Artificial intelligence is moving fast. New tools, platforms, and use cases seem to appear every week, and teams are eager to experiment. That excitement is a good thing, but without structure, it can quickly lead to inconsistency, risk, and missed opportunities.
That is where an AI Council comes in.
At Integrity, we formed an AI Council to bring structure, creativity, and accountability to how we explore and use AI. It helps us move beyond experimentation and toward intentional, responsible adoption that supports our clients, our team, and our long-term goals.
This post walks through what an AI Council is, what it does, and how you can build one that actually delivers value.
What Is an AI Council?
An AI Council is a cross-functional group that oversees and guides AI strategy, delivery, and risk management in line with company goals and values. The council’s purpose is to ensure that innovation is thoughtful, ethical, and useful.
At its core, an AI Council typically focuses on three key responsibilities:
- Creating pilots that drive measurable value by balancing impact and feasibility
- Setting guardrails around governance, ethics, compliance, and data usage
- Growing AI skills and literacy across teams, so adoption is shared across everyone in the organization
When done well, an AI Council turns AI from a collection of tools into a strategic capability.
Step 1: Build a Cross-Functional Team
The first step is assembling the right group of people. An effective AI Council includes voices from across the organization, such as design, development, marketing, operations, finance, and leadership.
Each department sees AI differently. Developers may focus on automation and efficiency. Marketers may look for help with content and buyer personas. Operations teams may see opportunities to streamline processes. Leadership brings perspective on risk, priorities, and alignment with business goals.
At Integrity, our AI Council includes members from every area of expertise. That gives us a complete picture of how AI can support both client work and internal operations. Just as important, it keeps the conversation collaborative. AI should feel empowering and accessible, not intimidating or controlled by a single team.
Step 2: Document What You Are Already Using
Before setting policies or exploring new tools, it is important to understand where you already are.
Many organizations are surprised by how much AI is already in use across their teams. Some tools are paid and approved. Others are free, experimental, or embedded in platforms employees already use.
Start by taking inventory of all AI tools currently in use. Create a centralized record that tracks the tool, who is using it, and how it is used. This helps identify redundancies, gaps, and potential risks.
At Integrity, we began by documenting every AI tool our teams used. That process alone revealed how quickly AI had become part of our daily workflow.
The next step, even if you have not done so yet, is to audit individual workflows. Look at how people do their jobs today and identify areas that could be enhanced by AI if they are not already. This often uncovers opportunities teams did not realize were possible.
Step 3: Identify How AI Is Already Being Used
Listing tools is only part of the picture. The real value lies in understanding how AI is used day-to-day.
Document specific use cases across departments and look for patterns. This helps you see where AI is delivering value and where it may introduce risk or inconsistency.
Common examples include:
- Marketing and Content: Brainstorming ideas, SEO keyword research, copy refinement, and image generation.
- Design and Development: Wireframes, code suggestions, and automation support.
- Operations: Meeting summaries and recordings, data organization, and workflow improvement.
- Strategy and Sales: Proposal support, objection responses, and trend analysis
Our teams use AI to brainstorm campaign ideas, refine copy, summarize meetings, and accelerate internal processes. Seeing these use cases together helps us identify best practices and areas where guardrails or training may be needed.
This step also highlights success stories that can be shared across the organization.
Step 4: Understand Your Team’s AI Comfort Levels
Not everyone approaches AI with the same level of confidence or experience. That is why understanding your team’s comfort levels is critical.
Surveys are a simple and effective way to gauge familiarity, interest, and skill levels. They can also reveal who is excited to learn more and who may feel unsure or hesitant.
Our all-employee survey provided valuable insights into who was experimenting confidently and who wanted more guidance. It also helped us identify internal champions to lead education and support others.
These insights make future training more effective and inclusive.
Step 5: Create Spaces for Shared Learning
AI learning should not be a one-time event. It works best when it is ongoing and collaborative.
Create spaces where employees can share ideas, tools, and lessons learned. Lunch and Learns, informal demos, and collaborative working sessions all help normalize AI as part of daily work.
We also created a dedicated Slack channel for AI discussions at Integrity. It has become a place to ask questions, share discoveries, and learn from each other in real time. These spaces build confidence and sustain momentum.
Step 6: Develop AI Policies and Best Practices
As adoption grows, clear guidelines become essential.
AI policies do not need to be overly complex, but they should address key areas such as:
- What data can and cannot be uploaded into AI tools
- When and how AI-assisted work should be disclosed
- Standards for verifying AI-generated output
- Rules for protecting client and proprietary information
At Integrity, we formalized policies that protect client data while encouraging smart, responsible use of AI. Clear expectations help teams move faster with confidence and reduce uncertainty.
Step 7: Identify Opportunities for Innovation
With governance in place, the AI Council can shift focus toward innovation.
Look for pilot projects that solve real business challenges. Prioritize ideas that save time, improve quality, or deliver measurable results. Examples might include automating repetitive tasks, enhancing customer experiences, or analyzing large data sets for insights.
Encourage departments to propose ideas through the AI Council. This keeps innovation grounded in real needs and spreads ownership across the organization.
Step 8: Keep the Conversation Going
AI will continue to evolve, and so should your approach.
Schedule regular check-ins to review tools, policies, and outcomes. Quarterly updates from each department work well for many teams. Consider creating a simple feedback loop that allows employees to share ideas or concerns at any time.
Most importantly, make continuous learning part of your culture. An AI Council is not a one-time initiative. It is an ongoing commitment.
Make AI a Team Sport
AI adoption works best when everyone has a voice and shared responsibility. When structured well, an AI Council helps teams innovate safely, efficiently, and creatively.
If you are ready to start your own AI Council or want help identifying the right tools, policies, and opportunities for your organization, Integrity can help guide the way.
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