Summary
Planhat's AI features help you automate processes, surface insights, and work more efficiently across the customer lifecycle
A successful AI rollout requires a platform that connects your customer data with AI and a strategy that turns capabilities into outcomes
Our CRAWL–WALK–RUN framework helps you adopt AI in stages: from quick wins to measurable impact and embedded usage
Who is this article for?
Planhat Users who would like to start implementing AI
Series
Get started with AI (a strategy) ⬅️ You are here
Article contents
How to turn AI features into real business impact
AI in Planhat enables your team to scale their impact through automation and smarter workflows. With a range of AI features, e.g. intelligent automation and real-time insights from conversations, Planhat gives you a flexible platform to build meaningful AI-powered processes across your customer lifecycle.
But deploying AI successfully isn't just about having the right tools, it's also about having the right strategy - combining a platform that connects your customer data with AI and a strategy that turns capabilities into outcomes. We have developed a three-stage AI adoption framework to help you embed AI into your team's day-to-day work in a way that drives real, measurable outcomes.
Our AI enablement strategy is built around three stages of maturity: CRAWL, WALK and RUN. Each stage includes a note on data prerequisites. These are the minimum requirements needed to implement the strategy. As with any AI application, the more data you can include at each stage, the more accurate and valuable the AI analysis will be.
CRAWL: Get started quickly with single-click templates
The CRAWL stage is about getting quick wins with minimal setup by using out-of-the-box AI features already available in Planhat.
This includes:
Templated Automations: Use pre-built AI steps to help CSMs automate repetitive tasks, such as summarizing notes, drafting emails, or updating fields
Conversation Sentiment & Category Classification: Automatically classify incoming emails, chats, and call transcripts by tone (positive/neutral/negative) and type (Support, Billing, etc.) to unlock insights and trigger Automations
AI-Powered Health Scores: Incorporate sentiment trends and conversation metadata into your customer (Company) Health Scores
Data prerequisites:
Conversational data, e.g. emails, chats and call transcript
The goal is to save time for frontline teams and begin capturing new insights without needing to spend time and resources on development.
WALK: Expand AI across teams and use cases
Once your team is comfortable with core AI features, the WALK stage focuses on broadening usage and impact across the organization. We'll help you identify and implement AI use cases tailored to your business, such as:
Time-saving assistants for customer reps (e.g. auto-generated meeting notes, creating AI account (Company) summaries)
Early warning signals for at-risk accounts (Company) based on conversation trends or sentiment shifts
Generate weekly priorities based on meetings in the calendar
Data prerequisites:
Structured customer data (e.g. on Companies, End Users, Opportunities, Conversations, Revenue)
This stage often includes lightweight customization, more advanced AI Automations, and cross-team collaboration. The goal is to drive AI adoption and start aligning insights to strategic initiatives.
RUN: Operationalize AI with measurable business impact
The RUN stage is about making AI an integral part of your customer operations - starting with measurable AI outcomes to help you achieve your goals.
Here's an example of what that looks like in practice:
Use case: Automate meeting prep
Implement an AI-powered executive summary that's generated before each strategic customer meeting
Each summary saves ~10 minutes per reader. If 3 stakeholders read the summary, that's 30 minutes saved per meeting. Multiply that across your portfolio, and the value compounds
By tracking how often these summaries are created and used, you can quantify time saved, improve processes, and tie AI to real business outcomes.
Data prerequisites:
Structured customer data
Clear outcomes/KPIs
The goal is to embed AI in high-impact workflows, measure ROI, and continuously optimize.
Start by identifying the outcomes you want from AI - do you want to save time, improve operational efficiency or improve Net Revenue Retention (NRR)? Think of use cases where AI could help you reach your outcome, then use Planhat's AI features to implement the use cases.
🚀 Tip
Reach out to your Customer Success Manager or Technical Deployment Specialist at Planhat if you want support to get started with WALK or RUN.