How to effectively learn AI Prompting, with the 'AI for Chief Strategy Officers (CCOs) (Prompt Course)'?

Start here: Build an AI-enabled strategy office that moves faster and makes better bets

This course equips Chief Strategy Officers and strategy leaders with a clear, practical way to embed AI into the daily work of research, growth, and stakeholder engagement. It brings three high-impact areas together-market research, lead generation, and event planning-so your strategy team can source better insights, create stronger pipelines, and run executive-grade events that convert interest into measurable outcomes.

Rather than treating AI as a standalone tool, the course shows how to make it part of your operating rhythm: how your team scopes initiatives, gathers inputs, drafts outputs, reviews results, and updates plans. You will learn how to structure prompts for consistent quality, link outputs across topics, and create repeatable workflows that save time without sacrificing accuracy or strategic judgment.

What you will learn

• Strategic use of AI: How to position AI as a force multiplier for the strategy office-speeding research cycles, improving decision-quality inputs, and helping teams communicate with clarity and speed.
• Prompting fundamentals for executives: How to set context, define roles and boundaries, specify outputs, and create feedback loops so AI delivers consistent, board-ready work products.
• Structured workflows: End-to-end approaches that tie research, pipeline growth, and event planning together-so insights lead to action, action generates data, and data improves the next round of strategy.
• Quality control: Methods for checking accuracy, spotting gaps, validating assumptions, and aligning outputs with brand voice and leadership expectations.
• Governance and risk: Practical guardrails for data privacy, legal and compliance considerations, responsible use, and change management across cross-functional teams.
• Measurement and ROI: How to define useful metrics for research throughput, pipeline health, and event impact-and how to attribute results to your AI-enabled workflows.

How the three tracks work together

Each track focuses on a core responsibility of a strategy office and is designed to feed the others:

• Market Research sets the foundation with landscape scans, competitor and partner analyses, trend synthesis, and implications for portfolio choices. Outputs here inform priorities for events and outreach.
• Lead Generation converts research into targeted engagement, messaging, and prospecting plans. Feedback from lead gen-responses, objections, conversion patterns-returns to the research track to refine segmentation and positioning.
• Event Planning aligns stakeholders around key bets, showcases partnerships, and creates moments that accelerate deals. Event artifacts and attendee insights loop back into lead gen and research to sharpen next steps.

By linking these tracks, the course helps you run a closed-loop system: insights guide action, action produces data, and data matures your strategy.

Using prompts effectively as a CSO

The course walks through a practical prompting method that fits executive workflows without adding noise:

• Frame the objective and constraints: State the business goal, audience, success criteria, and any must-include or must-avoid elements.
• Provide relevant context: Share the minimum data the model needs-definitions, segments, product lines, geographic scope, or policy constraints.
• Specify structure: Ask for structured outputs (headings, bullet points, tables when appropriate) that your team can edit or present quickly.
• Iterate with critique cycles: Use short, focused review prompts to check assumptions, flag risks, and improve clarity without redoing the entire task.
• Ground with sources: Where appropriate, request citations, links, or reference points to support claims and enable verification by analysts.
• Operationalize the output: Convert final drafts into action items: research briefs, outreach plans, event run-of-show, dashboards, or executive summaries.

The method is simple, repeatable, and suited to teams with varying levels of AI experience. It also supports auditability, so leaders can see how a given output was created and improved.

Why this matters for strategy leaders

• Speed with accountability: Shorten time from question to insight while keeping controls in place for quality and compliance.
• Consistency across teams: Standardized prompting and workflows help different functions produce compatible outputs that fit together.
• Better use of scarce time: Free up senior leaders to focus on judgment calls-portfolio allocation, partnerships, and sequencing-while AI handles first drafts, summaries, and scenario outlines.
• Stronger alignment: Research, pipeline activity, and events reference the same strategy narrative and metrics, reducing rework and confusion.

Inside the course

The course is structured so you can either follow it end-to-end or jump directly to the track you need now. It includes:

• Clear learning paths for market research, lead generation, and event planning, each with step-by-step guidance and checkpoints.
• Prompts and workflows for common CSO deliverables, with instructions on how to adapt them to your sector, region, and go-to-market model.
• Leadership-ready templates for summaries, action plans, and metrics-so outputs look and read like executive work product.
• QA and risk checklists to reduce oversight gaps and strengthen reliability.

Practical outcomes you can expect

• Faster research cycles and more reliable synthesis that supports key decisions and portfolio choices.
• Clearer, more targeted outreach plans that align with ICPs, vertical plays, and partner motions.
• Events that create momentum for strategic initiatives, partnerships, account expansion, and pipeline acceleration.
• Closed-loop metrics that connect research insights to pipeline movement and event results.

Governance, ethics, and risk management

Responsible use is a core theme. The course details how to set guardrails that protect your organization and brand while enabling speed:

• Data hygiene: What to share and what to keep offline; redaction, abstraction, and secure workflows.
• Legal and compliance: Sector-specific considerations, approval processes, and documentation practices.
• Bias and fairness: Methods to spot skewed outputs and correction techniques to keep work grounded and equitable.
• Human oversight: Clear review points and sign-off steps so final decisions remain with accountable leaders.

Measurement and ROI

AI initiatives gain credibility when results are observable. You will learn how to structure meaningful metrics, such as:

• Research throughput, cycle time reduction, and coverage breadth.
• Lead quality, conversion rates across stages, and cost per qualified opportunity.
• Event impact, including attendee engagement, sourcing influence, and follow-up conversion.
• Qualitative indicators: stakeholder satisfaction, board feedback, and clarity of strategic narratives.

The course shows how to define baselines, set targets, and link improvements to specific AI-enabled workflows.

Change management and adoption

Lasting value comes from consistent use. You will learn how to:

• Pick the right pilot areas and expand without disrupting critical work.
• Set roles and responsibilities for executives, managers, and analysts.
• Run lightweight enablement so teams know when and how to apply prompts and when to escalate to human experts.
• Keep a library of approved prompts and templates with version control and feedback channels.

Who should take this course

• Chief Strategy Officers and heads of strategy seeking a practical, executive-level method for AI adoption.
• Leaders across corporate development, market intelligence, growth, partnerships, and PMM who work closely with the strategy office.
• Analysts and program managers who convert leadership priorities into research, pipeline, and events.

How the learning flows from start to value

• Foundation: Core principles for effective prompting, governance, and measurement.
• Application: Track-based lessons for market research, lead generation, and event planning.
• Integration: Guidance to connect outputs across tracks, create feedback loops, and publish executive dashboards.
• Scale: A practical rollout plan, with communication templates and enablement tips for teams and partners.

Why this course stands out

• Executive-grade outputs: Everything is built to the standard of board packs, investor updates, and cross-functional briefings.
• Action-first approach: Prompts and workflows translate directly into work products that support decisions and revenue outcomes.
• Cohesive system: Research informs outreach, outreach informs events, and the cycle improves with each pass.
• Reality-tested guardrails: Built-in practices for accuracy, compliance, and brand alignment.

Frequently asked questions

• Is this technical? No coding is required. The focus is on executive workflows, communication, and decision support.
• Will it fit our sector? The methods are sector-agnostic and adaptable. You'll learn how to adjust the prompts and workflows for your market.
• What about accuracy? The course includes quality checks, sourcing tactics, and review steps to reduce risk and improve reliability.
• How long to see impact? Many teams see time savings and clearer outputs within weeks, with measurable ROI as workflows become routine.

Your next step

If you lead strategy and want a practical way to bring AI into research, pipeline growth, and events-without adding complexity-this course gives you the structure, prompts, and guardrails to make it work. Start with the foundation section, choose the track that matches your immediate priority, and then link the tracks to run a continuous, data-informed strategy cycle.

Ready to build an AI-enabled strategy office? Get started and put these workflows to work across your next planning cycle.