[Edaily Reporter Yun Junghoon ]KTCorporation(030200)is accelerating the advancement of its B2B AX (AI Transformation) business by securing four of South Korea’s five major commercial banks as clients, in line with the growing trend toward the full-scale adoption of artificial intelligence (AI). The core of its strategy is to become a “Financial AX Partner” that goes beyond simply implementing technology to help client companies directly operate and internalize AI.

On the morning of the 24th, KTCorporation held a Financial AX Study session at the Four Seasons Hotel in Gwanghwamun, Seoul, where it unveiled AI transformation strategies for the financial sector and key AX implementation case studies.

“Beyond Simple Implementation to Full Internalization”… KTCorporation Secures 22 Financial AX Contracts in the First Half

Park Cheol-woo, Senior Vice President in charge of the Financial Business at KTCorporation’s Enterprise Division, who led the presentation that day, stated that KTCorporation is targeting the financial B2B market with its “End-to-End AX” strategy, which encompasses everything from strategy formulation to implementation, operation, enhancement, and expansion.

KTCorporation established a “5-Layer AX Full Stack”—a five-stage execution framework that organically links the entire process from initial planning to implementation, operation, internalization, and expansion—by analyzing financial institutions’ operations and data during the early planning phase and validating business feasibility through rapid prototyping.

In the initial phase, KTCorporation leads the implementation; in the expansion phase, it promotes joint development; and in the internalization phase, it provides validation and coaching to enable client companies to operate the system independently.

Executive Vice President Park emphasized, “While interest used to focus on comparing the performance of AI models—such as which large language model (LLM) was superior—visible business outcomes, such as cost reductions and productivity gains, have now become paramount.” He added, “AX in the financial sector is also rapidly shifting from mere AI implementation to a phase where operations and internalization lead to tangible business results.”

Widespread Chonbang Adoption Across Banking, Insurance, and Credit Card Sectors… Creating Leading Examples Such as the “Insurance Sales Assistant”

Leveraging its existing customer base, KTCorporation secured a total of 22 AX projects in the financial sector alone during the first half of this year. This represents a 250% year-over-year increase in the number of projects.

For Bank A, KT built an “Integrated AICC” platform that applies AI to its existing agent-centric contact center. The platform goes beyond agent knowledge search, response recommendations, and post-call summarization and categorization to implement the “Human-Like AI” stage, where AI agents perform tasks independently. For Bank C, KT supported the establishment of an enterprise-wide integrated AI platform and an AI agent system based on a “multi-agent” structure.

In collaboration with Insurance Company B, we developed a “Sales Assistant” that applies generative AI to the consultation process—a first in the industry. The AI analyzes the know-how of veteran insurance agents and a vast database of policy terms and underwriting guidelines in real time to recommend customized insurance plans.

For one credit card company, we built an AI data platform optimized for LLM use via an integrated data platform, along with “AI LLM Ops” to ensure the stable deployment and operation of AI.

Overhauling

the Data Framework… Promoting the Assetization of Knowledge Based on ‘Data4AI’

While carrying out various AX projects, KTCorporation identified a gap between proof-of-concept (PoC) and actual business results. The primary reason for the delayed adoption of AX in the financial sector was not the performance of AI models, but rather structural issues stemming from the inability to properly utilize dispersed unstructured data (such as documents, policy terms, regulations, and consultation histories).

In response, KTCorporation is implementing “Data4AI,” an integrated data service that helps AI understand and utilize data seamlessly, and “K-Ontology,” a knowledge model that links business processes and data into a single semantic framework.

In an actual insurance AX project, policy terms and product information were restructured based on meaning to build a knowledge DB that AI can reason from. Through the so-called “assetization of knowledge”—converting sales know-how, which had previously been limited to individual experience, into an asset for the entire organization—the company automated customer analysis and product recommendations, significantly boosting operational capabilities. Additionally, by implementing data governance, security, and regulatory compliance frameworks, the company ensured the high levels of reliability and stability required by the financial sector.

■ “Differentiating from

the Global Big 4 Consulting Firms”…Pooling Group Capabilities

KTCorporation aims to position itself as a specialized AX business company that differentiates itself from existing global strategic consulting firms.

To this end, it has consolidated the AI, cloud, and IT capabilities of its group companies—including KTCorporation itself, KT Cloud, KT DS, KT IS, and KTCORPORATION. Currently, among its approximately 4,000-strong B2B organization, about 800 are dedicated AX specialists who are directly engaged in the field as part of the “FDE (Forward Deployed Engineer)” strategy.

In terms of technology implementation, the company flexibly combines various technologies—including those from Microsoft (MS), AWS, Google Cloud, and Anthropic—tailored to each customer’s specific situation.

Kim Young-min, Executive Vice President and Head of the AX Engineering Division within the AX Business Division of KTCorporation, stated, “What sets KTCorporation AX apart is our ability to redesign workflows alongside our customers and define the necessary tasks together.” He added, “We will not stop at simply implementing requirements; instead, we will execute projects by continuously refining our direction in collaboration with customers to achieve optimal results.”