Generative AI
How Metataxis helps organisations with AI
AI solutions are only as useful as the data by which they are trained and built. Yet organisational data is diverse, massive in size, and exists in multiple formats (paper, audio, video, images, emails, and other types of unstructured data, as well as structured data) sprawled across locations and silos.
As many organisations look to implement AI, all this information must be accessible and usable to maximise its business value.
Metataxis helps organisations address these data challenges, to achieve AI readiness and fully realise the benefits of AI solutions.
From conducting a comprehensive inventory of your data and assessing data quality standards, to developing governance and security strategies to ensure data is used appropriately, we can help transform your data to unlock the full potential of AI and see a return on your investment in as short a time as possible, while remaining legally compliant and within appropriate ethical boundaries.
Metataxis offers a comprehensive and customised three-staged adoption plan to support AI implementation success.
Evaluate your readiness to adopt AI
The key to AI success lies in data preparation. Our AI Readiness Report is designed to evaluate your readiness to successfully adopt, deploy and embrace AI across your organisation.
To build your personalised AI Readiness Report, our information management consultants will assess and catalog your information and data quality to make a series of recommendations, encompassing:
- Information and data strategy – review both structured and unstructured data, within the context of your business goals and user needs, to identify where AI technology can bring the most value
- Leadership and governance – review and develop leadership roles and responsibilities; establish a data governance framework
- Data environment and technical readiness – create data environment maps, and assess the content against key data standards required for Gen AI, including data security, governance, and access
- Data readiness – assess and develop a roadmap to ensure information and data is ready for AI, including quality, data sprawl, ROT (redundant, outdated, and trivial information), fragmented data storage; review and create robust data processes and safeguards
- Organisational change and user enablement – review user readiness to accept, use and understand Gen AI tools and outputs; develop new information management policies including lifecycle management, retention and destruction
- Information risk management – develop a robust risk management framework ensuring new legal and regulatory requirements are considered
- Training needs – identify employee capabilities and training requirements, including information and AI literacy and prompt engineering to ensure smooth adoption of AI
Define the initiatives to become AI ready
The next step is to consider how AI will be governed and what accommodations must be made to existing governance programmes to ensure that AI is used in a secure, fair and compliant manner. As enterprise AI tools, such as Copilot, work with your enterprise content, Gen AI success also depends on a well-structured information architecture. Without this, AI systems typically struggle to generate meaningful results and offer real value.
Deploy those initiatives to successfully adopt and use AI
Once your foundations are defined, we can help you leverage and deploy the initiatives outlined in your information architecture and information governance frameworks to successfully adopt and use AI.
