You’re thinking about adding AI and automation in your inventory operations, but you’re not quite sure where to start, or what to expect.

You might be scaling quickly, or your reporting and inventory workflows are already showing strain. Maybe you’re realizing your team spends too much time wrangling data, fixing errors, or chasing suppliers for updates.

You don’t need a full engineering team to start making progress, but you do need a thoughtful roadmap. 

In this playbook, we’ll walk you through how the fast-growing CPG teams we work with are adopting automation, AI, and integrations today, and how you can do the same.

How Inventory Ops Teams Are Adopting AI + Automation

1. Data Integrations That Actually Work

We’ll start with the boring stuff, which is actually the most important.

Integrations save labor hours, just like AI does. Choosing vendors with open APIs or pre-built connectors is one of the fastest ways to future-proof your operations. When you eventually want to adopt AI agents, the quality of their output relies heavily on the quality of your underlying data.

Look for API access when you’re considering EDI providers. Choose a 3PL with a robust WMS and clear integration support. Make sure that your IMS or MRP plays nicely with your accounting software and reporting stack. For example, Cin7 has a whole host of pre-built connectors, as well as a robust API that allows you to connect your data to any software you’d like.

Pro tip: Not all APIs are equally valuable. Think of an API as a restaurant menu. If the “menu” (API documentation) doesn’t include things like shipping status or invoice creation, you won’t be able to automate those flows, even if the vendor says they offer an API.

If a system doesn’t connect easily, someone on your team becomes the connector (the “human API” shuffling data from one system to another). That doesn’t scale.

2. Multi-Step Automations Are Easier With AI Assistance

Tools like Zapier and Make.com are now embedding AI helpers like ChatGPT directly into their platforms.

Previously, these platforms were powerful but intimidating for non-technical users. Now, you can literally describe what you want to automate in plain English, and get a workflow scaffolded for you. 

Fair warning: if you build automations yourself or hire an hourly freelancer to do so, you also need to budget time and money for software maintenance. We’ve seen too many brands spend time and money building automations, only to revert to manual processes when they inevitably break, and nobody is around or willing to fix it.

3. “Vibe Coding” With AI Is A Superpower

If you've ever written an SOP or built a spreadsheet model, you already know how to think like a systems designer. Prompting AI to build software (“vibe coding”) isn’t that different. You can now build your own internal tools, but describing what your process should do, and the AI helps write the logic or code behind it.

It’s especially useful for:

• Internal dashboards
• Google Apps Scripts, Excel macros, and other spreadsheet-based workflows
• One-off automations that don’t need systems integration
• Heavy-duty number crunching with Python (think freight / 3PL reporting)

4. CustomGPTs Unlock New Skills and Self-Serve Reporting

Add your team’s database schemas to a CustomGPT, and you never need to rely on another teammate for ad hoc reporting needs again. 

CustomGPTs can help anyone generate the right SQL query or reporting logic, even without technical skills. 

E.g. write SQL for a one-off velocity report; summarize sell-through by channel over the past quarter. 

This unblocks reporting work across functions, giving team members faster access to insights while reducing bottlenecks.

How to Lead Automation + AI Adoption In Your Company

So how do you actually get any of these initiative types going, especially when you don’t have dedicated software engineers?

Here's the exact framework we use with clients at Crafty Crow:

1. Scope the Pain First

Everyone’s excited about AI demos. But executives want tangible results, like hours saved, fewer errors, faster cycle times, or better forecasting.

Start by identifying high-friction workflows:

• Where does your team spend time copying and pasting?
• What reports are delayed or inconsistent?
• What’s causing last-minute inventory fire drills?

Tie automation opportunities to clear business impact.

2. Redesign the Process Before Automating It

Often, existing workflows are layered with outdated steps that no longer serve a purpose. Before you automate a bad process, simplify it:

• What is your actual source of truth for inventory and orders?
• Are you entering the same data in multiple places?
• Can system-to-system integrations replace manual input?

A clean process creates a simple automation, which minimizes maintenance headaches later. 

3. Start Small to Build Buy-In

Pick one pain point that’s shared across functions, or one that’s annoyed everyone for months.

A quick win could be:

• Auto-tagging wholesale orders in Shopify to trigger a Slack alert
• Building a CustomGPT to help non-technical team members write SQL for Looker Studio

Tinker, pilot, and share early wins. Adoption builds when people see their own work getting easier.

4. Document your SOPs, Including the Change History

Every automation should have a clear before-and-after:

• What did the manual process look like?
• What does the new process do?
• If the system fails, how do we fall back to a (simplified) manual process?

Bonus points if you also document why certain decisions were made – so that team members can make informed decisions when modifying processes in the future. This documentation helps future-proof your automations, and gives new team members clarity and confidence.

5. Set Expectations of an Iterative Journey

Automation and AI take time, and the goal is to have progress that you can build on to a bigger vision. Often, for teams that are dealing with manual ops work, a successful v1 feels more like “relief from pain.” While “relief from pain” is a small step, it gives the team breathing room and makes the final vision – working on higher-leverage items in a “dream outcome” – feel much more attainable.

• Set realistic milestones:
• What does a v1 look like? 
• What can you deliver in two weeks, two months, two quarters?

When teams know where they're going and what success looks like along the way, they're far more likely to stay bought in.

Parting Thoughts

Ops teams are often stretched thin, asked to support the business as it scales, without scaling themselves.

But they’re also uniquely positioned to lead automation and AI initiatives. Ops teams think in workflows and edge cases. You live with the inefficiencies. When you’re empowered with the right tools and support, you can eliminate busywork, improve accuracy, and unlock leverage not just within your team, but across the entire organization. One Operations leader we worked with needed an automated system to project-manage suppliers. She realized that what she built could easily be modified for the Marketing team to reach out to influencers, as well as for the Sales team to target new wholesale accounts.

Ready to Get Started?

At Crafty Crow, we help fast-growing CPG brands like yours identify, design, and maintain automations that free up your team and scale your operations.

Whether it’s automating PO flows, streamlining inventory reporting, or setting up a clean data warehouse layer on top of Cin7, we’ll help you get from “we should automate this” to “it’s already running.”

👉 Learn more or book a discovery call here.