Organizational Responses and Adoption of Generative AI
Across industries — from banking and pharmaceuticals to government agencies and tech firms — many have restricted or even banned ChatGPT and similar AI tools due to governance concerns. Those who have adopted generative AI are implementing oversight frameworks to manage risk. Without governance, Gen AI can produce biased, inaccurate, or harmful outputs, exposing organizations to reputational damage, regulatory scrutiny, and legal liability.
To mitigate this, organizations are developing governance frameworks that address data usage, model training, security, compliance, and ethical standards. These frameworks help companies balance innovation with responsibility, enabling AI adoption that aligns with corporate values, safeguards sensitive data, and meets evolving regulatory expectations. The result is not just compliance, but sustained stakeholder trust.
Despite the hurdles, Northern Light has successfully deployed dozens of GenAI solutions, across IT, financial services, and life sciences, for some of the world’s largest enterprises. How did we do it?
Business Strategy and Research Enhancement with GenAI
Generative AI transforms business strategy research. It delivers fast, high-quality answers to complex questions about markets, competitors, and consumer behavior. A BCG study found that consultants using GenAI completed strategy tasks 25% faster and with 40% higher quality.
By aggregating insights across multiple documents, GenAI allows users to consume synthesized intelligence rather than sift through individual search results. A Microsoft study revealed that 75% of employees already use AI at work, with 78% bringing their own tools. This “Bring Your Own AI” trend poses a clear governance challenge — because these tools often fall completely outside the purview of corporate oversight.
GenAI System Architecture and Security Governance
Northern Light’s GenAI systems are built with security, transparency, and control at their core. Each solution integrates high-quality content via Retrieval-Augmented Generation (RAG) — ensuring outputs are grounded in approved document text, not LLM training data. We use enterprise-grade providers like OpenAI (SOC 2 certified), with encrypted APIs, zero data retention, and contractual safeguards that prohibit using client data for model training.
Governance frameworks reinforce this architecture, ensuring safety, reliability, and trustworthiness by design — not as an afterthought.
The NIST AI Risk Management Framework
Many enterprises adopt the NIST AI Risk Management Framework (RMF) — published January 26, 2023 — as their governance foundation. It outlines the essential traits of responsible AI systems:
- Validation: Ensure outputs are accurate, reliable, and generalizable across use cases.
- Security: Protect against adversarial attacks, data poisoning, and model exfiltration.
- Safety: Safeguard human life, health, property, and the environment under defined conditions.
- Resilience: Maintain performance during unexpected disruptions and degrade gracefully.
- Explainability & Interpretability: Help users understand how outputs are generated to build trust.
- Transparency & Accountability: Document how systems work, how decisions are made, and who is responsible.
Increasingly, corporate governance teams require that any AI system demonstrate conformance to these principles, often supported by architectural diagrams, technical documentation, and use-case examples.
Governance Processes and Industry Recognition
Today’s enterprise governance processes are extensive — involving questionnaires, documentation, risk assessments, and security reviews. While evolving, they are rapidly becoming standard practice across large organizations.
Northern Light helps clients navigate these requirements by providing the documentation, evidence, and support needed to satisfy governance committees. More fundamentally, we architect our systems from the outset with all the attributes required to earn approval.
Case in point: a top pharmaceutical company, managing over 400 AI projects, referred to Northern Light’s GenAI solution as the “Gold Standard” during a governance review. The committee chair stated that the RMF-based governance documentation we provided would serve as the benchmark for evaluating the other projects.
Ready to Explore GenAI for Your Organization?
Northern Light has the expertise, frameworks, and proven track record to help enterprises adopt generative AI safely and effectively.
Contact us today to learn how we can help your organization accelerate innovation while ensuring governance, compliance, and trust.
