Finding the Hidden AI in Your Company
Artificial intelligence is already embedded in your business. It may not look like a robot or a chatbot, but it is quietly shaping decisions, communications, and risk exposure across departments. The impact of AI in your company may not be immediately visible, but it influences many levels. For many companies, AI did not arrive in a single announcement. It crept in through software upgrades, vendor tools, and promises of efficiency.
For GCs and legal leaders, this creates a leadership test. The first challenge is not regulation or ethics. It is awareness. Before you can govern AI, you have to find it within your company. Most organizations already have several active AI systems running in operations, HR, marketing, or sales. Each one carries regulatory, contractual, privacy, and reputational implications that legal must understand and control.
The good news is that identifying these systems is not a technical project. It is a curiosity exercise. You need focused questions, structured listening, and follow-up.
Uncovering AI in Your Company’s Vendor Agreements
Start with your contracts. Many of your vendors already use machine learning or generative AI to deliver services. A SaaS platform that predicts customer churn, a marketing automation tool that optimizes engagement, or an HR system that automatically ranks resumes are all examples of AI-driven systems. These are just some examples where AI may already be influencing your company.
The risk is not that they use AI. The risk is that they use your company’s data to train it. Review your vendor agreements for terms like “data analytics,” “optimization,” or “learning systems.” These are often signals of AI. Pay attention to data ownership, usage rights, and confidentiality clauses. Ask who owns the data and outputs created by the system, and what limits exist on how your data can be reused.
If these answers are vague or missing, you already have AI governance work to do. Begin drafting standardized definitions of “AI system,” “training data,” and “derived output.” Create a clause library for AI-related terms. Over time, this will become the backbone of your AI in your company governance playbook.
Uncovering AI in Your Company’s Human Resources Systems
Your HR function is likely one of the earliest adopters of AI. Resume screening tools, employee analytics platforms, and workforce planning software all use algorithms that learn from data. These systems evaluate candidates, predict attrition, or even recommend compensation changes. Every one of those predictions carries bias, fairness, and due process risks.
The legal team’s role is to ensure fairness is measurable, transparent, and defensible. Start by mapping all HR systems that make automated decisions. Ask how each tool was trained, what data it uses, and how accuracy or fairness is verified. If the vendor cannot answer these questions clearly, assume you carry the liability.
Work with HR to create fairness checks and to define how results are reviewed before action is taken. Recommend an annual bias audit and create an internal “AI in HR” policy that requires disclosure to employees about automated decision-making. Their understanding will support managing AI in your company, turning legal into a proactive ally, not a roadblock.
The Third Hidden Zone: Marketing and Customer Experience
AI has transformed marketing faster than any other corporate function. Recommendation engines, dynamic pricing, and automated content generation all rely on algorithms that adapt in real time. These systems influence customer perception, brand integrity, and compliance exposure.
The danger lies in invisible personalization. AI-driven campaigns can target based on inferred characteristics that overlap with protected categories or can generate product claims that stray from verified data. Legal must translate these risks into marketing terms: brand safety, regulatory exposure, and consumer trust.
Meet with marketing leaders to understand how data feeds into personalization systems. Review privacy policies, consent mechanisms, and disclaimers. Develop a marketing AI playbook that defines approval workflows, review standards, and accountability for automation errors. It should cover brand tone, accuracy, and data use boundaries, ensuring the careful management of AI in your company.
How to Conduct Your AI Discovery
Schedule short sessions with leaders of each key function—HR, Marketing, Sales, Operations, Finance, and IT. Ask the same three questions in each meeting. What systems in your area use predictive analytics or automated decision-making? Where does their data come from? Who validates their outputs before decisions are made?
Record their answers and compile a basic AI inventory. Classify systems by risk level based on data sensitivity and business impact. This becomes your living AI map.
Building the Habit of Discovery
Finding AI is not a one-time audit. It is a recurring practice of curiosity. Add an “AI impact” checkpoint to every policy review, vendor onboarding, and technology discussion. Encourage your team to ask how any new system makes decisions and what data it uses. Treat discovery as an ongoing operational rhythm.
Leading Through Awareness
Awareness is influence. The GC who can locate and articulate where AI operates earns credibility as a trusted advisor to the board and the business. The ability to see technology before it becomes risk is a hallmark of strong legal leadership.
If you aspire to become a GC, start practicing this awareness skill now. If you already lead a legal function, teach your team to look for AI patterns in everyday tools. Governance starts with visibility. The companies that manage AI well will not be those that ban it but those whose legal leaders saw it early, understood its impact, and guided its use toward trust and accountability in your company.
