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Focus on Data Governance to Help Hong Kong Enterprises Build Trusted AI Decision-Making Capabilities

HONG KONG SAR – Media OutReach Newswire – 9 June 2026 – FanRuan Software, a leading business intelligence (BI) software brand in the Asia-Pacific region, today held the “FANRUAN DATA & AI SUMMIT 2026” at the Kowloon Shangri-La Hotel. Themed “Data Shapes AI, AI Redefines Decisions,” the summit brought together enterprise representatives and technology experts from industries including finance, construction, retail, and manufacturing to explore practical pathways for enterprise data governance, BI applications, and intelligent decision-making in the AI era.

At the event, FanRuan highlighted that as generative AI and intelligent analytics tools accelerate their entry into enterprise scenarios, the focus of Hong Kong businesses has shifted from “whether to adopt AI” to “whether AI can truly support business judgment and management decisions.” In an environment characterized by multiple coexisting systems, complex cross-departmental collaboration, and heightened compliance and access control requirements, enterprises lacking a consistent, accurate, and traceable data foundation will find it difficult for AI to produce analytical results trusted by management.

Therefore, FanRuan proposed an enterprise AI implementation pathway of “Governance First, Intelligence Second,” emphasizing that AI’s value stems not only from model capabilities but also depends on whether enterprises possess a governable, verifiable, and sustainably usable data foundation.

AI Applications Enter Deep Waters: Data Governance Becomes a Critical Prerequisite

In recent years, Hong Kong enterprises have actively explored AI applications in operational management, financial analysis, procurement decisions, customer engagement, and risk control. However, in actual implementation, many companies still face challenges such as data fragmentation, inconsistent metrics, system silos, and complex access controls.

For enterprises, the true value of AI lies not merely in generating answers, but in its ability to help managers faster understand business changes, diagnose problems, and take action based on trusted data. If underlying data sources are untraceable, metric definitions are inconsistent, or different departments maintain separate versions of data for the same business issues, even advanced AI tools will struggle to form analytical bases credible to decision-makers.

FanRuan believes that enterprise AI applications are moving from tool experimentation into the deep waters of business operations. In the future, the key to successful AI adoption within enterprises hinges on whether they can first establish a clear, stable, and manageable data governance foundation.

From Standardization to Intelligent Analytics: FanRuan Presents an Enterprise AI Implementation Pathway

Addressing enterprise needs to progress from data governance to intelligent decision-making, FanRuan showcased its “Governance First, Intelligence Second” implementation approach at the summit, helping enterprises sequentially build comprehensive capabilities from data standardization and BI applications to AI analytics.

First, at the data standardization level, FanRuan provides standardized analytics templates across multiple industries through Fine Gallery (App Marketplace), assisting enterprises in rapidly establishing consistent metric definitions and analytical frameworks. For companies whose data architectures still require refinement, standardized analytics scenarios serve as a starting point for building a Single Source of Truth (SSOT), reducing cross-departmental communication costs and enhancing the reusability of data applications.

Second, at the BI application level, FanRuan helps enterprises transform data scattered across ERP, finance, procurement, project management, CRM, and other systems into reports, dashboards, and analytical charts usable by both management and business teams. Through consistent data presentation and access control management, enterprises can more effectively grasp operational conditions, transforming data from backend records into daily management tools.

Building on this foundation, FanRuan further demonstrated Dora Data Agent, an AI-powered data analytics assistant designed for enterprise management and business analysis scenarios. Based on governed enterprise business data, Dora assists users in conducting multi-dimensional root-cause analysis, anomaly interpretation, and issue diagnosis. When enterprises face performance fluctuations, cost variations, procurement anomalies, or deviations in operational metrics, Dora helps managers shorten the time from “problem discovery” to “cause diagnosis,” making AI analytics more aligned with actual business objectives and decision-making contexts.

Deepening Presence in Hong Kong Market to Drive AI Data Analytics Adoption

FanRuan stated that for AI applications to deliver long-term value within enterprises, reliance on single tools is insufficient; supporting data governance methodologies, talent training, and localized service support are equally essential. For the Hong Kong market, FanRuan will continue to advance its digital talent certification system, helping enterprises reduce dependence on individual technical staff experience, enabling more business and management personnel to acquire data analytics capabilities, and gradually fostering an organizational culture where “everyone can understand data and use data for decision-making.”

As Hong Kong enterprises accelerate their digital transformation, the key to successful AI adoption will be how to transform data scattered across different systems, departments, and processes into decision-making assets trusted by management and routinely used by frontline business operations. Moving forward, FanRuan will continue to center on the “Governance First, Intelligence Second” core pathway, helping Hong Kong enterprises lay a solid data foundation for the AI era and establish more robust decision-making advantages.
Hashtag: #FanRuan #DataGovernance #ArtificialIntelligence #BusinessIntelligence #DoraDataAgent #DigitalTransformation #HongKongTech #TrustedAI #DataAnalytics

https://www.fanruan.com/en
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About FanRuan Software

As the leading all-in-one Data Analytics & BI platform, FanRuan empowers enterprises worldwide to bridge the gap between raw data and strategic action. Founded in 2006, FanRuan serves over 43,000 clients globally through 50 strategic branches, combining international leadership with localized expertise to help organizations transform information into lasting business value. With over 5 million daily users across industries including finance, construction, manufacturing and retail, FanRuan provides the future-ready foundation for sustainable growth. For more information, please visit https://www.fanruan.com/en

The agreements involve SK Telecom, SK Hynix, Naver, Doosan Group, LG Group, Hyundai Motor Group and continued discussions with Samsung Electronics, linking Nvidia’s graphics processors, AI factory architecture and robotics platforms with South Korea’s strengths in memory chips, telecoms, manufacturing, cloud services and industrial automation.

The deals were unveiled during Nvidia chief executive Jensen Huang’s Seoul visit, which has underlined how South Korea is moving from being a supplier of critical memory chips to a broader AI infrastructure hub. The push comes as governments and large companies seek sovereign computing capacity, tighter control over data, and dedicated facilities capable of training and running advanced AI models.

SK Telecom plans to build a gigawatt-scale AI cloud in South Korea using Nvidia’s DSX platform, with the first AI factory expected to come online in 2027. The infrastructure is designed to support enterprise AI, robotics, industrial automation and agentic AI services, using SK Telecom’s network, data centre and corporate technology base.

Naver, one of South Korea’s leading internet and cloud companies, is expanding its sovereign AI infrastructure with Nvidia, starting with 55 megawatts of capacity and a plan to move towards gigawatt scale. The collaboration is aimed at serving businesses, public-sector users and industries seeking locally controlled AI platforms.

SK Hynix, already a key supplier of high-bandwidth memory for Nvidia’s AI accelerators, has entered a multi-year technology partnership to develop next-generation memory for global AI data centres. The agreement strengthens the role of high-bandwidth memory as one of the most important bottlenecks in the AI hardware supply chain, with demand rising sharply as large models require faster data movement between processors and memory.

Samsung Electronics remains part of the wider conversation around next-generation foundry and memory cooperation. Its semiconductor leadership held talks with Nvidia on advanced chip manufacturing and future high-bandwidth memory, including technologies beyond the current HBM4 generation. Samsung is also involved in manufacturing AI accelerator chips for other customers, keeping it central to Nvidia’s broader supply chain calculations even as SK Hynix maintains a strong position in premium memory.

Doosan Group’s cooperation with Nvidia extends the agreements beyond data centres into physical AI. Doosan Robotics is working with Nvidia’s simulation, robotics and on-device AI platforms to develop an agentic robot operating system, while Doosan Enerbility is expected to support power infrastructure for AI factories. Doosan Corporation’s electronics materials unit is also positioned to support next-generation data centre hardware through advanced materials used in AI accelerators.

LG Group is working with Nvidia on an AI factory focused on physical AI, mobility and data centre technologies. The partnership is expected to support LG’s work in robotics, autonomous driving, smart manufacturing and GPU cloud services, giving the conglomerate a platform for applying AI across consumer electronics, industrial systems and vehicle technologies.

Hyundai Motor Group’s cooperation with Nvidia is centred on mobility, manufacturing and robotics, including support for Hyundai’s AI Valley project in Saemangeum. The group’s ownership of Boston Dynamics gives it a strong position in humanoid and industrial robotics, while Nvidia’s platforms can support simulation, model training and factory deployment.

South Korea’s national AI strategy gives the corporate agreements wider significance. The country had already announced plans to secure more than 260,000 Nvidia GPUs, with more than 50,000 intended for public AI infrastructure and the rest allocated to major companies including Samsung, SK Group, Hyundai Motor Group and Naver. The latest agreements suggest that those commitments are moving into more defined industrial projects.

The expansion also reflects a shift in Nvidia’s business model. The company is no longer selling chips only as components; it is promoting full-stack AI factories that combine processors, networking, software, reference architecture and operations. That approach gives Nvidia deeper influence over how data centres are designed and operated, while offering partners faster deployment at a time when AI capacity remains constrained.

South Korea’s Science and ICT Ministry is also seeking priority access to Nvidia’s Vera Rubin GPUs, amid expectations that next-generation chip supply could face delays. The effort shows how advanced AI processors have become strategic assets for countries competing in model development, cloud infrastructure and industrial automation.

The agreements carry risks as well as opportunity. AI factories require vast power supplies, expensive cooling systems and long-term commitments from corporate customers. Heavy dependence on one US chip supplier may also raise questions over supply security and bargaining power, even for a country with world-class semiconductor companies.

For Nvidia, the South Korean partnerships strengthen memory access, broaden its AI factory customer base and create new demand in robotics, cloud services and industrial AI. For South Korean companies, the deals offer a faster route into high-value AI infrastructure at a time when global competition is shifting from model development to the computing systems needed to run them at scale.

The hiring programme would expand the workforce of One 97 Communications, Paytm’s parent, by about 10 per cent from a base of roughly 40,000 employees. The company is also expected to reduce about 1 per cent of its staff, or nearly 400 employees, as it removes overlapping functions and redirects resources towards areas tied to revenue growth, automation and financial services distribution.

The planned additions will run through March 2027 and cover product, technology, artificial intelligence and senior leadership roles. Paytm has already added more than 800 employees over the past two months and is in the process of recruiting the next tranche as it widens its merchant network and builds AI-led tools across its platform.

The move reflects a broader recalibration inside the Noida-based fintech company after two years of regulatory pressure, cost discipline and business restructuring. Paytm is seeking to convert its large base of users and merchants into higher-value customers for loans, investments, insurance and other financial products, while keeping a tight watch on employee costs and operating expenses.

Chief Executive Officer Vijay Shekhar Sharma has been working to rebuild confidence after the Reserve Bank of India imposed severe restrictions on Paytm Payments Bank in 2024 and later cancelled the licence of the independently held affiliate in April 2026. One 97 Communications holds 49 per cent in the payments bank, while Sharma owns the remaining 51 per cent.

The banking affiliate’s closure has continued to shape staffing decisions. Most of Paytm Payments Bank’s employees have already exited over the past two years, with some absorbed into other parts of the fintech group. The remaining few hundred employees at the bank are expected to leave as the winding-down process advances.

Paytm’s latest hiring plan comes after a year in which the company sharply reduced headcount. Average on-roll employees fell from 43,960 in FY24 to 39,368 in FY25, a decline of about 4,600 people. A large portion of the workforce remains tied to sales, underlining the importance of merchant acquisition and field distribution in Paytm’s model.

The company’s restructuring has coincided with an improvement in profitability. Paytm posted four consecutive profitable quarters and reported its first full-year profit since listing, with FY26 net profit of about ₹552 crore compared with a loss of ₹663 crore in FY25. Revenue for FY26 rose to about ₹9,291 crore from ₹7,625 crore a year earlier.

For the March 2026 quarter, One 97 Communications reported a consolidated net profit of about ₹184 crore, compared with a loss of about ₹540 crore in the year-earlier period. Revenue from operations rose 18.4 per cent year-on-year to ₹2,264 crore, supported by payments services and financial services distribution.

The improved performance has given Paytm more room to invest in growth areas, but the company is still balancing expansion with caution. Its shares have gained around 7 per cent over the past year, though they remain more than 50 per cent below the 2021 initial public offering price, a reminder of investor concerns over profitability, regulation and the durability of its business model.

Artificial intelligence has become central to Paytm’s operating strategy. The company has used automation to reduce repetitive work in customer support, risk management, merchant servicing and internal processes. The next phase appears focused less on replacing headcount across the board and more on redeploying resources towards AI-enabled products, data-driven lending, fraud control and personalised financial offerings.

That shift mirrors a wider trend in the technology and fintech sectors, where companies are cutting roles in legacy or routine functions while hiring for engineering, machine learning, product design, compliance technology and platform operations. For Paytm, the challenge is sharper because its business relies on both software capability and a large physical merchant network.

The company began in 2010 as a mobile recharge platform before expanding into wallets, QR-code payments, Soundbox devices, payment gateways and financial services. Its growth accelerated after the 2016 currency note withdrawal pushed millions of merchants and consumers towards digital payments.