Artefact’s Post

AI thrives on quality data; its governance can't be ignored. Why is this significant? Every groundbreaking AI application, from the chatbots you interact with to the algorithms predicting market trends, relies heavily on data. And not just any data – quality, well-governed data. Here's a quick peek into its importance: ✅ Quality Data = Reliable AI: The effectiveness of AI models is directly tied to the quality of the data they're trained on. ✅ Protect and Respect: Ensuring the integrity and security of data isn't just a technical need; it's about respecting user privacy. ✅ A Strategic View: Treating data as a strategic asset can be the differentiator in today's competitive landscape. ✅ Consistency is Key: With multiple systems in play, ensuring data consistency becomes paramount. As we navigate the rapid advancements of the AI world, consider this: How can businesses truly maximize the benefits of AI without first mastering their data? ---------- 🎁 If this topic resonates with you, I'll share resources and articles in the comments, emphasizing the role of data governance in the era of AI.

How organisations can do more with AI - Technology Record: How organisations can do more with AI  Technology Record #datagovernance #CDO #finperform

Are you feeling overwhelmed by data silos, expertise gaps, and the complexities of #AI adoption? I’ve watched many organizations eager to leverage AI get stuck on the "how." In this article, I share my insights on why managed services is the ideal launchpad for operationalizing AI success. Discover ways to conquer data challenges, streamline processes and drive tangible business results. Check out the full article: https://lnkd.in/dd-Y5MJM #AIOps #ManagedServices #AIAdoption

Strategizing usage of AI is crucial for achieving success from the perspective of the C-Suite.

The best definition of an AI system yet! An "AI system" is defined as a machine-based system capable of operating with varying levels of autonomy, designed to infer from inputs to generate outputs like predictions, content, recommendations, or decisions that can impact both physical and virtual environments. Why do I consider it the best definition? This is the EU AI Act's precise definition of an "AI system". It significantly influences compliance and regulatory responsibilities for developers and deployers within the AI domain. By categorizing AI systems as machine-based entities capable of operating with varying levels of autonomy and adaptiveness, the Act sets a clear boundary for what technologies fall under its regulatory scope. This clarity is crucial for developers and deployers, as it delineates the types of AI systems that require adherence to the Act's stringent requirements, including risk assessment, transparency, and data governance protocols. Understanding this definition is paramount for businesses and innovators in the AI space. It not only informs them of the regulatory landscape but also guides the development and deployment processes to ensure compliance. For AI systems that meet the Act's criteria, developers must incorporate design considerations that align with the Act's safety, accountability, and transparency mandates. Similarly, deployers must be diligent in selecting AI systems that comply with the Act, understanding their operational capabilities, and ensuring their use aligns with the intended purposes as defined by the Act. This comprehensive understanding fosters a culture of compliance and innovation, encouraging the development of AI technologies that are not only advanced but also ethically responsible and legally compliant. 

This article explores the use of cutting-edge AI tools in transforming business operations. It discusses the different types of AI tools, their benefits in tasks like automation and data analytics, as well as their limitations in areas such as content curation and automated interactions. The article emphasizes the need for caution when implementing AI, highlighting the importance of balancing AI capabilities with human oversight to ensure accuracy, data privacy, and security in business operations. #ai #artificialintelligence #businessautomation #digitaltransformation #aiinbusiness #dataanalytics #machinelearning #chatbots #airisks #aibenefits

Raymond Holder recently said that, "the point is not the technology, the point is to move the mission forward and help people". For me, this encapsulates the essence of what digital modernization with a human-centered approach is all about- using technology to improve [not replace] the human experience. As I think about this, it also brings to mind that innovation requires an agnostic approach to technology, as no single solution can dominate in order to remain on the cutting edge of what is new, next, and necessary. However, one technology, in particular, might challenge this way of thinking. Artificial Intelligence (AI), while not new to the Federal space, has yet to demonstrate its full potential due to the associated risks. The potential to improve customer experience with AI lies in federal agencies establishing an enterprise-wide approach and governance framework. This framework should align AI efforts with a strong overarching data strategy, ensure swift response times to evolving policies, and it must support adoption while mitigating risks. https://lnkd.in/eSq6yg4u

The world of #technology is constantly evolving, and so should your approach to managing it. In this article, industry expert Matthew Lee from Thoughtworks explains how AI-powered managed services can revolutionize your IT operations: https://ter.li/nlw1uh #AI #ManagedServices #ITOps