In the realm of data and analytics (D&A) governance, the integration of generative AI (GenAI) capabilities within D&A governance platform is revolutionising the landscape, allowing for more automated, effective, and coordinated decision-making.
The implications of GenAI on technology capabilities enabling D&A governance are profound. This transformative technology not only boosts the efficacy of D&A governance platforms but also enhances the productivity and user experience of personnel involved in governance, particularly nontechnical users like data stewards.
1. Transforming governance decision-making
Generative AI, particularly large learning models (LLMs), play a pivotal role in bridging the gap between natural language and human language within D&A governance platforms. By leveraging GenAI alongside other technologies such as knowledge graphs and metadata activation, organisations can unlock a broader spectrum of governance use cases while addressing inherent limitations like inaccuracies and hallucinations. The constructive collaboration between GenAI and traditional AI/machine learning (ML) empowers different governance personas to make informed decisions at scale and with heightened efficiency, thereby accelerating time to value of data and analytics governance programs.
GenAI offers multiple use cases for D&A governance platform capabilities, such as automating documentation processes, suggesting industry-specific regulations, streamlining governance tasks and enhancing operational workflows.
Infusing domain-specific or institutional knowledge into GenAI outputs and using metadata for output validation can enhance the accuracy and diversity of GenAI-enabled governance use cases. As D&A governance platform vendors continue to embed GenAI in their product roadmaps, considerations around cost-effectiveness and performance comparisons with traditional AI/ML solutions will be paramount in broad-based adoption of GenAI in such platforms.
2. Understanding vendor-specific roadmaps and risk mitigation strategies
In this evolving landscape, embrace GenAI not just for developing business-facing use cases but also for operationalising and scaling D&A governance initiatives. Understanding vendor-specific roadmaps and risk mitigation strategies is crucial, as is maintaining a human-in-the-loop approach for validating GenAI outputs.
Data stewards emerge as key players in this shift, requiring upskilling to navigate the nuances of training LLMs for specific use cases and ensuring the seamless integration of AI governance practices. By reimagining stewardship functions and fostering a culture of continuous learning within governance roles, organisations can harness the full potential of GenAI to drive intuitive decision-making processes that resonate beyond the confines of traditional data management teams.
The fusion of generative AI with D&A governance platforms heralds a new chapter in data stewardship and decision-making excellence. As organisations embark on this journey towards smarter governance practices, embracing GenAI as a catalyst for innovation and efficiency is critical, paving the way for more agile, informed, and impactful decision-making processes in the digital age.
Gartner analysts will provide additional analysis on D&A trends and the impact of AI technologies on the D&A team at the Gartner Data & Analytics Summit 2024, taking place 13-15th May in London.
Anurag Raj
Anurag Raj is a Senior Principal Advisor at Gartner. He advises Data and Analytics leaders on data management solutions, data strategy, data governance, data literacy and function management.
