Paper Will Not Disappear — How Decision Trace Model × Multi-Agent Systems Transform the Role of Documents and Forms*

Introduction

Even as digitalization advances, paper and forms are still widely used in real-world operations.

• Application forms
• Quotations
• Inspection records
• Medical records
• Contracts

Many people believe:

👉 “Paper will eventually disappear.”

However, reality is different.

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Why Paper Will Not Disappear

The reason is simple:

👉 Paper is a human decision interface.

Paper and forms are not merely records.

They are used to:

• Verify
• Approve
• Explain
• Agree

In other words, they are media that support decision-making itself.

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The Problem with Traditional Digitalization

Most digital transformation (DX) follows this pattern:

• Paper → PDF
• Manual input → Form input

However, the essence has not changed.

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Problem ①: Meaning Is Not Structured

In many digitalization efforts, paper fields are simply converted into form inputs.

As a result:

• What the information means
• Which decisions it is used for
• How it relates to other data

are not clearly defined.

Data accumulates, but it does not become knowledge usable for decision-making.

Furthermore:

• Why a field is important
• Under what conditions decisions change
• What rationale led to the conclusion

are not recorded.

So later, we only see entered facts, not decision reasoning.

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Problem ②: Decision Flow Is Fragmented

Real-world operations follow a continuous flow:

However, traditional systems split this into:

• Different screens
• Different systems
• Different people

This causes:

• Input data not fully used during approval
• Decision reasoning not passed to execution
• Results not feeding back into improvement

👉 The workflow is digitalized, but
👉 the decision flow itself is disconnected

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Problem ③: Lack of Explainability

Traditional systems record:

• Application content
• Approver
• Timestamp
• Result

But the most important part is missing:

• What was considered
• Which conditions mattered
• Why it was approved or rejected

As a result:

• We know what happened
• But not why it happened

This leads to:

• Inability to explain decisions
• Poor auditability
• No reproducibility
• No learning from past decisions

👉 Results are recorded, but reasons are not
👉 Therefore, decisions cannot be traced

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The Direction of the Solution

Transform Forms into Decision Systems

This is where:

👉 Decision Trace Model × Multi-Agent Systems

becomes essential.

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Redefining Forms

Before

Forms were:

• Input containers
• Storage for records

👉 A repository of results

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After

Forms become:

👉 Interfaces that trigger decisions

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Forms Through the Decision Trace Model

Forms initiate the following flow:

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What Happens at Each Step

Event

• Paper forms
• PDFs
• Handwritten notes
• Images

All become system inputs.

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Signal

• OCR
• Semantic understanding
• Structuring

👉 From readable data to decision-ready data

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Decision

• Rule matching
• Case comparison
• Risk evaluation

👉 Decisions executed as logic

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Execution

• Workflow updates
• Notifications
• Integration with business systems

👉 Decisions directly connected to operations

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Human

• Final validation
• Exception handling
• Responsible decision-making

👉 Humans focus on critical decisions

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Log

• Why decisions were made
• Which rules applied
• What data influenced outcomes

👉 Full traceability

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Multi-Agent Processing of Forms

This flow is realized by multiple agents:

① Document Understanding Agent

(OCR + semantic parsing)

② Context Agent

(Background integration)

③ Policy Agent

(Rule enforcement)

④ Risk Agent

(Risk detection)

⑤ Decision Agent

(Decision generation)

⑥ Explanation Agent

(Explainability)

⑦ Execution Agent

(Action execution)

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Overall Transformation

Before

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After

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The New Role of Forms

Forms evolve from:

👉 Information containers

to

👉 Decision interfaces

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Paper × AI: A New Model

Paper does not disappear.

Because it still has strong advantages:

• Easy to use
• Low learning cost
• Fits real-world workflows
• Ideal for face-to-face interactions

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What Changes

Paper remains, but its meaning changes.

Before:

• Something to fill
• Something to circulate
• Something to store

After:

• Input interface
• Entry point for decision systems
• Trigger for AI-driven workflows

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The Backend Becomes AI

Behind the paper:

• Data is automatically extracted
• Context is integrated
• Rules are applied
• Risks are evaluated
• Decisions are generated
• Execution is automated

👉 Front: Paper
👉 Back: AI

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Before / After

Before

• Manual processing
• Experience-dependent decisions
• No traceability
• High workload

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After

• AI-assisted decisions
• Consistent judgment
• Full traceability
• Reduced workload

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Practical Impact

Manufacturing

• Inspection → Anomaly detection
• Reports → Improvement suggestions

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Healthcare

• Records → Decision support
• Better explainability

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Finance

• Contracts → Risk detection
• Faster approvals

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Field Operations

• Paper input → AI-driven decisions
• Less workload
• Higher accuracy

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Conclusion

Traditional DX focused on:

• Digitizing information
• Improving input efficiency
• Storing data

However, the real problem is:

• Decisions are not structured
• Reasons are not recorded
• Processes are fragmented

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The Shift

👉 We must treat decision-making itself as a system

With Decision Trace Model × Multi-Agent:

• Forms become decision triggers
• AI understands meaning
• Context, rules, and risks are integrated
• Decisions are generated
• Reasons are explained
• Execution is automated
• Everything is recorded

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Final Insight

• Decisions become consistent
• Operations become explainable
• Improvement becomes continuous
• Workload is reduced

And most importantly:

👉 The way people work does not need to change

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Final Message

Paper will remain.
But its meaning will change.

• From record → to decision trigger
• From information → to decision system

This is not just efficiency improvement.

👉 It is the reconstruction of business itself as a decision system