The Hidden Cost in Every Inbox
Your finance team processes invoices from emails. Customer service copies data from customer emails into your CRM. Operations manually enters order information from supplier emails into your ERP system.
It feels like normal work. Everyone does it. But here's what the numbers actually say:
£28,500
Average annual cost per employee for manual data entry from emails
£2M
Annual cost for a team of 70 people handling email-based data entry
For a team of 70 people handling email-based data entry, that's nearly £2 million a year. Gone. Not into product development. Not into customer acquisition. Into copying text from one system to another.
The Real Problem Isn't the Time—It's What Happens Next
Here's what we see when we analyze email processing workflows:
30-50% of working hours
Consumed by manual data entry tasks
£220 per record
Average cost of manual errors
56% of employees
Experience burnout from repetitive data tasks
11-36 times per hour
Employees check email, destroying deep work
But the worst part? These aren't just productivity problems. They're retention problems. Your best people don't want to copy and paste. They want to solve real problems. So they leave.
Why Most Email Automation Projects Fail
"We tried to automate this before. It didn't work."
We hear this constantly. The share of companies abandoning AI projects jumped to 42% in 2025, from just 17% the year before. Why? Because most automation projects:
- •Take 6-12 months to deliver anything usable
- •Require massive upfront investment
- •Get stuck in IT backlogs
- •Can't handle the messy reality of real business emails
The problem isn't that email automation doesn't work. It's that most companies approach it as a technology project instead of a business process problem.
What Actually Works: The 30-Day Reality Check
Let's be specific about what's possible in 30 days—not in theory, but in practice:
Week 1: Analysis
We analyze one high-volume email process. Purchase orders, customer inquiries, invoice processing—whatever causes the most pain. We identify the exact fields that need extracting, the systems they need to flow into, and the edge cases that trip up simple automation.
Week 2-3: Build
We build and test a working AI system that:
- ✓Reads incoming emails
- ✓Extracts the data (even from PDFs, images, and poorly formatted text)
- ✓Validates the information
- ✓Routes it to your systems
- ✓Flags anything that needs human review
Week 4: Production
Your team uses it in production. You own the code. It handles exceptions gracefully. It gets better over time.
The ROI Is Ridiculous (When You Do It Right)
Companies using email automation save an average of 30% on operational costs. Automated processes achieve 90% higher accuracy compared to manual entry.
But the real value isn't the cost savings. It's what your people do with the time they get back.
One of our clients in operations went from having their team spend 40% of their week on email data entry to less than 5%. That's not 35% more email processing. That's 35% more time solving actual operational challenges, improving processes, building relationships with suppliers.
What This Looks Like in Practice
Purchase Order Processing
Before: 3 people spending 2 hours daily manually entering PO data from supplier emails into the ERP system.
After: AI reads the emails, extracts the data, validates it against existing records, and creates the PO automatically. Humans review only exceptions.
Time saved: 85%
Customer Service Intake
Before: Support team manually copying customer information and issue details from emails into the ticketing system.
After: System reads the email, categorizes the issue, extracts customer data, creates a properly tagged ticket, and assigns it to the right team.
Time saved: 60%
Invoice Processing
Before: Finance team downloading invoice PDFs from emails, manually entering data into accounting system.
After: AI extracts invoice data from attachments (even scanned PDFs), matches to purchase orders, flags discrepancies, routes for approval.
Time saved: 75%
The Honest Assessment
Not every email process is worth automating. Sometimes the volume is too low. Sometimes the variation is too high. Sometimes the ROI just isn't there.
We'll tell you if that's the case. We reject 60% of projects that come our way because they're not a good fit.
But if you have people manually copying data from emails into systems, and they do it more than a few times a week, the math probably makes sense.