Dave is charged with defining and executing on strategy for ModelOp Center, paving the way for customers to overcome their governance challenges and unlock the value of AI.
The new ModelOp Version 3.3 with the world’s first AI Governance Score
AI has an accountability problem
Enterprise CEOs are making substantial promises to investors and shareholders about using AI to drive business transformation. Yet, at the same time, less than 2% of executives can identify how AI is being used in their companies and its risks.
In many organizations, CEOs, CDAOs, CIOs, and AI leaders struggle to get visibility into AI initiatives, as the variety of new AI technologies constantly evolves at unprecedented rates, and the varying usages of AI by different business teams is skyrocketing. Furthermore, given the complexity of the technologies, enterprises struggle to identify the risks and how they differ with each technology.
Many organizations naively believe that their data science tool or vendor have all of the risks associated with the use of AI covered. But the reality is that these data science or MLOps tools were designed to build the best model, not objectively assess the risks associated with using this model for a specific business purpose. Data science capabilities such as experimentation management and pipeline execution are great for building a great model, but they don’t systematically identify risk, enforce governance processes, and provide audit-ready reports — all requirements for proper AI Governance.
Furthermore, those data science and MLOps tools are meant for model development, but internally developed models typically make up only a fraction of the total AI usage throughout an organization — many enterprises use third-party (vendor-purchased) models or have software with AI-embedded, like Salesforce Einstein or Microsoft Copilot.
This can leave enterprises with burdensome, static, and seemingly untenable methods for getting their arms around the usage and risk of their AI initiatives. And there’s no time to wait, the EU AI Act and the US Office of Management and Budget (OMB) have urgent deadlines for implementing AI safeguards in 2024.
Introducing ModelOp 3.3: AI Visibility and Accountability for Executives
ModelOp, the world’s leading AI Governance software for enterprises, addresses these visibility and accountability challenges with the release of ModelOp Version 3.3. This new release includes the world’s first AI Governance Score, which gives executives a standardized metric to measure risk across diverse AI initiatives, regardless of whether an organization is using generative AI, in-house, third-party vendor, or embedded AI systems. As with prior versions, ModelOp is powered by automation, to provide the C-Suite with the assurance that AI Governance policies are being followed, but not slowing down innovation for business teams that are rapidly trying to harness the power of AI.
ModelOp 3.3 Capabilities
ModelOp 3.3 extends support for generative AI, enabling enterprises to quickly harness the power of Large Language Models (LLMs) while safeguarding the business. New users will be able to get up to speed even more quickly and have additional intuitive tools at their fingertips. Version 3.3's major enhancements include:
- AI Governance Inventory & Comprehensive Use Case Management — Version 3.3 introduces an enhanced AI Governance inventory, making it straightforward for users to register and customize new AI use cases, including those involving generative AI, and quickly bulk import existing models.
- AI Governance Score & Automated Compliance Controls — The new ModelOp AI Governance Score offers a rapid assessment tool — designed for leaders and executives — to ensure continuous adherence to policy and regulatory compliance, including for third-party vendor and embedded systems.
- Enhanced Reporting on AI Governance Adherence — With enhanced search capabilities, users can swiftly navigate AI initiatives across the organization, generate comprehensive AI use case reports, maintain oversight of AI systems, and perform critical comparisons of model versions focusing on performance, fairness, bias, and more.
What ModelOp 3.3 Enables Enterprises To Do
Governance Score to simplify AI models for executives
Unlike traditional GRC (Governance, Risk, and Compliance) systems that rely heavily on static spreadsheets and documents, ModelOp’s AI Governance Score transforms governance into a dynamic and continuous process.
Advanced use case experience for proactive risk management
This advanced capability within the AI Governance inventory continuously monitors for new risks associated with AI use cases. Risk assessments are also consolidated into a comprehensive governance score.
New Inventory use case and advanced search capabilities
The new inventory functionality allows users to search across AI use cases using custom metadata to quickly filter and retrieve relevant information. This customizable search capability ensures that enterprises can easily manage and access AI use cases based on parameters most critical to their operations.
Tailored AI Onboarding
The AI onboarding wizard provides users with a powerful tool to capture and manage specific AI initiative information through a guided form engine. This allows for tailored metadata to reflect unique organizational needs, ensuring that all relevant data points are captured and easily accessible.
Enhanced user interface for simplified risk management
This significant update to the user interface streamlines the identification, management, and mitigation of AI risks through an intuitive and simple experience, and leverages automation to systematically identify common risks.
With ModelOp 3.3 — including the world’s first AI Governance Score — leaders gain unprecedented visibility into the AI being used across their organizations, which enables enterprises to deliver transformational and responsible AI systems. ModelOp 3.3 enables executives to stay on their front foot as regulations like the EU AI Act and US OMB rules take effect.
Learn More About How ModelOp 3.3 Can Help Your Enterprise
Request a demo of ModelOp 3.3 today and learn how you can implement AI Governance in fewer than 90 days using our Minimum Viable Governance approach.
