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Through 2026, at least 80% of unauthorized AI transactions will be caused by internal violations of enterprise policies concerning information oversharing, unacceptable use or misguided AI behavior rather than malicious attacks. Is the status quo of your AI governance strategy good enough to overcome this? Download* the 2025 Gartner Market Guide for AI Trust, Risk, and Security to learn more about emerging solutions and sample vendors: https://hubs.li/Q03dnW9v0 *This report is available for a limited time from Monitaur. #AIgovernance #AIsecurity #AIrisk

?? AGENTIC AI GOVERNANCE - PRACTICAL TIP #1 As highlighted in our recent article on Agentic AI governance, one of the biggest challenges in deployment is the increased difficulty in responsibly building and validating these systems. Why is this different from traditional AI? Traditional model development focuses on single-task abstraction. LLMs generate human-like text. But Agentic AI introduces multi-step sequences with complex decision points that multiply the validation challenges. ?? Practical governance tip: Define the different states of your Agentic AI system and decision points with possible results. This is important for building, testing, and stress testing medium and high-risk systems. Questions for your team: ?? Have you defined every possible state and transition in your Agentic AI system? ?? Do you have validation methods that are suitable for multi-step optimization? ?? Are your quality gates enough for complex decision sequences? Learn more here: https://hubs.li/Q03d7VjW0 Follow Monitaur so that you don't miss this series. Coming soon: "Multi-step, contextual monitoring." #AIGovernance #AgenticAI #AIrisk

The business case for AI governance in 2025: When "good enough" isn't good for business. It's easy to think that AI governance is just about checking boxes to comply with varying regulations. "Good enough" often gets by. But that concept changes quickly when teams can't show real results from their AI projects. That's when key stakeholders notice there's not much progress, visibility, or value being delivered. AI governance is about combining risk management with plans to meet business and stakeholder goals. Clear processes and practical steps can help align these goals by setting clear requirements and using best practices when building complex AI systems. When this happens, compliance becomes one of the bonuses of having AI systems with high visibility and reduced risks throughout the lifecycle. Rules and regulations will keep changing, and so will the AI models and products you use. But small, proven successes lead to bigger successes over time. Showing results from your AI investments today through actionable governance is important for the future of your business. https://hubs.li/Q03cm5DH0

"AI trust, risk, and security issues reveal problems between departments, forcing teams to collaborate across boundaries to solve these challenges.” That is one of 4 key findings by Gartner?. Discover more in the?2025 Market Guide for AI Trust, Risk, and Security Management (TRiSM). Monitaur is named as a Representative Vendor and is providing this report for a limited time. AI leaders should use this report to understand TRiSM and discover solutions for their organizations. Download your copy today. https://hubs.li/Q03chnKW0 #aigovernance #aisecurity #airisk

Are you implementing, deploying, or managing AI systems within your organization? Check out this executive discussion where Monitaur CEO and co-founder Anthony Habayeb joins Miguel Edwards of 5M Consulting to explore "What insurers need to know about AI governance." At Monitaur, we've consistently observed that effective AI governance serves as a strategic business enabler rather than a regulatory burden—delivering 2-3x greater return on AI investments for organizations with mature governance frameworks. Key insights from the conversation include: ? Structured governance establishes clear mechanisms for project prioritization, organizational alignment, and performance measurement ? A comprehensive governance approach is essential regardless of whether AI systems are developed internally or acquired from vendors ? Early implementation of governance policies and visibility mechanisms creates a foundation for sustainable AI growth As Anthony notes, "Insurance is an industry built on models," making it an ideal industry for others to follow in effective governance implementation. Does your organization recognize AI governance as an enabler yet? Discover how governance can transform your AI strategy from a compliance requirement into a competitive advantage here: https://hubs.li/Q03bgWTS0

This episode of The AI Fundamentalists is dedicated to the modelers and engineers out there who are skeptical of what the hype train is calling "AI agents" The AI systems of tomorrow will be complex. In this discussion, we explore the right tools for the right jobs in these evolving systems. ?? More AI agent disruptors (0:56) ?? AI Paris Summit - What's next for regulation? (4:40) ?? Modeling paradigms explained (10:33) ?? Paradigm 1: Agents (11:23) ?? Paradigm 2: Generative (14:26) ?? Paradigm 3: Mathematical optimization (regression) (18:33) ?? Paradigm 4: Predictive (classification) (23:19) ?? Paradigm 5: Control theory (24:37) ?? The right modeling paradigm for the job? (28:05) Plus, commentary on recent AI events that make these paradigms and governance of their resulting systems that much more important. https://hubs.li/Q039sfnV0

Before you pursue AI at all costs (too late?), listen to this conversation about the aspirational vs practical uses of AI systems. ROI might be closer than you think. #insurance #analytics #aiprojects

Did you get your copy of the Executive AI Governance Playbook? ? By forging ahead with AI or any model-based system (hello, agents??), how will you know what works, what to do more of, buy more of, and what to quit? Regulation helps, but objectives and performance speak ROI's language. High expectations for AI might not be realized without balancing value and risks via well-thought-out AI governance.?According to Gartner?, a good AI governance program should be able to: - Create, maintain, and enforce AI governance policies and controls - Create and develop an AI governance operating model - Design, develop, integrate, test, and?deploy governance oversight systems. Get the Executive AI Governance Playbook from Gartner while this complimentary download period lasts. UPDATE: Download period has ended. Contact us if you have any questions: https://lnkd.in/ebJ5wDff

What are regulators really looking for from AI systems in insurance? Watch this encore presentation to get the answer to that question and more.

Before you put those AI agents into production... ?? #insurance #insurtech #aigovernance