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AI & Enterprise

AI app companies build in-house models as push grows; what next for Dokpamo overhaul?

More AI service companies are building in-house models to cope with the cost of using advanced AI models and to compete with large model developers. Legal AI startup Harvey has developed its Tenet model based on Moonshot\'s low-cost open-source Kimi K3. Coding AI Cursor is also accelerating its own model work and has launched its Origin code hosting platform. South Korea plans to revamp support for firms in the Dokpamo project from the third evaluation round.

AI & Enterprise

Analytics enters agentic era as AI delivers insights first

Salesforce global Tableau product management vice president Matthew Miller defined the current moment as an “agentic analytics” era in which insights reach users first. He said AI agents can understand needs, remember work patterns and adapt to organisational terminology. Miller outlined three stages: moving from passive to active analytics, from descriptive to advanced analysis, and from expert-only outputs to results anyone can understand. He also highlighted Tableau’s Knowledge Engine and Decision Engine.

AI & Enterprise

AX success depends on defining tasks; KPIs should focus on revenue and ROI, not adoption

Corporate AI transformation success depends on defining the problems to solve rather than simply adopting AI, UnboundLabDev CEO Cho Yong-min said at Salesforce Korea\'s Agentforce Digital Summit 2026 in Seoul. He said companies should translate goals into performance indicators such as revenue and return on investment and design tasks to improve top business outcomes. Panelists cited cases where generic AI tools saw low usage and projects stalled at proof-of-concept without clear strategy.