On-Demand Webinar: Overcoming Three Persistent Challenges After AI Adoption in Due Diligence and Valuation - Practical Solutions for Error Control, Prompt Dependency, and Excel Transfer Disruption
Key facts
- On-Demand Webinar: Overcoming Three Persistent Challenges After AI Adoption in Due Diligence and Valuation - Practical Solutions for Error Control, Prompt Dependency, and Excel Transfer Disruption
- DataSnipper has launched an on-demand webinar video addressing practical challenges of AI adoption in Due Diligence (DD) and valuation operations. While generative AI use expands, the field still faces issues such as controlling errors, reducing the burden of optimizing prompts per case, and eliminating manual transfer of AI outputs to Excel. This video explains how to overcome these three barriers in real-world DD and valuation scenarios.
- Source: PR Times
- Date: June 10, 2026
Direct answer
DataSnipper has launched an on-demand webinar video addressing practical challenges of AI adoption in Due Diligence (DD) and valuation operations. While generative AI use expands, the field still faces issues such as controlling errors, reducing the burden of optimizing prompts per case, and eliminating manual transfer of AI outputs to Excel. This video explains how to overcome these three barriers in real-world DD and valuation scenarios.
- Citation
- On-Demand Webinar: Overcoming Three Persistent Challenges After AI Adoption in Due Diligence and Valuation - Practical Solutions for Error Control, Prompt Dependency, and Excel Transfer Disruption (June 10, 2026), PR Times
- Source
- PR Times
- Date
- June 10, 2026
DataSnipper has launched an on-demand webinar video addressing practical challenges of AI adoption in Due Diligence (DD) and valuation operations. While generative AI use expands, the field still faces issues such as controlling errors, reducing the burden of optimizing prompts per case, and eliminating manual transfer of AI outputs to Excel. This video explains how to overcome these three barriers in real-world DD and valuation scenarios.
📋 Article Processing Timeline
- 📰 Published: June 10, 2026 at 10:00
- 🔍 Collected: June 10, 2026 at 10:33 (33 min after Published)
- 🤖 AI Analyzed: June 10, 2026 at 20:03 (9h 29m after Collected)
This video explains how to overcome these three barriers in line with practical DD and valuation scenarios.
Click here for details on the on-demand distribution.
[Background of the On-Demand Distribution]
In recent years, interest in AI utilization has been rapidly increasing in DD and valuation operations. Particularly in tasks involving reading large volumes of documents, extracting, organizing, and verifying necessary information within a limited timeframe, expectations for efficiency through AI are rising. On the other hand, there are many challenges in the field that cannot be solved simply by introducing AI.
For example, anxiety about errors regarding how much AI responses can be trusted, prompt dependency requiring changes in instruction methods for each case, and the manual workload of transferring AI output results back to Excel or work sheets are typical issues hindering practical adoption in DD and valuation. There are cases where, despite using AI, the burden of review and transcription remains, making the field more complex.
This video, based on these challenges, explains how AI should be positioned in DD and valuation practice, and how autonomous AI can support a series of accounting tasks. It is characterized not just as an introduction to AI trends, but by delving into which tasks and in what form AI is easy to implement in practice, and how to ensure reviewability and reproducibility.
[What You Will Learn in This Video]
- Three practical challenges that tend to remain after AI adoption in DD and valuation operations
- Why error control, prompt dependency, and Excel transfer disruption occur
- How autonomous AI can fill operational gaps that conventional AI could not easily bridge
- How to consider AI utilization from the perspective of balancing reviewability and operational workflow
Click here for details on the on-demand distribution.
▶︎ Recommended for:
- Professionals in FAS, PE, investment banking, FA/brokerage firms engaged in DD and valuation operations
- Those who have tried generative AI but feel challenges in practical adoption
- Those looking to further streamline the processes of information extraction, organization, and verification
- Those who want to advance AI utilization without significantly changing their current Excel-centric operations
[On-Demand Distribution Overview]
Video Title: 2026 Edition: AI Utilization in DD and Valuation Operations: The Emergence of Autonomous AI for One-Click Accounting Tasks
Distribution Format: On-demand
Viewing Fee: Free
Target Audience: Professionals in FAS, PE, investment banking, FA/brokerage firms engaged in valuation and due diligence
How to View: Please register from the page below
Registration URL: https://eu1.hubs.ly/H0vXRym0
Notes: Applications from competing companies may be declined.
About DataSnipper
DataSnipper is an AI-powered Excel add-in digital audit platform that automates document matching, data extraction, and workpaper creation in audit and accounting operations. It reduces checking time by up to 90% compared to manual work, simultaneously enhancing audit quality and speed. It is used by over 600,000 users in more than 175 countries worldwide, and in Japan, it is used by major audit firms and Sumitomo Mitsui Banking Corporation.
[Company Overview]
SwiftLink Inc.
Established by members with the aspiration to 'change the world.' Our philosophy is to support 'sales capabilities,' create opportunities for valuable products to be provided to the markets that need them, and become a strategic partner necessary for corporate growth.
Established: January 22, 2024
Representative: Representative Director Satoshi Tanaka
Location: Navi Shibuya V 3F, 5-5 Maruyama-cho, Shibuya-ku, Tokyo
Website: https://www.swiftlinkglobal.com/
Business: Support for Japanese companies expanding overseas, support for foreign companies entering Japan, approach and scouting of overseas startups, meeting facilitation, overseas sales, marketing support, startup growth support
DataSnipper B.V.
Founded in 2017 to solve the repetitive manual work and inefficient data processing challenges faced by those involved in auditing. The company's mission is 'to help make better decisions by quickly verifying trustworthy data.' To achieve this, it aims to enhance data reliability by clarifying data provenance and providing context.
Company Name: DataSnipper B.V.
Established: 2017
Representative: CEO Vidya Peters
Japan Head: Genki Sunayama
Location: Hikarie Office Tower 33F, 2-21-1 Shibuya, Shibuya-ku, Tokyo
Website: https://www.datasnipper.com/jp
Business Overview: Software development and operation
Contact for this matter:
SwiftLink Inc. (DataSnipper Office)
Email: business@swiftlinkglobal.com
Inquiry: https://www.swiftlinkglobal.com/contact-ja
FAQ
What can I learn from this webinar?
You can learn about three post-AI adoption challenges in DD and valuation (error control, prompt dependency, Excel transfer) and solutions using autonomous AI.
Who is the target audience?
Professionals in FAS, PE, investment banking, FA/brokerage firms involved in DD and valuation, and those facing challenges with generative AI adoption.
Is there a fee to watch?
No, it is free. However, applications from competing companies may be declined.