Companies that even hint at leveraging AI are seen as high-potential players in today’s tech-driven scenario.
With increased AI adoption, the need for robust AI governance for responsible and compliant use has also grown. This paves the way for governance tools like compliant management tools and bias detection and mitigation tools to become popular choices.
To compile these tools, G2 has announced a new category called AI Governance Tools. These solutions help buyers manage, monitor, and optimize AI systems.
What are AI governance tools?
AI governance tools are designed to help organizations manage and monitor AI systems responsibly. These tools help organizations comply with regulations by detecting biases and ensuring transparency in AI systems.
AI governance tools typically offer data privacy and security control features, as well as the management, performance monitoring, and optimization of AI model lifecycles. These tools monitor key performance indicators (KPI) like accuracy, latency, and throughput. They also detect potential biases in real time, ensuring fairness across different user groups.
AI governance tools ensure that AI systems adhere to international and local regulations by automating compliance checks. They also assess AI systems for risk by providing transparency reports.
How AI governance differs from data governance
Today, AI is extensively used in almost every organization. With increased AI adoption, companies are highly vulnerable to data misuse. While companies have traditionally used data governance software to maintain data quality and regulate data usage, let’s understand what AI governance tools have extra to offer.
AI governance and data governance address distinct aspects of managing technology within an organization. While data governance focuses on ensuring the quality, security, and compliance of data throughout its lifecycle, AI governance addresses the unique challenges of AI systems. It provides model transparency, ethical considerations, and accountability, ensuring AI outputs are fair, unbiased, and aligned with regulatory and organizational standards such as the General Data Protection Regulation (GDPR), EU AI Act, and so on.
The data governance category on G2 deals with data privacy laws, access controls, and maintaining data accuracy, forming the foundation for building reliable AI systems. AI governance tools help govern AI/ML models, algorithms, and outcomes. They monitor real-time AI model performance and adapt to changes like model drift.
Future of AI governance
The future of AI governance depends on creating adaptable, scalable, and proactive systems that manage risks, boost innovation, and build trust among users and stakeholders. The already increasing complexity of AI systems will drive demand for advanced governance solutions capable of monitoring biases, ensuring transparency, and maintaining accountability in real time. Thus, it is safe to say that the AI governance space is set to evolve greatly in the coming times.
Dive into the G2 Trends 2025 to unlock AI utilization and measurable results.
Edited by Supanna Das
Ensure transparent and compliant AI
