Introducing Enterprise Safeguards for Generative AI

Large Language Models and Generative AI have massive transformational potential, so Corporate Boards and C-Level executives are putting enormous pressure on business, analytics, and IT leaders to quickly leverage this technology to improve revenue generation, increase customer satisfaction, and drive efficiencies. However, AI —and especially Generative AI — presents multiple socio-technical challenges that must be addressed to avoid financial, regulatory, and brand risk exposure.

Enterprise AI leaders are challenged to urgently navigate three major trends:

• Corporate boards are hyper-focused on using Generative AI, especially for customer service
• Executives need to protect the company from the brand, financial, and regulatory risks associated with Generative AI
• Engineering, finance, marketing, and sales are swiping credit cards to use third-party Generative AI tools like ChatGPT, Llama2, Claude, Bard, and Titan

Furthermore, there’s unprecedented support from academic institutions, governments, technology vendors, and citizens for regulations that provide guardrails for the safe and humane use of AI. From the EU Artificial Intelligence Act to the US NIST AI-Risk Management Framework and industry-specific guidance such as the Canadian OSFI E-23 Extensions for AI, the regulations will only continue to expand and evolve.

The bottom line is clear — enterprises can’t afford to wait to tackle AI Governance — the transformational potential is real, but the risks are already exposed within organizations.

That’s why ModelOp, the leader in AI Governance software for enterprises, released version 3.2 of ModelOp Center: to safeguard the use of Large Language Models (LLMs) for the entire enterprise.

Can't wait to see it action? Then contact us to schedule a live demo on governing LLMs.

ModelOp Enables AI, Risk, Compliance, Data, and Security Leaders To Accelerate Innovation with Generative AI

ModelOp Center version 3.2 is the first commercially available software that enables enterprises to safeguard Large Language Models (LLMs) and Generative AI without stifling innovation. 3.2 builds on ModelOp’s existing governance support for all models — including regressions, Excel, and vendor models — by adding new capabilities to manage LLM ensembles, track value, chart and visualize risks, provide universal monitoring, and enforce governance controls through model life cycle automation.

Supporting Generative AI Use Cases in a Fiscally Responsible Way That De-risks the Enterprise

The era of enterprise AI is here and companies are diving into Generative AI. According to Bain & Company over 40% of businesses are adopting or evaluating the top six applications for Generative AI:

• Chat-based interfaces embedded in products
• Coding assistants
• Customer communications / contact centers
• Knowledge assistants (e.g. sales copilot)
• IT automation / cybersecurity
• Content development (e.g. marketing personalization)

Generative AI is a catalyst for AI Governance. The innovative capabilities released in ModelOp Center version 3.2 were strategically built based on feedback from ModelOp customers who are dealing with the urgent issues surrounding both LLMs and more traditional models that have long powered decision-making in global enterprises.

Track Value and Visualize Risks

While LLMs offer enterprises transformational opportunities, they also need to be carefully tracked from a financial, data science, legal, security, and IT perspective, as there are many moving pieces that can introduce risk to the organization. ModelOp Center provides comprehensive, real-time insight into all facets of LLMs to present a true “Portfolio View” of an enterprise’s AI investments.

Track AI Usage and Monitor Production Risks

Version 3.2 adds support for comprehensive LLM Usage Tracking and Monitoring, including:

• Inventory: support for classifying and tracking LLM use cases and models in the ModelOp Center Governance inventory, including the ability to govern LLM ensembles
• Generative AI Asset Management: support for prompt templates, RAILS, etc. for Generative AI asset tracking
• Monitoring: support for Automated Production Monitoring of LLM related metrics, including sentiment analysis, PII/PHI analysis, and cross-LLM performance analysis

Enforce Controls Through Workflow Automation

ModelOp Center version 3.2 extends the existing governance workflow and controls enforcement to support LLMs and Generative AI, including:

• Risk Tiering: automated rules for proposing risk tiering based on key model inputs
• Governance Workflows: out-of-the-box regulatory workflows to support LLM specific testing and other gates  
• Controls Check: support for Excel-based attestation of controls, to support LLM/AI-specific policies
• Generative AI Testing: automated testing & documentation generation for LLM specific metrics

Take Advantage of Pre-built Templates and Out-of-the-box Tests

ModelOp Center version 3.2 extends its vast set of out-of-the-box capabilities by adding the following:

• Out-of-the-box Governance Workflows: specific LLM checks, such as ensuring that all LLM packages contain prompt templates and guardrails as part of the model package
• Out-of-the-box LLM Tests and Monitors
• Out-of-the-box LLM Review/Validation Reports

Enterprises Cannot Wait Any Longer to Establish AI Governance

AI governance is way more than model monitoring, ethics, and fairness. ModelOp’s AI governance platform delivers the critical capabilities needed to inventory, control, and report on all models – including LLMs – across your enterprise.

Watch this short demo video on how you can use ModelOp to govern LLMs, including how to:

• Accelerate innovation and measure model ROI
• Enforce AI guidelines that de-risk the enterprise
• Achieve significant faster time-to-value and lower total cost of ownership than building in-house solutions

Explore ModelOp Center version 3.2 Today

Want to see a live demo? Fill in the contact form and we’ll be in touch within one business day.

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