Document Identifier: GOV-AI-001
Version: 20260701.01-MGT
Status: Approved by Management
Classification: Public / Customer-Facing
Document Owner: Instantiations AI Governance Board
Executive Sponsor: Instantiations Management Team
Review Frequency: Annual or Upon Material Change
Artificial Intelligence (AI) is transforming the way organizations create value, improve efficiency, and solve complex business challenges. As these technologies evolve, organizations must balance innovation with appropriate governance, transparency, accountability, and risk management.
At Instantiations, we view AI as both an opportunity and a responsibility. We believe AI can enhance productivity, support decision-making, and enable new forms of innovation when implemented thoughtfully and responsibly.
Our objective is to help customers benefit from AI while maintaining security, privacy, operational resilience, and trust. This document outlines the principles and commitments that guide Instantiations’ approach to the policies, procedures, and ethical standards that we use to oversee the development, deployment, and operation of Artificial Intelligence.
Responsible Evolution™ is the foundation of Instantiations’ approach to AI. We believe technology should advance in ways that strengthen organizations without introducing unnecessary disruption, uncertainty, or risk.
AI should augment human expertise rather than replace human accountability. We seek to balance innovation with continuity, enabling customers to realize the benefits of AI while preserving operational stability, institutional knowledge, and long‑term sustainability.
Our AI governance approach is informed by recognized frameworks and guidance, including ISO/IEC 42001 principles, the NIST AI Risk Management Framework, applicable legal and regulatory requirements, customer expectations, and internal governance practices.
Governance provides the structure through which innovation, accountability, transparency, and risk management can coexist. We consider the interests of customers, employees, partners, and regulators as we evaluate AI-related opportunities and risks.
Instantiations maintains an AI Governance Board that provides multidisciplinary oversight of AI-related activities. The Board reviews emerging technologies, governance practices, customer expectations, regulatory developments, and AI-related risks and opportunities.
This oversight helps ensure that AI-related decisions remain aligned with organizational objectives, customer commitments, and Responsible Evolution principles.
Human Accountability: Humans remain accountable for decisions and outcomes associated with AI-assisted activities, including autonomous and semi-autonomous activities.
Transparency: We seek to communicate appropriately regarding the role of AI in our services and operations.
Fairness: We seek to identify and manage risks associated with unintended bias and inequitable outcomes.
Security and Resilience: AI technologies should support reliable, secure, and resilient operations.
Privacy and Trust: Protecting customer information remains a fundamental priority.
Continuous Learning: Governance practices evolve as technologies, risks, and expectations change.
Instantiations maintains governance controls intended to support the responsible use of AI technologies. Governance activities are applied in a manner appropriate to the intended use, associated risks, customer requirements, and applicable obligations.
Governance considerations will be applied throughout the lifecycle of AI-enabled capabilities, including evaluation, adoption, deployment, operation, monitoring, enhancement, and retirement as applicable.
Data quality is an important factor in the effectiveness, reliability, and trustworthiness of AI-enabled processes. We seek to promote the use of data that is appropriate, relevant, and fit for purpose and consistent with the definition of Data Quality in the Definitions section.
Data quality considerations are incorporated into broader governance, risk management, and operational review activities where appropriate.
Instantiations believes AI should support and augment human expertise rather than replace human judgment. Appropriate human involvement will be maintained in review, validation, oversight, or decision-making processes, with the level of involvement determined by the use case and associated risks.
Individuals remain accountable for AI-assisted outcomes. This commitment reflects our belief that AI delivers the greatest value when combined with human experience, professional responsibility, and informed judgment.
Traceability: We support governance practices that help establish accountability and provide visibility into AI-related activities.
Explainability: We seek to ensure that AI-assisted outcomes can be reasonably understood and reviewed by appropriate stakeholders.
Observability: We support monitoring and oversight practices that help identify emerging risks, performance concerns, and operational issues.
Data privacy and data sovereignty are critical considerations in the use of AI technologies. We are committed to protecting customer information in accordance with contractual, legal, and regulatory obligations.
Customer data will not be used by Instantiations to train AI models except where explicitly authorized by the customer, such as in contractual language and commitments in End User License Agreements, Master Service Agreements, Statements of Work, and similar vehicles. We also evaluate jurisdictional, supply-chain, and third-party considerations as part of our governance approach.
AI tools that we may use internally in the course of conducting business and providing services with customer data in scope will be bound by agreements to protect the confidentiality of customer data. Examples of these tools may include business productivity, document analysis, AI-assisted software development, etc.
Lastly, as a software-centric entity, Instantiations understands the sanctity of Intellectual Property as a special class of data confidentiality and sovereignty, and as such we will strive to honor Intellectual Property commitments as a special case of responsible use of AI.
The AI Governance Board is committed to reviewing this position on at least an annual basis. The Board periodically evaluates AI-related risks, governance practices, operational experiences, emerging threats, customer expectations, and regulatory developments.
Instantiations seeks to maintain an AI governance approach that remains effective, responsible, transparent, and aligned with evolving customer, regulatory, technological, and business needs.
Artificial Intelligence (AI): Technology that performs tasks commonly associated with human intelligence, using machine learning, deep learning, natural language processing, neural networks, and other related technologies, including those associated with Generative AI.
Data Model: A structured representation of information.
Inference: Generation of outputs, predictions, or recommendations from a model.
Prompting: Providing instructions or context to influence AI output.
Training: Learning patterns from data.
Fine‑Tuning: Adapting an existing model for a specific purpose.
Data Sovereignty: The acknowledgment that data may have distinct attribution to and ownership by an entity, which may solely direct the handling of said data.
Data Quality: Accuracy, completeness, consistency, relevance, and reliability of data. Data Quality carries an implication that the data has undergone review to eliminate quality issues such as bias, repetition, poisoning, and other attributes which may negatively influence a resulting Data Model.
Data Masking: Obscuring sensitive information.
Agentic AI: AI capable of acting with varying degrees of autonomy.
Traceability: Ability to establish accountability and reconstruct activities.
Explainability: Ability to provide understandable information regarding outcomes.
Observability: Ability to monitor and understand behavior and performance, including phenomena such as Model Drift.
Model Drift: Also known as Model Decay. Model Drift happens when the real-world environment or incoming data changes, meaning the model's underlying assumptions no longer reflect reality.
Human‑in‑the‑Loop (HITL): Human involvement in oversight, review, validation, or decision-making.
Generative AI: A subset of artificial intelligence capable of creating new content, such as text, images, videos, audio, and code, based on patterns it learns from vast amounts of training data.
Instantiations promotes Accountability, Transparency, Human Oversight, Privacy and Data Stewardship, Security and Resilience, and Continuous Improvement as foundational principles for trustworthy AI governance. These principles guide our approach to AI adoption and help reinforce customer trust and confidence.
Developed with consideration of recognized AI governance frameworks including ISO42001, the NIST AI Risk Management Framework, regulatory guidance such as the EU AI Act, customer governance expectations, Instantiations’ own Responsible Evolution™, and Instantiations’ own internal governance, security, privacy, risk management, vendor management policies and practices.
This document was last reviewed by the Instantiations AI Governance Board on 18 June, 2026 and approved by Instantiations Management on 1 July, 2026.
20260616.01 – Initial governance baseline.
20260616.02-BRD – Governance enhancements.
20260616.03-BRD – Expanded governance narrative, restored definitions, Trustworthy AI Principles, strengthened oversight and continual improvement language.
20260618.01-BRD – Reviewed by Instantiations AI Governance Board
20260618.02-BRD – Board Recommendations incorporated
20260701.01-MGT – Reviewed and approved by Instantiations Management
