Weber Shandwick’s North America CEO, Jim O’Leary, turned his office into an AI testbed in six months—building agents that summarize meetings, surface prioritized research, draft messages in his voice, and free up one to two hours a day. Here’s a clear playbook for leaders who want practical, secure AI that actually helps them lead better.
The hook: AI isn’t just for engineers—leaders can prototype it too
CEOs love the idea of AI—surveys show nearly universal optimism—but adoption at the executive level lagged until leaders began treating their own offices as laboratories. Jim O’Leary’s approach is simple and replicable: pick a handful of repetitive but high-value tasks (meeting summaries, curated research, consistent messaging), build a private knowledge repository, and stitch small AI agents together with clear privacy and security guardrails.
What O’Leary built (the minimum viable CEO AI)
Rather than chasing bleeding-edge demos, O’Leary and a small cross-functional team focused on three core capabilities:
- Secure meeting summarization — automatic, private summaries that reduce time spent poring through notes.
- Active research and prioritization — a feed that collects news, studies, and competitive signals and ranks them by relevance.
- A CEO-style writing agent — a draft generator trained on memos, speeches and past emails to produce on-brand communications.
They also created a central repository of organizational knowledge—press releases, past presentations, and CEO memos—so AI outputs draw from trusted, contextual sources rather than generic web content.
How the team set it up—practical steps
- Assemble a tight squad: executive assistant, chief of staff, innovation lead, and a technologist—small, cross-functional, decisive.
- Define the job-to-be-done: be explicit—summarize meetings, surface timely research, or draft talking points.
- Build a private knowledge base: import internal memos, press kits, and past communications as the model’s primary context.
- Start small and iterate: prioritize high-value tasks, pilot internally, collect human reviews, and improve the prompts and connectors.
- Set security and privacy as non-negotiable: encryption, access controls, and governance were table stakes for the team.
Concrete benefits—what changed for the CEO
O’Leary reports steady, measurable wins:
- Time saved: roughly 1–2 hours per day reclaimed for strategic thinking and leadership development.
- Consistency at scale: writing agent drafts on-brand all-hands emails and external statements with minimal editing.
- Knowledge becomes portable: expertise is no longer trapped in the CEO’s inbox; it’s surfaced when teams need it.
- Culture shift: executive-level adoption nudged wider employee experimentation with AI tools and platforms.
Two original insights you can’t ignore
1. Executive experimentation accelerates organizational adoption. When a CEO models thoughtful, secure AI use, it lowers psychological barriers across the company. Leaders who “show versus tell” create permission for teams to experiment responsibly.
2. The highest ROI is not automation alone but composability. O’Leary’s system is valuable not because any single model is perfect, but because small agents (summarizers, curators, writing assistants) are composed around a trusted knowledge graph. That composition, and the human review loop, is where durable value appears.
Risks and guardrails—what leaders must address
O’Leary stresses privacy, confidentiality and governance. For executives building similar setups, don’t skip:
- Access controls and encryption for sensitive corpora.
- Human-in-the-loop approvals for any outward-facing communications.
- Clear audit trails and retention policies for generated content.
A short checklist for CEOs who want to start
- Identify one repetitive, high-value task you personally do every week.
- Form a 3–5 person pilot team (assistant, chief of staff, one technologist).
- Assemble a private knowledge repository (past memos, presentations, templates).
- Build or subscribe to a summarization and a writing agent, and run it behind your existing security stack.
- Measure time saved and iteratively expand to the next task.
Final takeaway
Scaling a CEO with AI isn’t about replacing judgment—it’s about amplifying it. Jim O’Leary’s experiment shows that leaders can prototype practical AI systems in months, reclaim time, and create a credible leadership example for the whole company. The critical ingredient is composition: small, secure agents plugged into trusted knowledge, matched with human oversight.
Question: If you were to reclaim an hour of your day with AI, what would you spend it on—strategy, mentoring, product time, or something else? Share your pick and why in the comments or with your leadership team.
