AX Strategy
News and commentary on direction, organization, and investment decisions in enterprise AI transformation.
25 articles
제약 AX의 마지막 관문은 성능이 아니라 운영 통제
제약 산업의 AI 전환을 다룬 8회 기획 연재가 마지막 관문으로 운영 거버넌스와 성과 증명을 짚었습니다. 에이전트가 규제 영역으로 확산되는 순간 관리 대상이 성능에서 통제로 옮겨간다는 진단입니다.
Gartner Survey: Fewer Than a Quarter of Enterprises Have Scaled AI Across Multiple Business Units
A Gartner survey found that fewer than a quarter of enterprises have successfully scaled AI across multiple business units, yet 85% of tech leaders plan to increase AI investment next year. Companies that generated returns shared two disciplines: measurement and knowing when to stop.
What AI Engineers Need Isn't New Knowledge, But Erasing Old Judgment
"Essential Practical Knowledge Every Junior AI Engineer Must Know" (by Kim Tae-heon, Hanbit Media), published in late July, argues that engineers should first erase ingrained faulty judgment rather than add new knowledge. It offers clues for rethinking AX workforce standards and operating procedures.
Building Software In-House Instead of Buying It — What McKinsey's Survey Reveals About the Cost Math of Agentic AI
A McKinsey survey of more than 1,700 employees found that nearly a third of respondents have given up purchasing software capabilities because they can now build them in-house. While four out of five reported productivity gains, the share reporting cost savings from AI stayed flat year over year.
A Quarter of AI Pilots Fail to Scale — Infosys Survey of 1,000 Executives
In a survey of over 1,000 senior executives across industries, Infosys found that 72% of respondents scaled less than a quarter of their AI pilots, while two-thirds struggled to measure the ROI AI generated.
Factories Aren't Run by Chatbots — The Four-Layer Sequence Behind China's Manufacturing AX
CEO Park Ji-min's column on China's manufacturing AX defines AI transformation not as installing a model but as connecting four layers: physical infrastructure, data, operational software, and governance. Cases from Sany Heavy Industry, Haier, and CNPC all share the same sequence — standards came before models.
AI Adoption Should Be Scoped by Workflow, Not Feature — A Pharma AX Approach That Splits Human and AI Roles into Three Layers
Drawing on a pharmaceutical industry proposal, this piece argues that AI transformation should be scoped around end-to-end work workflows rather than individual features, dividing human and AI roles into AI-led, collaborative, and human-led layers, and examines the implications for Korean companies.
500 AI Factories, 2.8% Enterprise-Wide Use: Manufacturing AI's Bottleneck Isn't the Model, It's Data Circulation on the Floor
With the government's June 'Manufacturing AI 2030 Strategy' targeting 500 AI factories by 2030, NIA data shows that 83.5% of manufacturers using AI confined it to department or project-level use, while only 2.8% achieved enterprise-wide adoption. This piece examines why companies should check equipment connectivity, data quality, and pre-implementation baselines before choosing a solution.
The Age of AI Transformation: Signals Enterprises Must Watch in AI-Exposed Industries
A statistic cited in a National Assembly member's special contribution shows that youth employment fell by more than 210,000 in the three years since ChatGPT's emergence, with 98.6% of that decline concentrated in AI-exposed industries. This figure carries implications not only for national policy debate but also for how enterprises design their AX transformation strategies.
AI Readiness Splits SaaS Earnings: What It Means for Companies That Buy Software
On the 7th (local time), software companies' earnings and stock prices on the New York Stock Exchange diverged sharply based on their AI readiness. For companies that purchase software, this is less market news than a vendor checklist item.
A Quarter of Companies Halted Projects Over Unexpected AI Costs
A survey of 396 companies by Mavvrik found that a quarter had delayed or canceled AI projects due to unexpected costs. The core issue isn't the model fees themselves, but the lack of visibility into where the spending is actually occurring.
Unauthorized Access by AI Agents: Deployment Companies Bear Oversight Responsibility, Not Criminal Liability
OpenAI and Anthropic disclosed cases of unauthorized system access by AI models during internal testing, sparking legal debate over accountability. Prosecuting the AI itself proves difficult, shifting focus to the oversight responsibility of the companies that built and deployed the models.
AI Tool Access: One-Third of Executives Say It's Sufficient, Only 19% of Junior Staff Agree
A survey of more than 2,600 white-collar workers by the Infosys Knowledge Institute found that over a third of senior executives said they always have the AI tools they need, compared to just 19% of junior employees. Perceptions of transformation goals were also split between executives and middle managers.
Even as Token Costs Surge, More Companies Expand AI Investment: What EY's Survey Reveals
An EY survey of 500 U.S. decision-makers at SVP level and above found that despite growing concern over AI token costs, 37% of companies are actually expanding the scope of their AI adoption, while only 15% chose to scale back.
Why Pohang Is Building a Data Center Cluster — Where KRW 2 Trillion and 20,000 GPUs Are Headed
Pohang, North Gyeongsang Province, broke ground on an AI data center at Gwangmyeong General Industrial Complex on July 20. We examine the questions this KRW 2 trillion project, initially built to house 20,000 GPUs, raises for manufacturing companies.
What Orchestro's '11x Faster Development' Case Really Shows: AX Means Redesigning Work Itself
Orchestro reported a 10.6x increase in software development productivity after its AI transformation. Regardless of the exact figures, the case points to a clear conclusion: AX is not about adopting tools, but about redefining the nature of work itself.
AI Talent Race Reaches Construction — What GS E&C's ChatGPT Enterprise Adoption Signals
GS E&C's adoption of ChatGPT Enterprise, a first among Korean construction firms, signals that AI transformation is no longer confined to IT and manufacturing. We examine what it means for a field-driven industry like construction to invest in AI talent development.
Does Starting With a Company-Wide AI Strategy Doom You? The Question Behind “AX Starts at the Edge”
Many companies begin AI adoption by drafting a sweeping company-wide strategy document. One YouTube video argues that this approach is what leads to failure; TECH2030 examines how that claim should be read.
Why Did Palantir Choose a CEO with a Background in Philosophy? The Judgment Criteria Needed Before AX
Palantir CEO Alex Karp's philosophy background has drawn attention. This piece examines the implication that establishing organizational judgment criteria must come before technology in AI transformation.
Ministry of Trade Financial Support for Mid-Sized Firms: 'DX Leap' Rebranded as 'AX Leap'—Applications Close August 14
In the second-half round of the 'Rising Leaders 300' program, the existing DX Leap category has been restructured into an AX Leap category. Applications for this program, which offers up to KRW 30 billion in loans per company along with preferential interest rates, close on August 14.
Why Walmart Sold Its In-House Delivery Algorithm to Outsiders: Implications for Korean Enterprise AX
At a moment when Walmart lost the top revenue spot to Amazon, reports that it sold its proprietary delivery algorithm externally have drawn attention. While the facts need verification, the underlying question—how to turn in-house AI capabilities into an asset—is worth reflecting on.
LG CNS's Earnings Surprise and “Physical AI Infrastructure”: A New Axis of Enterprise AX
LG CNS reportedly signed a large-scale physical AI infrastructure contract with LG Electronics, drawing attention alongside an earnings surprise. The figures warrant checking against the original source, but the emergence of “physical AI” as the middle layer of enterprise AX is worth watching in its own right.
From DX to AX: What the 'X+AI' Paradigm Shift Defining 2026 Really Means
AI Transformation (AX) is emerging as a defining theme across industries in 2026, moving beyond Digital Transformation (DX). It's worth examining the source material to understand whether this is merely a buzzword swap or a genuine shift in how organizations make decisions.
Warning: Manufacturing AX Risks Becoming a Big-Business-Only Game
The polarization problem in manufacturing AX is back in the spotlight. TECH2030 examines the warning that small and mid-sized manufacturers could fall further behind in AI transformation without support for education and GPU infrastructure.
Government's Strategy to Lead the Agentic AI Ecosystem: What Enterprise AX Teams Should Prepare For
The government is moving to seize early leadership in an execution-focused agentic AI ecosystem through initiatives such as a physical AI port strategy, privacy guidelines for public-sector AX, and securing GPU infrastructure. Here's what this means from an enterprise perspective.