Accelerate approval processes: AI routes intelligently – optimal forwarding based on responsibilities

How AI Intelligently Routes Approval Processes

Imagine your digital inbox had an extremely experienced assistant. Someone who analyzes every document in seconds and instantly knows: This goes to Thomas in Engineering, that to Anna in HR, and this one is definitely a case for the executive team.

That’s exactly what smart AI routing delivers.

What is Intelligent Document Routing?

Intelligent routing leverages machine learning (ML) and natural language processing (NLP) to automatically classify incoming documents and forward them to the responsible people. The system continuously learns from past decisions and gets more accurate over time.

The AI analyzes various factors:

• Document type: contract, invoice, proposal, complaint letter
• Context: department, product category, customer group
• Value thresholds: automatic escalation above certain amounts
• Urgency: recognition of time-sensitive phrases and deadlines
• Sender information: customer type, supplier, internal department

The Technology Behind AI Workflow Optimization

Three core technologies work seamlessly together to deliver intelligent routing:

Document Intelligence: OCR (Optical Character Recognition) converts scanned documents into machine-readable text. Modern systems also recognize tables, signatures, and logos.

Natural Language Processing: NLP algorithms understand the context of the text. They can tell the difference between a “termination of lease agreement” and “employee termination”—even though both documents contain the word “termination.”

Rule-Based Logic: In addition to AI analysis, you can define fixed rules. Example: “All invoices over €10,000 automatically go to management for approval.”

Automated Assignment of Responsibility in Practice

Let’s look at a real-world example: A mechanical engineering company receives about 50 different documents by email each day.

Without AI routing: The secretary reads every email, decides who to forward it to, then manually enters the recipients. Time spent: roughly 90 minutes a day.

With AI routing: The system automatically analyzes all incoming emails and routes them to the right place within seconds. Time spent: just 10 minutes for control and exception handling.

The result? 80 minutes saved every day—with a significantly lower error rate.

The 5 Key Benefits of Automated Responsibility Assignment

Why are more and more companies investing in intelligent routing systems? The answer lies in measurable benefits that go far beyond simply saving time.

1. Drastic Reduction in Processing Times

Intelligent routing systems can significantly cut the average processing time for approval workflows.

It’s simple: Documents land immediately with the right contact. No detours, no back-and-forth, no delayed handovers.

A mid-sized company with 100 employees can save an average of 15 hours per week—time that can be put to productive use.

2. Fewer Errors Due to Human Oversight

People make mistakes. Especially with repetitive tasks like manually sorting documents.

AI systems, by contrast, work consistently. They don’t get tired, distracted, or forget forwarding rules. The error rate drops from the typical 8-12% to below 2%.

This means: fewer corrections, less frustration among colleagues, and fewer lost business opportunities due to delayed processing.

3. Transparency and Traceability Across All Processes

Where’s the contract right now? Who last worked on it? How long has it been sitting there?

Intelligent routing systems automatically document every step. You get real-time overviews of all ongoing approval workflows and can spot bottlenecks instantly.

This transparency helps not only with controlling but also with ongoing process optimization.

4. Automatic Escalation of Critical Situations

Some documents are time-sensitive. A proposal that needs to be signed by Friday. An invoice offering a 2% early payment discount if processed within 10 days.

The AI system detects such deadlines automatically and escalates in time—via email, SMS, or direct notification within the system.

This way, you never miss important deadlines—and your suppliers appreciate timely payments.

5. Scalability Without Proportionally Rising Personnel Costs

Your company is growing? Congratulations! But that also means: more documents, more approvals, more complexity.

With manual routing, you’d need to hire more staff accordingly. An intelligent system, however, scales with you—without additional full-time positions.

Investment in AI routing pays for itself especially quickly for growing companies.

Step-by-Step: Implementing AI Routing in Your Company

Theory is all well and good, but how do you actually bring intelligent routing into your business?

Here’s the proven approach we’ve used successfully with over 50 mid-sized companies:

Phase 1: Analyze Existing Approval Processes (2-3 Weeks)

Before automating anything, you need to understand whats actually happening—and especially, what isn’t working.

Catalog document types: What kinds of documents come in daily? Invoices, quotes, contracts, complaints? Create a complete list with average daily volumes.

Document current routing paths: Who decides on forwarding? What are the criteria? How long does it typically take?

Identify pain points: Where do delays regularly occur? Which documents often end up with the wrong recipient?

A helpful tool for this phase: Keep a “routing diary” for a week. Log each forwarding operation with timestamp and reason.

Phase 2: Define and Prioritize Business Rules (1-2 Weeks)

Now it gets interesting: Define the rules your AI system should use to make decisions.

Create a responsibility matrix: Who is responsible for which type of document? At what value thresholds must escalation occur?

• Invoices up to €1,000 → Department Manager
• Invoices €1,000-10,000 → Division Head
• Invoices over €10,000 → Management
• Personnel topics → HR Department
• Technical inquiries → Engineering
• Complaints → Customer Service + Quality Management

Define exception rules: Any special cases? Specific customers who always go straight to management? Suppliers with special arrangements?

Set escalation levels: After how much time without action should the system escalate automatically?

Phase 3: Start with a Pilot Project Using One Document Type (3-4 Weeks)

Start small and learn fast. Choose the simplest document type—for most, that’s incoming invoices.

System selection and setup: Choose a suitable AI routing solution and configure it for your pilot area.

AI training: Feed historical data into the system. The more examples, the better the AI learns your specific routing patterns.

Parallel operation: Run both the old manual system and the new AI system side by side at first. This allows you to analyze differences and make adjustments as needed.

Train your team: Your staff need to understand how the new system works and how to handle exceptions.

Phase 4: Optimization and Gradual Rollout (4-6 Weeks)

After a successful pilot, it’s time to fine-tune and expand.

Analyze performance: How accurately is the system routing? Where do errors still occur? Which rules need adjustment?

Integrate more document types: Gradually expand the system to cover new categories—no more than one new type per week.

Establish feedback loops: Make it easy for employees to report incorrect routings. This information flows directly back into machine learning.

Deepen integration: Link the routing system to your existing tools: CRM, ERP, document management.

Phase 5: Full Productive Operation and Continuous Improvement

After about three months, you have a functioning intelligent routing system up and running.

But a word of caution: this isn’t the time to rest on your laurels. AI systems get better the more they learn.

Regular reviews: Analyze performance metrics monthly. Where is there still potential for optimization?

Add new rules: Your company will continue to evolve. New products, new departments, new processes—your routing system needs to keep pace.

Include team feedback: Your employees are your best testers. Listen to their suggestions for improvement.

Common Pitfalls When Introducing Intelligent Workflows

Let’s be honest: Not every AI implementation goes smoothly. With experience from over 50 projects, clear patterns have emerged—typical mistakes you can avoid.

Pitfall 1: Underestimating Incomplete Data Quality

The number one killer for intelligent routing systems? Poor data quality.

The problem: Your historical documents might not be as neatly structured as you think. Scanned PDFs with poor resolution, emails with vague subject lines, attachments in exotic formats.

The solution: Invest time up front in data cleansing. Define clear standards for incoming documents. Train external partners to submit documents in a structured way.

Practical tip: Start with a “clean slate”—all new documents from go-live must be structured. You can work through historical data gradually afterwards.

Pitfall 2: Rules That Are Too Complex From the Outset

Many companies want to account for every possible exception and special case from day one.

The result: A system with 150 different rules that gets it wrong 30% of the time because the rules contradict each other.

The solution: Start with the 80% standard cases. Handle complex exceptions manually at first. Gradually add rules over time as you gain experience.

Remember: A system that correctly automates 80% of cases is better than one that’s unreliable with 100% of them.

Pitfall 3: Ignoring Employee Resistance

“AI will take my job away”—a concern that’s very human and understandable.

If you don’t include employees from the very start, they’ll sabotage the system—not out of malice, but out of fear.

The solution: Transparent communication from day one. Explain that AI takes over repetitive tasks so employees can focus on more valuable work.

Show concrete examples: Instead of manually sorting documents, the secretary can concentrate on customer service. Instead of fixing routing errors, the department manager can drive strategic projects forward.

Pitfall 4: No Success Measurement

How do you know if your AI routing is working? Many companies implement the system and then never check if it actually delivers on its promises.

The solution: Define clear KPIs before implementation:

• Average processing time per document type
• Number of misrouted documents per week
• Time spent on manual routing corrections
• Employee satisfaction with the new system

Measure these values before, during, and after rollout. Only then can you prove ROI and identify areas for further optimization.

Pitfall 5: Inadequate Technical Integration

An AI routing system that operates in isolation next to your existing tools won’t achieve the desired effect.

Your employees don’t want to juggle five different systems just to complete one approval process.

The solution: Plan integration with your existing IT infrastructure from the very beginning. The AI system should work seamlessly with your CRM, ERP, and email system.

If full integration isn’t immediately possible, at least ensure automatic data synchronization and unified user interfaces.

ROI and Success Measurement: The Business Case for AI-Based Routing

The key question for any CEO: Does investing in intelligent routing actually pay off?

The honest answer: It depends on your company. But with the right metrics, you can precisely calculate if—and when—the investment will break even.

Calculating Costs Realistically

Let’s be transparent: AI routing isn’t free—to implement or to operate.

One-time implementation costs:

• Software license or cloud platform: €15,000-50,000 depending on company size
• Consulting and implementation: €10,000-30,000
• Employee training: €2,000-5,000
• Data cleansing and migration: €5,000-15,000

Ongoing operating costs (per year):

• Software maintenance: 20-30% of license costs
• Cloud hosting (if required): €3,000-8,000
• Administrative support: 0.2-0.5 FTE (full-time equivalent)

For a mid-sized company with 100 employees, this equates to about €40,000-80,000 in the first year and €15,000-25,000 each following year.

Measuring the Savings Precisely

Where do you actually save money? Here are the main levers with realistic calculation bases:

Time savings from manual routing:

A typical 100-employee company processes about 150 incoming documents per day. With manual handling, the time spent is:

• Document review and decision: 2 minutes per doc = 300 minutes/day
• Forwarding and follow-up: 1 minute per doc = 150 minutes/day
• Correcting misrouted docs: 10% error rate × 5 mins = 75 minutes/day

Total: 525 minutes (8.75 hours) daily

AI routing reduces the effort to about 60 minutes per day (exception handling and quality control).

Savings: 7.75 hours per day = 1,940 hours per year

At average personnel costs of €35/hour, that’s a saving of €67,900 per year.

Reduced cost of delays:

Misrouted or delayed documents cause secondary costs:

• Missed discounts due to delayed invoice processing: approx. €3,000/year
• Delays in proposals due to misrouting: €15,000/year
• Compliance risks from contracts not handled in time: hard to quantify, but very real

Additional saving: about €18,000 per year

ROI Calculation for Different Company Sizes

Key Metrics for Ongoing Success Measurement

After implementation, you should monitor these KPIs monthly:

Efficiency metrics:

• Average routing time per document
• Share of automatically routed documents (target: >90%)
• Manual corrections per week

Quality metrics:

• Routing accuracy (target: >95%)
• Average processing time from receipt to approval
• Number of escalation cases due to missed deadlines

Business impact metrics:

• Staff hours saved per month
• Reduced lead times for critical processes
• Employee satisfaction with the new system

Pro tip: Set up a monthly dashboard with the most important metrics. That way you’ll quickly spot when adjustments are needed.

When Doesn’t AI Routing Pay Off?

Honesty is good advice: Intelligent routing isn’t worthwhile for every organization.

Not suitable if:

• Less than 20 documents per day (volume too low)
• Very simple, already effective manual processes
• Less than 20 employees (overhead too high)
• Very specific document types requiring much human judgement

In these cases, implementation and maintenance effort will likely outweigh the benefits.

The Future of Approval Processes: What Comes After Intelligent Routing

Intelligent routing is just the beginning. AI-powered process automation is evolving at an incredible pace.

Which trends should you be watching—and what do they mean for your investment decisions today?

Trend 1: From Routing to Intelligent Preparation

The next stage: AI not only routes documents, it also prepares them for decision-making.

In practice, this means: A contract isn’t just sent to the in-house lawyer, but arrives already accompanied by an automatic risk analysis, benchmarking with similar contracts, and specific suggested changes.

By 2027, it’s expected that about 40% of all approval workflows will not only be intelligently routed but also AI-prepared.

This saves time not just in routing, but also in the actual processing.

Trend 2: Predictive Routing Based on Workload

Currently, AI routes mainly based on document content and fixed responsibilities.

The future: The system will also consider recipient workload, subject matter expertise, and even past processing speed.

Example: A technical issue normally goes to Engineer A. But A is overloaded and has taken longer with similar cases before. The system now routes to Engineer B, who is available and has proven fast with that issue type.

Trend 3: Automated Approvals for Standard Cases

Why should a human approve an invoice if all criteria are fulfilled and it’s from a trusted vendor?

Advanced AI systems will fully automate standard approvals. People will only need to intervene in exceptions, unusual cases, or when thresholds are exceeded.

It’s estimated that up to 70% of routine approvals could be handled without human intervention.

Trend 4: Integration with Conversational AI

The future of human-AI interaction is natural language. Instead of complex user interfaces, your employees simply talk to the system:

All invoices from vendor XY over €5,000 should also go to management from now on.

Show me all contracts expiring in the next 30 days that haven’t been renewed.

Why was yesterday’s cost estimate forwarded to Anna instead of me?

The system understands the request, executes it, and explains its decisions in plain language if needed.

What Does This Mean for Your Decision Today?

These future trends have real consequences for the investment decisions you make now:

Choose future-ready platforms: Ensure your AI routing system is extensible and offers open APIs, so you can add new features later without a complete overhaul.

Plan modular growth: Start with basic routing, but design your processes so they can gradually become more intelligent.

Invest in data quality: The better your data foundation now, the more you’ll benefit from future AI improvements.

Continuously train your team: The AI landscape is evolving rapidly. Make sure your employees keep up with the technology.

Realistic Timelines for New Features

• 2025: Intelligent document preparation becomes standard in enterprise solutions
• 2026: Predictive routing based on workload becomes widely available
• 2027: Automated standard approvals reach 90%+ accuracy
• 2028: Conversational AI for process management becomes mainstream

The take-home message: Don’t wait for the “perfect” future solution. Start with intelligent routing today and gradually adopt advanced features as you grow.

Companies that get started today will not only save costs in three years, but also gain invaluable experience with AI-driven processes—experience that will be a key competitive advantage once AI becomes the industry standard.

Frequently Asked Questions (FAQ)