We’re Making AI Harder Than It Needs to Be

Hey Reader,

In executive meetings across the protein industry, AI conversations are usually heading in one of two unproductive directions:

• We ignore it because we don’t know where to start.
• We try to use it to solve something extremely complex like forecasting or scheduling.

The first response creates paralysis. The second creates chaos.

When leaders don’t have a clear entry point, AI feels overwhelming, abstract, and risky so it gets pushed to "next year." On the other end of the spectrum, when organizations jump straight into applying AI to deeply interconnected, business-critical systems, they introduce risk into processes that keep the operation running.

Forecasting and scheduling are not beginner-level AI projects. They are layered with historical workarounds, cross-functional dependencies, and operational nuance. Starting there almost guarantees failure.

If you want traction, start somewhere smaller and more practical.

The Better Entry Point: Repetitive Task Automation

Instead of asking how AI can transform your business, ask:

Where are we wasting highly capable people on repetitive, low-value tasks?

In most protein operations, those tasks are everywhere:

• Weekly labor reports that require manual manipulation
• Data exports that must be reformatted before distribution
• Sales decks rebuilt from scratch for every top-to-top meeting
• KPI summaries that take hours to assemble

These aren’t strategic activities. They’re time drains.

And they are perfect for AI.

A Lesson from the Case Ready Floor

Early in my career at IBP, I was a Sr. Industrial Engineer in the Case Ready group in Council Bluffs. Each week, I produced a labor report in Excel that took 2–2.5 hours of copying, pasting, and restructuring across multiple sheets.

That wasn’t engineering. It was clerical work.

So I built a series of macros to automate it.

The report went from over two hours to less than ten minutes.

That gave me two extra hours every week to:

• Spend time on the production floor
• Identify yield improvements
• Balance labor more effectively
• Drive real cost savings

We didn’t need a new system.
We needed wasted motion eliminated.

AI today is no different than Excel macros were then.

Sales Teams Are a Prime Example

Consider your commercial organization.

How many hours are spent building customer decks?

With modern AI presentation tools, a salesperson can:

• Input customer objectives
• Upload historical performance
• Generate a structured, professional deck in minutes

Instead of spending three hours formatting slides, they can generate multiple versions in under an hour, make light edits, and redirect time toward:

• Store visits
• Deeper customer analysis
• Additional sales calls
• Competitive research

That’s not headcount reduction.
That’s time multiplication.

Why Large-Scale AI Efforts Stall

When leaders attempt to apply AI to forecasting or scheduling first, they run into:

• Interconnected legacy systems
• Political ownership issues
• Edge-case complexity
• Fear of job replacement

The organization becomes defensive instead of curious.

But when you automate a repetitive report and give someone two hours back each week, adoption becomes self-reinforcing.

Small wins build cultural momentum.

A Practical Framework for This Quarter

If you want movement without disruption:

1. Have each department identify three tasks that consume 1+ hour per week and involve repetitive formatting or manipulation.
2. Pilot AI tools on just one task.
3. Measure time saved.
4. Intentionally redeploy that time into floor presence, analysis, or customer engagement.

Do not let the saved time disappear into more email.

Reallocate it to value creation.

The Executive Shift Required

AI in protein should not be viewed as:

• A wholesale department replacement
• A core systems overhaul
• A multi-million-dollar transformation program

It should be viewed as a disciplined way to eliminate wasted motion.

Your plant managers are not valuable because they build spreadsheets.
Your sales leaders are not valuable because they format slides.

They are valuable because they:

• See inefficiencies others miss
• Make judgment calls
• Build customer trust
• Solve problems in real time

Automation should handle the repetitive tasks.
Your people should handle the thinking.

That’s where the real return begins.

What I'm Actually Using

If you’re curious how I’m personally using AI tools across operations, reporting, content creation, and commercial prep, I’m happy to share what’s working and what’s not. Not hype or theory, just practical applications that are saving time inside our business. If you want to compare notes or see specific examples, reach out and let’s start the conversation.

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​Judson Armentrout​
FreshOps | Practical Insights for Fresh Food Operations

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P.S. IFFA Recap is available!

This year’s IFFA show in Frankfurt was packed with future-shaping insights from automation designed to address labor gaps to packaging trends that haven’t even reached the U.S. market yet.

I put together a focused recap specifically for protein producers and retailers. It’s designed to help you anticipate what’s coming and begin realigning your strategy now, before the next wave hits.

Three ways to access it:

• Single Chapter – $245
• Full Report – $995
• Full Report + Consultation – $1,495

Learn more and purchase here: https://buildingblock.solutions/iffa-recap-report​

P.P.S. Want to know 5 Cost Saving Upgrades from IFFA?

Not sure if the Recap report is for you? This FREE 2 page guide shares some of our insights that could provide immediate value to your operation.
​Get the free pdf guide here​
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