Set the strategy

Ensure your plan is ready

You may already have a plan for putting AI to work in your organization. Turning that plan into action requires leadership alignment and an explicit decision about what moves forward.

A strong C-suite proposal can make that decision easier. It should include a focused recommendation, the evidence behind it, a clear view of expected costs and returns, and specific asks for leadership.

Before you build your proposal, you should have four key decisions in place:

• The outcome: One measurable business result
• The department: One team where impact and readiness overlap
• The workflows: Two or three workflows, each with a named owner
• The metrics: A baseline, 90-day target, owner, and review date for each

If any of those decisions are still open, take the time to resolve them before building your proposal.

Build your AI strategy in four decisions

Learn how to define your outcome, choose a department and workflows, and set the metrics.

What goes in the proposal

An effective proposal is short and specific. Focus it on six things:

• Where you are today: Show your starting point with relevant adoption and usage data, such as licenses deployed, active users, teams using Copilot regularly, and workflows that are already redesigned with AI. That last number can reveal where there’s still room to improve how work gets done.
• Why it matters now: Bring two or three pieces of evidence that establish the business need or opportunity.
• Where you’ll start: Name the workflows you selected, the department they support, and the metric each one is intended to improve.
• What you’ll achieve in 90 days: Include the baseline, target, and owner for each workflow.
• What it costs and returns: Show the expected investment and return, including what you’re not asking for.
• What you need from leadership: Be specific about the decisions you need and when you’ll return with results.

Don’t include anything in the proposal that doesn’t support one of these six points.

See it in practice: Zava is a retailer with 4,000 employees and 1,200 Copilot licenses. 61% of licensed employees were active in the last 30 days, 14 teams use Copilot weekly, and no workflows have been redesigned with AI. The company has already identified a clear business outcome: reduce the time it takes the enterprise sales team to produce a customer proposal from nine days to four. That outcome becomes the focus of the C-suite proposal.

Bring the right evidence

Support your recommendation with two kinds of evidence: internal data and external research.

Start with your own numbers. Use your organization’s adoption, usage, and business data to establish your starting point and the opportunity you’re addressing. Be prepared to explain where the numbers came from and how they were measured.

Add external evidence for context. Relevant research shows that the opportunity or challenge extends beyond your organization. For example, Work Trend Index research found that organizational factors like culture, manager support, and talent practices account for roughly two-thirds of AI’s reported impact, compared with about one-third for individual mindset and behavior.

Keep the evidence focused. Two or three external data points can strengthen your recommendation without turning the proposal into a research briefing.

See it in practice: Zava’s AI leader brings the company’s adoption and usage data, the Work Trend Index finding, and an observation from the sales director: reps spend more of the sales proposal cycle assembling documents than talking with customers.

Together, the evidence connects Zava’s AI opportunity to a specific business problem.

Ask for a decision

Don’t end your proposal with a summary. End by clearly stating what you need from leadership.

Be explicit about the decisions and support you need:

• Approve the pilot workflows. Name the workflows you’re proposing.
• Confirm ownership. Align with leadership on who will be accountable for each workflow.
• Clear the blockers. Identify any decisions you need around access, budget, data readiness, or competing priorities.
• Sponsor the work. Be specific about where and when you need leaders to communicate their support.

Before the meeting ends, agree on when you’ll return to review the results. A review date creates accountability and sets a clear timeline for measuring progress.

See it in practice: Zava asks leadership to approve three specific workflows in enterprise sales and confirm an owner for each. The team also needs a decision on data access that has been pending with IT and executive sponsorship at the December operations review. They agree to return in 90 days to review progress against the target.

What a strong recommendation sounds like

Close with a concise recommendation that brings the key pieces of your proposal together.

A strong recommendation should:

• Name the business outcome.
• State what you’re proposing and what you need from leadership.
• Summarize the expected cost and return.
• Clarify what you’re not asking for.

See it in practice: “We’re proposing a 90-day pilot of three enterprise sales workflows to reduce customer proposal cycle time from nine days to four. We’ll use licenses we already have, with enablement time as the primary cost. Based on the estimated seller hours saved, we expect the value of the pilot to offset the cost within a year. We’re asking for approval to move forward without adding headcount or a new platform.”