AI Governance is a comprehensive framework of policies, principles, and practices designed to oversee and manage the development, deployment, and use of AI systems to create an environment of trust.
We aim to ensure that AI is used in an ethical, transparent, and compliant manner, according to your business needs and use case.
AI governance is about building trust, based on transparency and ethical use - it’s not about the technology itself, but rather how we use it that determines its impact.
Developing an AI governance framework can seem daunting, so our approach is designed to identify the use case, applicable regulations and evaluate existing structures to establish a baseline understanding of gaps in governance.
From this, we iteratively build out a tailored governance strategy that aligns with your goals and regulatory requirements, while fostering stakeholder engagement.
To start with, we evaluate your existing AI systems and governance practices to identify gaps and areas for improvement. From this we step-by-step develop a tailored AI governance strategy that aligns with your goals, industry standards, and regulatory requirements.
It is critical to determine who the stakeholders should be, such as AI governance officers, privacy and security experts, a legal team and also system users, where applicable. Involving stakeholders early in the process is vital to create engagement and a sense of ownership and trust. Ask stakeholders to assess whether the use of AI is suitable for the intended use case, and to understand which requirements to prioritise - perhaps accuracy is more important than privacy. Create regular stakeholder meetings to continuously evaluate success towards the stated goal, as well identifying issues and verifying compliance.
Identifying and classifying potential risks, both internal and external, associated with your AI systems will include ethical, legal, and operational risks. With this knowledge, we will develop strategies to address and manage those risks, including creating contingency plans and response protocols. In parallel, we will establish who is ultimately responsible for risks and mitigations.
Next, we design and implement policies and procedures for managing AI systems, including ethical use, transparency, data protection, and risk management. All the while, taking into account the risk tolerance and organisational priorities.
Equipping internal teams with the knowledge and skills needed to maintain and evolve AI governance practices ensures continued stakeholder engagement and compliance, and provides scope for further internal training to expand the number of stakeholders.
Finally, we implement systems for continuous monitoring of AI systems to ensure ongoing compliance and performance. In parallel, we establish schedules for regular audits of the AI systems and governance practices to ensure adherence to policies and continuously identify areas for improvement.
By leveraging our team’s knowledge, organisations can better navigate the complexities of AI governance, ensuring that their AI systems are used responsibly and in alignment with their strategic objectives and regulatory obligations.
Promote equitable outcomes and prevent discriminatory practices in AI systems.
Enhance stakeholder confidence in AI technologies through transparency and accountability.
Identify and mitigate potential risks associated with AI systems to protect your users and organisation.
Meet legal and regulatory requirements to avoid legal issues and penalties.
Ensure that AI technologies are used in ways that align with ethical standards and societal values.
The Virtual Forge is a trusted, global software development company with a solid history of delivering comprehensive solutions for global brands, equipping diverse organisations with the finest technology available.
A team of creative and analytical minds leverages cutting-edge technologies and out-of-the-box thinking to deliver innovative software solutions. We’re always on the lookout for new technologies that can leverage our offer, helping our clients materialize their needs into new systems that streamline their business processes.
Quality is our core focus. Our team ensures high standards through rigorous quality assurance processes, thorough testing, code reviews, and continuous improvement.
Our track record is a testament to our reliability. Always by our client’s side, ensuring that nothing is left to chance. With our commitment to excellence, we pride ourselves on delivering dependable solutions that businesses can trust.
From setting ethical guidelines to ensuring accountability, our roadmap explores the process of defining and establishing the foundational pillars of governance that aim to balance innovation with safe, transparent and ethical use of AI.
The first stage in creating an AI governance framework involves identifying and engaging stakeholders who have an interest or concerns regarding the use of AI. Then we will conduct an analysis of existing AI policies and governance in order to assess the current and future usage of AI and potential risks.
In this phase, we will establish clear goals for the governance framework, identify organisational priorities and principles such as transparency, fairness, accountability, and then define a governance structure.
With the goals in mind, we can then review best practice, legal and regulatory requirements for this context and scope, and develop initial drafts of governance policies and guidelines.
Next, we will present the draft framework to stakeholders for feedback, and then conduct workshops to gather diverse feedback. Based on this input, we can then revise and refine the framework.
Once the feedback has been incorporated, the governance framework can be finalised and roll out can commence, coupled with training for employees on the new or revised policies and best practices. The final implementation stage is establishing monitoring and a review process to assess compliance and effectiveness of the framework.
With regular reviews of the framework, keeping tabs on regulatory changes and a process to gather feedback from stakeholders, we can ensure continuous improvement and refinement of the framework.
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