The Chief of Staff role has always been about navigating ambiguity and driving clarity. Now, as AI moves from experiment to business imperative, Chiefs of Staff are emerging as the critical force behind this organizational transformation.
According to our Chief of AI Report, 84% of companies are already piloting or deploying AI tools. But effective adoption isn’t about picking the right software, it’s about rethinking how work gets done, how decisions are made, and how teams align around change. That kind of shift requires leadership from the center.
Enter the AI Triad: the CEO, who sets the vision; the CTO, who owns the tech infrastructure; and the Chief of Staff, who bridges strategy, execution, and people. Together, this group is responsible for embedding AI into the operating system of the company.
If you’re driving AI adoption in your org, you can’t just oversee it from a distance. You need to be deep in the weeds, testing tools, refining workflows, and understanding exactly how AI integrates into real use cases.
Here’s what that means in practice:
1. AI Literacy: Knowing What’s Possible
You don’t need to code, but you do need to stay up to date on what AI can and can’t do. That means testing tools like ChatGPT, Claude, Perplexity, and Retrieval-Augmented Generation (RAG) systems (e.g. You.com, Knode AI, etc.). Chiefs of Staff are already using AI for things like:
- CEO prep: Summarizing leadership team updates into digestible, actionable insights.
- Determining Annual Goals: Based on company’s mission, latest board decks, annual plan document, and any other relevant updates.
- Competitive intelligence: Automating tracking of industry trends and surfacing key insights.
- Decision support: Analyzing internal data to spot bottlenecks and inefficiencies before they escalate.
As one Chief of Staff in our AI Report shared, “For CoS/Operators, ChatGPT is incredibly useful for data analysis. You can give it a raw data set & it will crank out great visualizations with the right prompts. It's really like having a junior BA in your back pocket.”
Starting to make AI work for your day-to-day responsibilities will give you the confidence to get the rest of your team engaged.
2. Change Management: Selling AI Internally
AI adoption isn’t just a technical implementation, it’s a cultural shift. And for many teams, it may trigger real fear: fear of redundancy, fear of incompetence, fear of change itself. Our Chief of AI Report showed that 38% of participants cite change resistance and 41% cite security/ethical concerns.
One Chief of Staff we interviewed shared how a senior team member quietly admitted, “I’m afraid I won’t be valuable if I don’t get this AI stuff.” When you're rolling out AI, you're not just introducing new tools, you’re confronting people with existential questions about their careers.
Your job isn’t to force AI into the org. It’s to create conditions where adoption feels natural, empowering, and even exciting.
Here’s a framework you can use for your rollout:
Phase 1: Groundwork
- ✅ Acknowledge concerns: Normalize uncertainty, especially about job security.
Pro Tip: Framing Matters - You’re not replacing people, you’re valuing their time by removing busywork. Phrase it as “freeing up time for higher-leverage thinking” or “giving you more hours in the week.”
- 🧠 Educate softly: Short demos > long docs. Host intro sessions with real examples.
Pro tip: Don’t launch with a slide deck. Launch with a demo. Showing Claude auto-generate OKRs based on last quarter’s goals or using a pre-trained ChatGPT project to write a board memo makes it real. That 30-second wow moment is often what turns skeptics into believers.
Phase 2: Show Quick Wins
- 🛠️Start with your Principal. Find a quick win that solves a pain point for them.
Pro Tip: Consider fostering collaboration within your AI Triad. Successful rollouts require coordination across a CEO, CoS, and CTO. As a CoS you are uniquely suited to play the role of bridge-builder between strategic vision and operational adoption.
- 🚀 Choose low-stakes pilots: Things like project summaries, research reports, meeting prep are all internal. Start with workstreams that won’t disrupt customer acquisition, retention, or revenue.
Pro Tip: Use pre-trained projects by uploading strategic docs into ChatGPT/Claude for better outputs.
Phase 3: Internal Influence
- 💬 Frame benefits by role:
- Operators → Efficiency
- Strategists → Insight
- Marketing → Time back
Pro Tip: Experiment with AI in internal workflows first. Don’t start with customer comms or investor reports. Let people learn in low-stakes environments and share what works.
- 🎯 Create advocates: Spotlight early adopters in team meetings or Slack
Pro Tip: Reflect back successes to the wider team. Report on time saved, insights uncovered and innovative use cases employed by your colleagues.
Phase 4: Scale Responsibly
- 🔁 Create AI playbooks: What to use, when, and how
Pro Tip: Meet each team where they are—use function-specific metrics, workflows, and tools to frame AI as solving their own problems, not the company’s at large. - 📣 Host peer demos: Encourage teams to share wins and fails
Pro Tip: Schedule 15-minute “show & tell” slots during existing team meetings. Highlight wins and lessons learned. People trust peer stories more than polished rollouts - 🔐 Align with legal & ops: Standardize tools, handle privacy concerns
Pro Tip: Loop in Legal, Ops, and IT early with a standing monthly check-in. Frame it as a shared responsibility to unlock AI’s value safely and scalably.
3. AI-First Workflow Design: Rethinking How Work Gets Done
Using AI tools well requires rethinking processes from the ground up. Instead of layering AI onto existing workflows, ask: How would this function be built from scratch today if AI were a core team member?
- Start With Zero-Based Design: If you were building this process today from scratch, what steps could be owned by AI? What decisions still need a human touch?
- Automate the Low-Leverage Work: Things like meeting notes, status updates, basic data pulls, internal comms, research briefings can be fully handled by AI tools like Claude or ChatGPT Projects.
- Reframe Human Roles: As AI takes over more repetitive work, redefine what "value-add" looks like for each role. Are team members becoming better thinkers, collaborators, strategists?
One Chief of Staff shared how they used Claude to auto-generate meeting agendas and ChatGPT to summarize OKRs, saving 6–8 hours per week across the exec team. That time was reinvested in cross-functional strategy sessions, creating an AI-powered productivity loop.
Building the Org of the Future
Chiefs of Staff are uniquely positioned to drive AI adoption not just as a tool, but as a lever for how the business works.
In a world where most companies are already piloting or deploying AI, waiting is risky.
The most successful Chiefs of Staff won’t be the ones who implement a tool here or there. They’ll be the ones who redesign systems, win trust, and operationalize AI across the entire company.
You don’t need to be a technologist. You need to be a translator, a champion, and most of all, a builder.
Chief of AI Fellowship
AI is no longer a future trend, it’s reshaping the way businesses operate. As a Chief of Staff, BizOps leader, or senior operator, you have a unique opportunity to drive AI adoption and position yourself as a leader in this transformation.
That’s why we’re excited to introduce the Chief of AI Fellowship, a 6-week immersive program designed to equip high-level operators with the AI strategy, automation, and implementation skills needed to create next-gen organizations.
