Frost & Sullivan, commonly referred to as Frost & Sullivan, during the 2026 China International Service Trade Fair, officially released for the first time the "Public Trusted Knowledge Network (PTKN) co-construction plan," and began recruiting partners from industry institutions, knowledge producers, verification partners, technology platforms, and application responsible parties.
As artificial intelligence's ability to acquire, integrate, and reorganize information continues to improve, whether industry knowledge can be accurately understood, verified, and continuously updated has become a governance issue of concern to enterprises and the industry. When AI provides a figure on the industry market size, is it the sales volume, shipment quantity, or final transaction amount? Which year and region does it correspond to? What is the source, calculation method, and rationale for the selection? The answers to these questions often determine the reliability of business decisions.
Knowledge 3.0: From "stored and accessible" to "reliable use with accountability"
PTKN is based on Frost & Sullivan's "Knowledge 3.0" research framework. According to Wang Chenhui, managing partner and president of Frost & Sullivan, in this framework, Knowledge 1.0 focuses on "storing" – text, publications, archives, and corresponding professional systems, enabling knowledge to be stablely recorded, referenced, and passed down beyond individual memory; Knowledge 2.0 focuses on "accessibility" – the internet, search engines, databases, and network collaboration, allowing dispersed content to be connected, discovered, and jointly produced across regions and organizations. The new challenge faced by Knowledge 3.0 is: when machines begin to participate in the selection, transformation, and use of knowledge, can a piece of knowledge continue to be reliably used by humans and machines, can it be traced, questioned, corrected, and have someone responsible for it?
Frost & Sullivan refers to the units of knowledge that machines truly need as "knowledge objects" – they are not the shortest text segments, but the smallest units that can be identified and called upon with necessary context and can return to the original material for verification. To prevent knowledge objects from becoming distorted during transmission, Knowledge 3.0 proposes five types of questions that cannot be forgotten: the content layer explains what it is about and what conditions it applies to; the experience layer preserves the context, trade-offs, and exceptions of judgment; the evidence layer connects direct sources, methods, and conflicts; the responsibility layer records who provided, transformed, verified, published, maintained, and corrected; the lifecycle layer explains versions, status, alternative relationships, and reasons for changes.
Frost & Sullivan points out that these three capabilities are not mutually exclusive. Complete documents remain important carriers for preserving the argument process, institutional context, and complex judgments; what needs to be added is another capability: after key knowledge in a document leaves its original location, it should still be able to move with necessary context and return to the original text for verification.
PTKN: An inter-organizational public infrastructure for Knowledge 3.0
The Public Trusted Knowledge Network (PTKN) is an infrastructure solution for Knowledge 3.0 in inter-organizational public scenarios. Knowledge can still be distributed within the original systems of enterprises, research institutions, industry organizations, media, standard agencies, and legal authorities. PTKN connects knowledge, evidence, versions, and responsibilities through common data structures, verification mechanisms, identity and rights rules, and machine invocation interfaces.
PTKN builds on Frost & Sullivan's previous explorations in "Enterprise Trusted Knowledge Network (KNIT)" and "Open Industry Research Format (OIRF)". KNIT focused on how internal enterprises organize verifiable and sustainably maintained trusted knowledge; OIRF focused on how research records and published content preserve sources, evidence, and applicable boundaries. On this basis, PTKN further extends the perspective of trusted knowledge to inter-organizational and cross-subject industry public scenarios.
"In the past, research institutions were mainly responsible for a report; now, as AI begins to large-scale extract and reorganize knowledge, we also need to consider whether key knowledge can be reliably used after leaving the report," said Wang Chenhui, managing partner and president of Frost & Sullivan China. "The core value of PTKN is to improve the conditions for accurate understanding, verification, and correction of enterprise information."
Industry, academia, and research collaborate to accumulate theoretical and standard foundations
Regarding issues such as enterprise trusted knowledge, industry research, and enterprise expansion abroad, Frost & Sullivan has produced a series of publications, including "Brands in the AI Era: From Traffic Competition to Cognitive Management", "Applications of AI in Industry Research and Investment Management", and "The Growth Coaching Book (Guide to Enterprise Expansion Growth)", and participated in leading the formulation of the "Guidelines for Classification and Grading of Industry Research Data Governance" group standard, providing theoretical and standard foundations for PTKN co-construction.
In academic research, Frost & Sullivan is advancing projects related to Knowledge 3.0 and collaborating with well-known domestic universities, focusing on research on knowledge production, reliable use, and responsibility mechanisms in the AI era. In industrial practice, Frost & Sullivan is advancing strategic cooperation with two leading model manufacturers. One intends to cooperate on knowledge production around Agents and industry-defined knowledge, and the other intends to cooperate on Ontology knowledge and enterprise-level multi-agent capabilities.
Multiple parties participate and balance each other to build public trust
PTKN emphasizes that public trusted knowledge needs to be based on multiple parties' participation, mutual balance, and continuous review. Enterprises contribute first-party facts, data, and professional experience; research institutions and experts participate in evidence production and review; industry associations participate in the construction of terms, classification, and dispute mechanisms; technology and model partners participate in machine interfaces, evaluation, and correction; knowledge users should also have channels for feedback and objection submission.
Open propositions invite industry to verify together
PTKN has been officially proposed and entered public discussion. Currently, relevant work is in the stages of joint definition, mechanism improvement, and practical verification. As AI generates answers at an increasing speed, evidence, boundaries, versions, and responsibilities that can be continuously seen and verified will become a more scarce knowledge foundation. Frost & Sullivan invites industry institutions, enterprises, researchers, verification partners, technology platforms, and knowledge users to participate together, ensuring that sources, evidence, boundaries, versions, responsibilities, objections, and corrections truly enter the production and use process of industry knowledge.
If you wish to participate in PTKN co-construction, please scan the QR code below to fill in information. We will compile relevant intentions and contact you further based on the subsequent co-construction direction and fit.
