Why Leaders Must Learn the Real Game of Prompting
By now, most leaders have at least experimented with ChatGPT. Some are dabbling in Claude. A few are exploring Gemini or Notion AI. And many have started deploying Microsoft Copilot across M365 to speed up document creation, meeting prep, or status updates.
But here’s the problem: the tool isn’t the strategy.
Most executives are still using these platforms with outdated, vague, or curiosity-driven prompts. The result? Generic outputs. Misaligned results. Wasted time. We don’t need more noise. We need AI outputs that move the business forward—safely, strategically, and securely.
The Real Shift:
From Prompting Curiosity to Prompting Leverage
We’ve entered a new phase. Generative AI is no longer a novelty or a tech demo. It’s a tactical capability for leadership, decision-making, operational design, and client engagement. But if your inputs aren’t structured around role, output, and risk, then your results are at best cosmetic—and at worst, noncompliant.
Prompting: Old vs. New
| Prompting Style | Old Prompt Example | Power Play Prompt Example |
| Role-Aware? | “Give me tips on productivity.” | “As an AI coach, build a 5-day sprint plan for output.” |
| Output-Driven? | “What’s a good sales strategy?” | “Create a coaching system I can run inside my CRM.” |
| Context-Rich? | “Summarize my meeting notes.” | “Design a decision dashboard based on KPIs and risk insights.” |
| Reusable? | One-off idea | Repeatable, client-ready, or automatable assets |
Old-school prompting creates homework. Power Play-style prompting creates leverage.
That’s the difference between playing with AI and using it to move your business forward. This is the new literacy for modern leadership.
Toolset Spotlight: Know the Strengths
While ChatGPT remains a strong generalist, understanding each platform’s real strength can help you operationalize AI across your org:
Microsoft Copilot
Best for: Seamless integration across Teams, Outlook, Word, Excel, and PowerPoint Unlocks value when paired with prompt systems like R.I.S.E.N. to generate executive summaries, classify email trends, or simulate business reviews with contextual awareness.
Claude (Anthropic)
Best for: Strategic reasoning, policy generation, long-form documentation with clear logic Use cases: Executive comms, vendor comparisons, security framework evaluation
Gemini (Google)
Best for: Embedded analysis across Google Workspace with AI-backed citations Use cases: Sheet-based forecasting, internal FAQ generation, data-backed presentations
Notion AI
Best for: Operational documentation, SOPs, and knowledge management Use cases: Onboarding guides, workflow design, meeting briefs with role-specific outputs
Secure Prompting Isn’t Optional Anymore
As AI tools become embedded across workflows, leaders must treat prompting like a security and compliance function—not just an efficiency tactic.
For example:
“As a security architect, classify this dataset using our internal data policy. Highlight what cannot be used in external LLM environments.”
When AI becomes part of your infrastructure, every prompt is a potential data disclosure. Treat it that way.
The Prompt Framework I Use: R.I.S.E.N.
Whether for my team, a client, or a boardroom presentation, every prompt I run follows this structure:
Role – Define the perspective "Act as a Chief of Staff…
Input – Provide source materials "Use CRM data, KPIs, meeting notes…”
Structure – Define the format "Create a 1-page summary, dashboard, or briefing…”
End-User – Identify the audience "For my sales leaders, client decision-makers, or IT team…”Next Action – State the goal“So I can delegate, take action, or present next steps…”
Without this? You’re just prompting in the dark.
Key Takeaway
- AI literacy is now a leadership skill, not just a tech curiosity.
- The quality of your output starts with the clarity of your prompt.
- Power Play-style prompting outperforms vague inputs every time by delivering structured, usable, and scalable results.
- AI tools like Claude, Gemini, and Notion offer deeper specialization, especially in operations, documentation, and compliance.
- Always stay security vigilant. Never enter sensitive, proprietary, or personal data into unsecured AI environments without clearly defined boundaries and acceptable use policies.
- Adopt a Zero Trust mindset for AI usage. Every prompt is a potential vector—validate the environment, verify the tool’s compliance status, and control access.
- Classify your data before you prompt. Treat AI tools like third-party vendors: if the data isn’t sanitized or tiered by sensitivity, don’t feed it.
- Develop internal AI usage guidelines. Leaders must codify what’s safe, what’s off-limits, and how to review outputs for risk and integrity.
- Leaders must build prompting systems that align with role, risk, and result. Otherwise, you’re just generating more noise.
You don’t need more information. You need better execution.