KT's survey of AI transformation (AX) in the financial and public sectors found that about 60 percent of financial institutions have moved beyond proof-of-concept (PoC) projects to applying AI to actual business operations. The figure was just 30 percent for public institutions, indicating that the pace of AX implementation in the financial sector was about twice as fast as in the public sector.
KT said Monday that it has published the "KT AX Insight Report," covering both the financial and public sectors, which analyzes the current status and key challenges of AX in these areas. The survey, conducted in July, included 200 employees from domestic banks, securities firms, insurance companies, and card issuers, as well as 200 employees from central government ministries, local governments, and public sector institutions, totaling 400 respondents.
Results showed that 59.5% of financial institutional investors have entered the AX execution phase, including PoC for AI utilization, partial operational application, or enterprise-wide expansion. In comparison, only 30% of public sector institutional investors had reached this stage, falling 29.5 percentage points behind their financial counterparts.
Barriers to overcome also varied by sector. For the financial industry, key challenges were identified as demonstrating ROI (return on investment) from AI investments and establishing trust in AI systems. In the public sector, major issues included creating a framework to link budgets with measurable outcomes and integrating data scattered across different institutions.
In response, KT categorized AX adoption levels into three stages: 'pre-consideration', 'PoC/partial operation', and 'enterprise-wide diffusion', offering tailored strategies for each stage. For the financial sector, KT proposed applying AI first to tasks that yield quick results, such as repetitive document processing and customer service, followed by expansion through ROI measurement, data standardization, and the establishment of AI governance.
For the public sector, KT suggested starting with lower-risk tasks like document creation and handling citizen complaints, then linking performance outcomes with budget allocations and expanding data standardization and integration across institutions. Another identified challenge was building governance using 'explainable AI' that allows verification of AI decision-making processes.
The report also includes real-world application cases. One financial institution built a generative AI platform based on a financial-specialized LLM (large language model) and an AI agent platform, which is now being used for document creation and credit assessment support. A government ministry implemented a subscription-based AICC (AI contact center) combining AI chatbots with voice recognition-based telephone counseling, reducing service gaps and enabling counselors to focus on specialized consultations.
Jang Dae-sung, director of KT Enterprise's division, said, "We hope that the AX Insight Report, created based on customer feedback, will assist B2B and B2G clients in successfully advancing their AI transformation initiatives."
in TECH
