ModelOp, the world’s leading AI Governance software for enterprises, has officially announced the launch of ModelOp Version 3.3, which happens to be the world’s first ever AI-driven governance score system. According to certain reports, the stated system enables enterprise leaders to score AI risks and continuously govern AI initiatives as global regulations evolve. In practice, this presents itself as an ability to provide executives with real-time visibility into all AI initiatives — including generative AI, in-house, third-party, and embedded AI systems, as well as their risks across the entire enterprise. Talk about the whole value proposition on a slightly deeper, we begin from its promise of AI Governance Inventory & Comprehensive Use Case Management. You see, with an enhanced AI Governance inventory, the Version 3.3 makes it possible for you to register and customize new AI use cases, including those involving generative AI. Beyond that, you can also quickly bulk import existing models. Next up, we must get into the technology’s AI Governance Score & Automated Compliance Controls, where ModelOp AI Governance Score offers a rapid assessment tool for the purpose of ensuring continuous adherence to policy and regulatory compliance, including for third-party vendor and embedded systems.
“ModelOp 3.3 gives executives clear visibility into the performance, value, and risk of all AI initiatives across the entire enterprise. The game-changing AI Governance Score introduces a standardized metric to measure risk across diverse AI initiatives, which is helpful given the complexity and diversity of projects,” said Pete Foley, CEO at ModelOp. “Unlike other solutions, ModelOp offers true AI Governance software tailored for executives, providing a single source of truth for AI Governance and Risk Management. It’s comprehensive, agnostic, and answers the biggest AI accountability questions facing every executive at every enterprise.”
Fair enough, the solution in question also brings to the fore a set of reporting capabilities in regards to AI Governance Adherence. Thanks to its comprehensive and intuitive search mechanism, ModelOp Version 3.3 is able to help users 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. Hold on, there is more, considering we still haven’t acknowledged the product’s commitment towards customizing the entire onboarding process through AI. This it does by putting to use its AI onboarding wizard who relies upon a guided form engine to help you capture and manage specific AI initiative information. Such functionality allows tailored metadata to reflect unique organizational needs. Complimenting the entire gamut of features is, of course, a top notch user experience. Powered with an intuitive and simple experience, ModelOp Version 3.3 applies automation to systematically identify common risks, and therefore, streamline the identification, management, and mitigation of AI risks.
The overarching development here delivers a rather interesting follow-up to one Accenture report, where the company claimed that less than 2% of executives can currently identify how AI is being used in their companies, making up an enormous accountability problem. This problem, if left untreated, can slow innovation and expose enterprises to significant security, data privacy, regulatory, brand, and financial risks. On top of that, it also contextualizes US Office of Management and Budget’s decision to issue a new memo in M-24-10, mandating each of the 400+ Federal Agencies to appoint Chief AI Officers by the end of May and to implement AI safeguards by December 1, 2024.