“Businesses that understand intellectual property and how to leverage their digital assets with a roadmap are well placed to succeed. It would be unfortunate to pass on potential revenue and have unintended exposure to risks, including infringement.""
Program Benefits
- Evaluate the key attributes of digital asset management and the interface between business, creative and technology.
- Justify the value of Digital Asset Management and how it can integrate into current business, IT and marketing processes to create overall efficiencies.
- Determine what metadata fields and relationships are appropriate for AI integration leveraging meaningful metadata such as public domain data (e.g. color, shape, sentiment) and other business-centric data (e.g. product hierarchy, ingredients, etc.) in contextualizing and categorizing for data with your digital assets in the DAM.
- Perform requirements gathering and analysis for a DAM migration or implementation of a new DAM.
- Implement and facilitate an AI project management workflow that addresses both process and user experience and defines scope, resources, budget and timeline for a DAM system that is measurable.
- Optimize opportunities to increase the ROI of your digital assets across diverse content channels and verticals.
- Apply a user-centered strategic approach to creating a multi-platform and intuitive DAM ecosystem and developing an AI strategy.
- Employ best practices in metadata standardization, search, and taxonomy for the repurposing of digital assets.
- Understand how AI technologies like Machine learning (ML), Natural Language Processing (NPL), blockchain and other technology has impacts on IP rights management.
- Champion change for a digital transformation with a DAM systems integration that aligns with an organization’s goals.
- Create a Digital IP rights and risk management framework that is transparent, complies with regulations & industry standards, privacy and aligns with an organization’s vision and goals.
- Evaluate the key attributes of digital asset management and the interface between business, creative and technology.
- Justify the value of Digital Asset Management and how it can integrate into current business, IT and marketing processes to create overall efficiencies.
- Determine what metadata fields and relationships are appropriate for AI integration leveraging meaningful metadata such as public domain data (e.g. color, shape, sentiment) and other business-centric data (e.g. product hierarchy, ingredients, etc.) in contextualizing and categorizing for data with your digital assets in the DAM.
- Perform requirements gathering and analysis for a DAM migration or implementation of a new DAM.
- Implement and facilitate an AI project management workflow that addresses both process and user experience and defines scope, resources, budget and timeline for a DAM system that is measurable.
- Optimize opportunities to increase the ROI of your digital assets across diverse content channels and verticals.
- Apply a user-centered strategic approach to creating a multi-platform and intuitive DAM ecosystem and developing an AI strategy.
- Employ best practices in metadata standardization, search, and taxonomy for the repurposing of digital assets.
- Understand how AI technologies like Machine learning (ML), Natural Language Processing (NPL), blockchain and other technology has impacts on IP rights management.
- Champion change for a digital transformation with a DAM systems integration that aligns with an organization’s goals.
- Create a Digital IP rights and risk management framework that is transparent, complies with regulations & industry standards, privacy and aligns with an organization’s vision and goals.
Curriculum
The program is designed specifically for professionals working in organizations that are currently engaging in digital asset management or about to explore a digital transformation in the digitalization of assets, with the skills and competencies to be able to create a strategic vision and roadmap, as well as plan, implement and execute on a digital asset management strategy.