Framework: Use AI for Structured Updates
An emerging best practice for managers is using AI to structure updates, escalations, and promotion cases. By applying structured frameworks, managers can create more effective and consistent executive communications. The argument is that leaders who leverage AI for this purpose will significantly outperform their peers.
One foundational method is the Pyramid Principle, developed at McKinsey by Barbara Minto, which inverts traditional storytelling by starting with the answer first. This top-down approach is tailored for executive audiences, immediately delivering the main recommendation before layering in supporting, mutually exclusive arguments. For technical leaders, this means leading with business impact—revenue, timelines, and risks—rather than implementation details. A similar, narrative-driven approach is Amazon's "6-pager," a document that replaces PowerPoint presentations in meetings. Meetings begin with a silent reading period of the six-page memo, ensuring all stakeholders are fully briefed before discussion. This format forces authors to articulate complex ideas with quantifiable data, such as "reduce P99 latency by 200ms" instead of a vague "improve performance." Frameworks like PREP (Point, Reason, Example, Point) offer a simple structure for persuasive communication in any context, from technical proposals to leadership conversations. Another direct approach is BLUF (Bottom Line Up Front), considered a critical framework for senior leader communication, which starts with the main point or request before adding necessary context. To structure the AI's role in generating these communications, prompt engineering frameworks like RISEN (Role, Input, Steps, Expectations, Narrowing) and ROADS (Role, Objective, Audience, Deliverables, Style) provide a clear blueprint. These models turn high-level ideas into actionable instructions for AI, ensuring the generated output is focused and aligned with the desired perspective, be it a strategist or a data analyst. The adoption of AI for such tasks is becoming a factor in career progression. A report from Cisco found that employees recommended for promotion used AI 50% more often than their peers. Similarly, companies like Meta are beginning to tie performance reviews to an employee's "AI-driven impact," while a VP at Amazon's home security division has made describing AI utilization a requirement for all promotion applications. While AI can mitigate human biases in promotion and performance decisions by analyzing broad datasets, it also introduces the risk of perpetuating historical biases present in the training data. A Resume Builder report showed that while 77% of managers use AI for promotion decisions, only about a third have received formal training on how to use these tools ethically.
