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PrivacyTech Co., Ltd. will officially launch “PrivacyTech GRoW-VA,” a Compound Intelligence-type AI platform that helps companies resolve their chronic labor shortages, on May 29, 2026.
GRoW-VA is a platform that comes standard with a large number of LLM-integrated Packages/Modules, allowing for the quick development and implementation of customized AI applications for each client company, provided that business requirements are defined. For the past five years since our founding, we have specialized in supporting companies in the fields of AI and data governance. This area is characterized by a severe shortage of specialized personnel and is an extremely difficult area to implement AI in, with a huge amount of communication occurring between operational and specialized departments. We have systematized the knowledge we have accumulated in this most challenging area into a platform, and as the first phase, we will provide it to business areas where communication occurs between operational and specialized departments, such as AI and data governance, security checks, vendor identification (supply chain understanding), internal controls (J-SOX compliance), and ISMS renewal support .
Background of the launch
The shortage of skilled personnel in specialized fields is the biggest bottleneck in AI adoption.
While the use of AI in companies is rapidly advancing, there is a chronic shortage of personnel in specialized areas such as AI and data governance, compliance, internal control, and information security. In these areas, cumbersome back-and-forth processes such as “consultation, document creation, review, countermeasure consideration, and result sharing” occur between operational departments and specialized departments, leading to reliance on individual expertise and chronic delays in work.
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Changes in the regulatory environment will further increase the workload of specialized tasks.
With the amendment to the Personal Information Protection Act approved by the Cabinet in April 2026, the EU AI Act, and the development of AI governance guidelines in various countries, corporate governance is now required to go beyond mere legal compliance and encompass an integrated approach that includes ethics, social acceptance, and brand recognition. The structural gap between the ever-increasing volume of specialized work and the continuing shortage of skilled personnel is the biggest bottleneck in AI adoption.
General-purpose LLMs cannot make “corporate-like decisions.”
Simply implementing a general-purpose LLM (Limited Licensing Model) into business operations will not produce “corporate-specific judgments.” This is because only about 20% of the information within a company is structured, while the remaining 80% is scattered as unstructured data, including “business context” such as meetings, emails, chats, and documents (Gartner, 2023). Because organizational knowledge such as internal regulations, past review precedents, operational manuals, and individual know-how is not structured, general-purpose AI will converge to safe, median answers and will not be able to reach company-specific judgments.
SOURCE: PRTimes
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