\/207","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/tiwastech.com\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/tiwastech.com\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/tiwastech.com\/en\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/tiwastech.com\/en\/wp-json\/wp\/v2\/comments?post=207"}],"version-history":[{"count":2,"href":"https:\/\/tiwastech.com\/en\/wp-json\/wp\/v2\/posts\/207\/revisions"}],"predecessor-version":[{"id":211,"href":"https:\/\/tiwastech.com\/en\/wp-json\/wp\/v2\/posts\/207\/revisions\/211"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/tiwastech.com\/en\/wp-json\/wp\/v2\/media\/209"}],"wp:attachment":[{"href":"https:\/\/tiwastech.com\/en\/wp-json\/wp\/v2\/media?parent=207"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/tiwastech.com\/en\/wp-json\/wp\/v2\/categories?post=207"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/tiwastech.com\/en\/wp-json\/wp\/v2\/tags?post=207"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}