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discussions I have had over the last year, IT product companies appear to be moving towards an AI first model The traditional model—where product managers coordinate with software engineers, UI designers, data analysts Companies like Vercel, Replit, and dozens of Y Combinator startups demonstrate this model in action daily AI reliability and maintenance  - AI systems need monitoring, debugging, and optimization Develop AI model customization expertise  - Fine-tuning, prompt optimization, and model selection Master AI-human collaboration

Known-Unknowns (Complicated Domain) Here we have moderate visibility. Traditional models struggle to provide explanations for what occurs in this domain. State of AI Uncertainty Current AI technologies, particularly advanced systems that use large language models What aspects of AI should receive attention: the technology itself, the models, the companies developing we can't predict specific outputs with perfect accuracy We understand enough about potential failure modes

By extending VCA to encompass these dimensions, we create a more comprehensive model that affords management foundational principles enable practical applications including compliance streams, operational compliance models

For example, engineering has traditionally relied on algorithms, statistical analysis, models, and prediction

For AI systems, monitoring extends to model performance metrics, prediction latency, and data drift detection , it struggles with novel or complex failure modes. In AI contexts, observability encompasses the full model lifecycle—from data ingestion through training In AI systems—where complex models often operate as black boxes—explainability techniques like SHAP,

Current models are based on a reactive and transactional approach to how health care is delivered. focused on the future of health care, what it might look like, and how it can change from a reactive model We have the wrong model Reactive Transactional Funding the wrong things Regulation that constrains My thoughts Health care systems are based on a model that is not sustainable and it has been this way

The RACI (Responsible, Accountable, Consulted, Informed) model is a framework that defines roles and The Obligation Owner aligns with this model by assuming the role of the "Accountable" party for compliance obligations they make certain that obligation objectives are achieved and the other roles of the RACI model

analytics can help to prevent a total failure if controls can respond fast enough and if the failure mode due to a lack of knowledge (epistemic uncertainty) prediction is limited based on the strength of our models

This week we explore a question that was posed in reference to IIA’s 3 line model “should risk management As a quick overview: The 3 lines model is an updated version of what was previously known as 3 lines The first line of the IIA model focuses on management responsibility to deliver products and services The second line of the IIA model provides assistance to the first line to contend with risk. The model depends on all functions working together to create and protect value With respect to risk

brain, provides a useful model and operational approach applicable to this situation. Geoffrey Moore's concept of business zones aligns closely with McGilchrist's hemispheric model. Two Types of Risk McGilchrist's two hemisphere model also helps to understand how we contend with threats Two Management Capabilities The left and right brain model also sheds light on two management capabilities McGilchrist's model of the divided brain offers a compelling lens through which to view these management

Uncertainty with the model of the organization Each organization will have some idea or model for how The sophistication of the model is not always what is important. Improved models are needed to effectively buy-down reducible risk by reducing likelihoods and the consequence

Following the laws of cybernetics, to be a good regulator they must be a model of the system they are In this field, "freezing" a model is a critical strategy to ensure consistent performance and safety. Our governance models must innovate beyond traditional, static approaches and embrace the inherent complexity