Insights
Practical Security Guardrails for Large Language Models
Actionable techniques to ensure secure LLM deployments that balance innovation with function, from using prompt injection protection to ethical use and access controls.
The Dimensions of Enterprise AI Governance: A Focus on Model Lifecycle Management
Explore how structured model lifecycle management turns governance principles into an operational reality, helping to guide AI development from design through retirement with control, transparency and trust.
The Human Element in AI Governance
Successful AI depends not just on tech, but on humans - particularly responsible development, deployment and use.
Unlocking AI's Potential: The C-Suite Blueprint for Responsible Innovation
A C‑level framework to adopting AI responsibly, balancing innovation with risk, oversight and scalability to achieve fast and ethically scale solutions.
Setting an Acceptable Use Policy for Generative AI in Your Business
Why and how enterprises need to build and maintain an Acceptable Use policy, which should create guardrails, rules and oversight for how generative models are used internally.
AI Agents and the Three Lines of Defence: A Banking Inspired Approach
This blog provides an AI governance framework for highly-regulated industries, using the banking industry as inspiration.
5 Essential Best Practices for LLM Governance: A Framework for Success
Key practices for organising, monitoring and securing large language model systems in enterprise settings.
Building a Pragmatic AI Governance Framework: Lessons from the Trenches
Discover practical steps to building effective AI governance, including balancing innovation with risk, compliance and accountability.
Generative AI - With Great Power, Comes Even Greater Responsibility
Explore the essential steps for governing generative AI in this blog by Ben Saunders. As generative AI becomes a powerful tool for innovation, it's crucial to establish robust guardrails and controls to prevent unintended consequences. Learn about the potential risks of unrestricted AI use, including ethical and legal implications, and discover how to implement technical controls and governance frameworks to ensure responsible AI deployment. Stay ahead in the digital age by adopting effective governance strategies that balance innovation with accountability.
Navigating the Risk Landscape of AI Systems: A Short Guide
Navigating the Risk Landscape of AI Systems: A Short Guide provides crucial insights into the complexities of managing AI-related risks. As AI technologies become increasingly integrated into various sectors, understanding potential threats such as data privacy concerns, algorithmic biases, and security vulnerabilities is essential. This guide offers practical strategies for identifying, assessing, and mitigating these risks to ensure safe and ethical AI implementation. Whether you're a business leader, IT professional, or AI enthusiast, this short guide equips you with the knowledge to navigate the evolving AI risk landscape effectively.
Navigating AI Risks with Key Risk Objectives and Indicators
The evolving AI risks landscape is rapidly changing, presenting new challenges and opportunities for businesses and individuals. This blog explores the latest AI threats, including deepfakes, data privacy breaches, and algorithmic biases. Learn how to mitigate these risks with strategic planning, robust cybersecurity measures, and ethical AI practices to stay ahead in this dynamic environment. Stay informed to safeguard your future in the AI-driven world.