Feature Article: Integrating AI in DAM: A Strategic Approach
For the second part in his series on Metadata, DAM and AI, Mark Davey digs deeper into the key practical considerations when implementing AI within DAM. This concise and comprehensive article covers everything from making sure your organisation is ready to adopt new technologies by preparing a well-defined strategy and acquiring a thorough understanding of the numerous technical aspects required for maximum DAM interoperability (API compatibility, metadata standards, field mapping, exchange protocols, security, scalability), through to vendor selection, implementation, and ongoing maintenance and improvement.
“A clear and well-defined AI strategy is crucial for the successful integration of AI into your DAM system. Over the years, I’ve seen that those who take the time to strategise not only achieve smoother implementations but also extract more value from their investments and teams.
Integrating AI into a DAM system often involves connecting multiple technologies and platforms through Application Programming Interfaces (APIs). Over time, I’ve learned that the success of these integrations depends on careful planning and a thorough understanding of how these systems will interact.” [Read More]
Mark continues by highlighting the importance of effective vendor relationships, and how choosing experienced yet flexible providers that can demonstrate a commitment to ongoing support, collaboration and innovation is crucial to the success of your AI initiatives.
“Establish clear SLAs with your vendors to define expectations for performance, uptime, support, and response times. This ensures that your DAM system remains operational and effective even as AI tools are integrated. SLAs should be realistic and enforceable, with penalties for non-compliance.
Select vendors who demonstrate a commitment to innovation and staying ahead of industry trends. This helps ensure that your AI and DAM integrations remain relevant and effective in the face of rapid technological change. A vendor who is focused on the future will be better equipped to support your evolving needs.” [Read More]
Mark also highlights a number of common obstacles that organisations face when implementing AI, including a lack of sufficient resources and investment, poor vendor support, and neglecting the importance of the underlying data by focusing too much on software minutiae.
The article concludes with a series of insights and practical tips on the implementation process itself, including pilot testing, fostering user adoption, continuously monitoring and tweaking your integration in order to achieve maximum efficiency and value, and the importance of establishing and enforcing clear data governance guidelines and metadata management practices.
You can read the full article at the link below.
https://digitalassetmanagementnews.org/features/integrating-ai-in-dam-a-strategic-approach/
Share this Article: