A 90 Day Plan for an AI Mandate With No Plan

Receiving an AI mandate without a clear plan can feel overwhelming. Many sales leaders are tasked with “doing AI” but lack a defined strategy or understanding of where to begin. The key is to break down the challenge into manageable phases, focusing on assessment, prioritization, and controlled experimentation.

Your first 90 days should establish a foundation for strategic AI adoption. This involves understanding your current state, identifying specific problems AI can solve, and launching a small, measurable pilot. This structured approach prevents wasted resources and builds internal confidence.

Day 1-30: Assess and Define Your Starting Point

The initial month is dedicated to understanding your current sales operation and identifying potential AI intervention points. This is not about choosing tools, but about understanding problems.

1. Current State Analysis

Start by mapping out your existing sales processes end-to-end. Document every step from lead generation to deal closure and post-sale activities. Identify bottlenecks, manual tasks, and areas where data is inconsistent or incomplete.

Many AI initiatives fail because they try to solve an undefined problem, or a problem that doesn’t exist.

Review your current tech stack. Understand what tools are used, how they integrate, and what data they generate. This helps identify data silos and integration challenges that AI might exacerbate or help solve.

2. Data Health Check

AI relies heavily on clean, structured data. Conduct a thorough audit of your CRM data. Look for inconsistencies, missing fields, duplicate records, and outdated information. This is a critical prerequisite for any successful AI deployment. Without good data, AI will produce unreliable outputs. For more on this, see CRM data hygiene: the prerequisite nobody wants to do before AI.

CRM Data Hygiene Checklist

3. Identify High-Impact Use Cases

Based on your process mapping and data audit, pinpoint specific areas where AI could provide immediate, measurable value. Focus on pain points that:

• Are repetitive and time-consuming for your team.
• Involve large volumes of data.
• Have clear, quantifiable outcomes.
• Are currently inefficient or prone to human error.

Examples include lead scoring, email personalization, or call transcript analysis. Avoid trying to automate entire complex processes at this stage.

Day 31-60: Prioritize, Plan, and Select

With a clearer understanding of your needs, the second month focuses on refining your strategy and selecting the right approach for a pilot.

1. Prioritize Use Cases

Not all identified use cases are equal. Prioritize based on potential ROI, ease of implementation, and data availability. A simple matrix can help:

AI Use Case Prioritization Matrix

Aim for a “quick win” for your first pilot. This builds momentum and demonstrates value early.

2. Build a Pilot Plan

Define the scope, objectives, and success metrics for your chosen pilot. What specific problem will this AI solve? How will you measure its impact?

• Objective: Increase SDR meeting booking rate by X%.
• Scope: Apply AI to a specific segment of outbound leads.
• Metrics: Meeting booked rate, time saved per SDR, lead conversion rate.
• Timeline: 30-day pilot, followed by review.

Consider the resources required: budget, internal team members, and potential vendor support. This is where you might start exploring specific AI tools or platforms. For guidance on evaluating vendors, refer to The RFP checklist for evaluating AI sales vendors.

3. Vendor or Build Decision

For your pilot, decide whether to leverage an existing AI solution (buy) or develop something in-house (build). For a 90-day plan, “buy” is almost always the faster and more practical option. Building requires significant technical expertise and time.

If you choose to buy, focus on solutions that directly address your pilot’s specific problem. Avoid feature bloat. For more on this decision, see Build vs buy: when a Slack assistant beats an enterprise platform.

Day 61-90: Execute and Learn

The final month is about launching your pilot, monitoring its performance, and gathering feedback.

1. Pilot Implementation

Deploy the AI solution in your chosen, contained environment. This might involve integrating a new tool, training a small group of SDRs, or configuring an existing platform.

Provide clear instructions and support to the pilot team. Communicate the “why” behind the initiative and how it benefits them directly. This helps drive adoption.

2. Monitor and Measure

Track the defined success metrics rigorously. Collect both quantitative data (e.g., conversion rates, time savings) and qualitative feedback from the pilot users.

A pilot’s success isn’t just about hitting targets; it’s about learning what works and what doesn’t.

Regularly review progress against your objectives. Are you seeing the expected improvements? Are there unexpected challenges? Adjust as needed.

3. Review and Plan Next Steps

At the end of the 90 days, conduct a comprehensive review of the pilot.

• Did it achieve its objectives?
• What were the actual ROI and impact? (See How to calculate the real ROI of a sales AI tool before you buy it for help.)
• What did you learn about the technology, your data, and your team’s readiness?
• What are the next steps: scale, pivot, or stop?

This review forms the basis for your long-term AI roadmap for a sales team. Document your findings and present them to stakeholders. This structured approach ensures that future AI investments are data-driven and aligned with business goals.

Common Pitfalls to Avoid

Even with a plan, certain issues can derail your AI efforts.

• Ignoring Data Quality: As mentioned, poor data leads to poor AI performance. Invest in data hygiene upfront.
• Over-Automating Too Soon: Don’t try to automate entire complex workflows immediately. Start small and iterate.
• Lack of User Adoption: If your sales team doesn’t see the value or struggles with the tools, adoption will fail. Involve them early and provide training.
• Chasing Hype: Focus on solving real business problems, not just implementing the latest AI trend.
• Lack of Clear Metrics: Without defined success metrics, you won’t know if your AI initiatives are actually working.

By following this 90-day framework, a VP of Sales can transform an ambiguous AI mandate into a clear, actionable strategy. It provides a structured path to assess, prioritize, and execute initial AI pilots, setting the stage for more impactful AI adoption across the sales organization.