AI is already helping 3PLs prevent millions of dollars in BPO errors

Outsourcing operational labor to BPOs isn't working out for many 3PL providers. According to Deloitte, 70% of companies have started bringing their outsourced work back in-house over the last five years to regain control over their operations. They may eliminate vendor markups, but even using internal shared services can cause problems.

When BPOs, or shared services, provide inaccurate or outdated carrier information, it creates a ripple effect throughout the supply chain. One study found that poor customer service causes 62% of failed 3PL partnerships, while another 10% fail due to unmet expectations and communication problems. These failures stem from mishandled shipping updates and incorrect information, which damage the relationship between 3PLs and shippers and cost 3PLs millions in revenue.

This isn't just a theoretical problem. One major freight marketplace provider working with Reindeer AI tried working with a BPO to process carrier documentation. Although the shipping codes were clearly visible, BPO agents couldn't find them. They may have been tired or rushing through a sea of differently formatted documents to hit a quota. But whatever the reason — they missed those codes.

Their system defaulted to premium rates, leading to millions in carrier overpayments over just six months. This is where artificial intelligence offers a practical solution. Where humans get overwhelmed, misread documents, or take too long to process information, AI systems handle these tasks quickly and accurately. Plus, AI learns from its mistakes after only being taught once. Humans may falter several times before they know better.

1. AI reads and processes all carrier document formats

3PLs face a fundamental challenge—their carriers send important shipment information in many different ways, from EDI files and PDFs to basic emails and text messages. This fragmentation has pushed many 3PLs to rely on BPOs for manual document processing, creating a complex web of information beyond basic data entry. It requires teams to pull relevant information from various sources, check it against the 3PL's policies, and decide whether to update systems or start escalation procedures. 

When BPO staff handle high volumes of documents, even small mistakes can become major issues. For example, a mistyped container number might mean a shipment gets overlooked at the port, while an incorrectly entered delivery time could throw off an entire supply chain schedule. These errors are particularly problematic with cross-border shipments, where a single mistake in product codes or quantities can lead to disputes over payment.

Many products claim to fix this process but fail because they can't adapt to a 3PL's custom workflow like AI can. AI can extract unstructured data, like whether a delivery was signed, from a variety of differently formatted documents and always ensures it evaluates that data against the most up-to-date policy.

Consider how AI could fix this process, using ocean shipments as an example. A carrier sends daily EDI files containing arrival times and customs clearance status. Without automation, staff must manually parse these messages and enter them into the TMS—a process where a single misread field can trigger expensive demurrage fees. 

An AI system can instead automatically read these files, standardize the data, check it against the 3PLs policy, and update the TMS in real-time. BPOs have a harder time with this. Even the most well-rested and diligent employees will find it challenging to keep up with ever-changing policies, let alone managers who need to enforce new rules consistently across hundreds of BPO employees. If you’re working with tens of thousands of customers — even if they each change their policies just once a year — that could mean a policy change every day. Humans can't perfectly track all these changes, but AI can.

This capability extends to simpler formats like PDF manifests from regional carriers or email updates from small couriers. It can even process plain text messages like "Picked up 3 boxes from Warehouse A at 10:17 AM" and turn them into normalized data.

2. AI escalates issues immediately

BPOs have to manually check spreadsheets, emails, and carrier portals to spot problems. They compare expected times against actual status updates and then notify the 3PL if something's wrong. 

AI completely automates this manual process by watching all these data sources in real time, automatically catching problems, and then escalating them in your TMS.

For example, a 3PL shipping electronics from Europe to the U.S. might expect customs to clear the shipment by mid-week. 

Without AI, staff might not notice a delay until the warehouse starts complaining or they are hit with demurrage fees. But AI immediately spots the missing customs clearance, letting the 3PL jump in to handle the issue. 

3. AI continually learns to improve tracking accuracy

BPO teams can't match AI's learning speed. While human teams might review historical performance every few months to adjust their estimates, AI systems constantly process new shipment data and refine their predictions. This means more accurate ETAs and better decision-making for both 3PLs and shippers.

Take holiday season logistics planning. A BPO team typically updates its forecasts once a quarter using basic spreadsheets, but when they spot a trend, it's often too late to prevent disruptions. AI systems, on the other hand, constantly analyze current shipping patterns and carrier performance. This means 3PLs can proactively adjust their capacity and routing well before issues impact deliveries.

The advantages are obvious in situations like long-haul trucking. BPO teams plan routes using standard drive times that don't account for traffic or weather. AI systems combine live GPS data with historical performance to improve route planning.

AI also transforms how 3PLs manage their carrier relationships. Instead of waiting for quarterly reviews or customer complaints, AI systems track carrier performance metrics in real time. They can spot declining service levels early and automatically and make strategic recommendations for better carriers based on actual performance data.

4. AI integrates across systems to create a single source of truth 

The impact of AI goes beyond just learning from data—it transforms how your systems work together. While BPOs typically handle data manually, copying information between different platforms, AI creates direct connections that automatically keep everything in sync.

Take cross-border shipments as an example. When a carrier updates their arrival time, that information needs to flow into multiple places: your TMS for delivery planning, your WMS for warehouse staffing, and your ERP for payment tracking. Instead of waiting for someone to update each system manually, AI instantly pushes these changes everywhere they need to go.

AI is only as powerful as the systems it connects to. When you're looking at AI solutions, find a company who you’re confident can integrate with the same systems your BPO uses. Whether you're running an older TMS that only handles EDI files or the latest cloud-based platforms, AI should be able to adapt to your existing setup. This flexibility should extend across your entire technology stack, connecting seamlessly with TMS platforms, ERP systems, warehouse management systems, and document storage in SharePoint or Google Drive.

Take invoice processing, for example. When carriers submit invoices, AI should be able to automatically extract the key details, validate them against contracted rates, and update your ERP system. This will replace error-prone manual data entry with instant, accurate updates.

This benefit can also be seen in shipper relationships. Rather than having partners log into multiple systems or wait for email updates, they would get a single, always-current view of their shipments. These direct system connections speed up operations and make them more reliable.

Go from reactive to proactive with Reindeer AI

The transition away from BPO or reliance on shared services represents a fundamental shift in how 3PLs can operate. When outsourced teams handle critical documentation and communication, they effectively control your reputation and customer relationships—a risky position for any logistics provider.

Reindeer AI addresses this challenge by automating the routine digital tasks typically outsourced to BPOs: payment approvals, document processing, and other data-heavy operations. Their system is particularly valuable for 3PLs and freight forwarders who deal with non-standardized data from multiple sources. Instead of managing overseas teams or troubleshooting data entry errors, these companies can bring operations back in-house while improving speed and accuracy.

The logistics industry is ready for this change. Companies that take control of their core processes through AI automation aren't just reducing errors—they're positioning themselves to provide fundamentally better service. The technology exists; the main question now is who will adapt first.