AI technology is evolving at the speed of light. The emergence of generative AI, in particular, demands more than just technological innovation—it requires fundamental changes in management strategies and business models. We are entering an era of transformation comparable to how the Industrial Revolution completely transformed the artisanal society.
How should companies respond to this era of transformation? A lecture by Oh Soon-young, former head of KB Bank's Financial AI Center, at the HUNET CEO Forum 'Foresight Korea 2025' provides clear answers to this question. His presentation outlines the new business landscape that AI will create and details the strategies companies need to survive and thrive in this new world.
We now stand at the peak of AI's massive wave. Will we ride this wave into the future, or will we be swept away by it? Through Oh Soon-young's insightful lecture, we can find answers to this question.
AI: Moving Beyond Science Fiction
Imagine robots helping with housework, AI assistants understanding and responding to your words and actions, and smart devices monitoring your health in real-time. Just a few years ago, these scenes were distant future stories found only in science fiction movies. But now, they're becoming reality. AI is no longer just a data processor.
The emergence of 'spatial intelligence' means that AI can now understand and interact with our three-dimensional world. When you say "make the lighting brighter" in your living room, AI doesn't just execute the command—it considers the current time, external weather, and your activities to adjust to the most appropriate brightness. This is the power of spatial intelligence.
Even more remarkable is that humanoid robots are on the horizon. NVIDIA CEO Jensen Huang predicts practical humanoid robots will emerge within 2-3 years. This isn't mere speculation—companies like Boston Dynamics and Tesla are already accelerating their human-form robot development. Soon, we'll see robots working alongside humans in factories, hospitals, and even homes.
AI in Action: Real-World Transformations
These changes aren't limited to specific industries. The financial sector is already at the forefront of the AI revolution. Morgan Stanley's case vividly shows how AI can innovate business. Their AI assistant has evolved beyond a simple chatbot—it analyzes complex financial data to create investment reports, responds to customer inquiries at an expert level, and even suggests personalized investment strategies.
Perhaps most interesting is Morgan Stanley's 'Debrief' system. Can you imagine automatically recording and summarizing over a million meetings annually? Previously, this required significant time from high-level personnel. Now freed from these repetitive tasks, they can focus on more creative and strategic work. This represents a revolutionary change in optimizing human resources beyond simple efficiency improvements.
Nike's case demonstrates AI's potential in creative domains. Nike uses AI to design and develop products based on athlete data. According to Oh Soon-young, this process has reduced product design development from months to just hours.
Specifically, Nike inputs various data into their AI system, including athletes' movements, physical measurements, and performance data. The AI analyzes this data to suggest optimal designs. For example, it can generate customized shoe designs by analyzing a specific athlete's foot shape and running patterns.
This goes beyond simple task automation. AI can generate and evaluate thousands of design options instantly and might suggest innovative ideas that human designers haven't considered. This allows designers to focus on more creative aspects of their work.
Strategic Approach to AI Adoption
AI adoption isn't simply about implementing new technology—it's a major strategic decision.
Oh Soon-young presents key strategies for AI adoption:
Clear Goal Setting: A vague notion that "AI might be good to have" isn't enough. Companies need to clearly define what problems they want to solve and what effects they expect. This becomes an important criterion in determining necessary resources and personnel.
Data Preparation: AI grows on data. Without sufficient quality data, AI cannot function properly. He advises companies to check if they have the necessary internal data and, if not, start preparing it now. He also emphasizes the importance of converting historical data into AI-readable formats.
Establishing Collaborative Structures: AI projects aren't just for the technology team. They require cooperation between various departments, including business units, IT infrastructure teams, and data scientists. Business unit participation is particularly crucial—their knowledge and experience must be reflected in the AI system to create truly useful solutions.
Start with Pilot Projects: Don't try to implement on a large scale from the beginning. Start with smaller projects to verify effectiveness and increase organizational acceptance. Since each company's environment is different, going through the process of direct testing and verification is necessary.
Building AI Governance: Companies need to establish ethical and legal guidelines for AI use and ensure transparency and accountability in AI decision-making. The AI governance team should be separate from AI-related organizations, positioned similarly to an audit organization.
Real-World Challenges in AI Implementation
Anyone who has attempted to implement AI solutions in the field will deeply empathize with the concerns and difficulties mentioned by Oh Soon-young.
"Shouldn't we implement AI now?"
Projects that start with this simple question from management often face numerous obstacles. Field practitioners are well aware of how many challenges arise: executives hesitating before investment decisions, middle managers questioning "Do we really need to go this far?" and staff worrying "Won't this just create more work?" These concerns are far from trivial.
Cost optimization is a hot topic for many companies. Questions flood in: "How much will AI implementation cost?", "When can we expect to see results?", "What about our existing systems?" While it's easy to say ROI should be thoroughly evaluated, making large-scale investments in unproven technology is never simple.
Talent acquisition and development is another major challenge. Companies grapple with questions like "Where can we find AI experts?" and "Will our employees know how to use this?" Companies are engaged in fierce competition to recruit the few available AI experts while simultaneously wrestling with how to enhance existing employees' capabilities.
Integration with legacy systems is a headache for many companies. "How do we change a system we've used for over 10 years?", "How do we handle data compatibility?" How can you harmoniously integrate systems and data built up over years with new AI systems? This is a complex challenge that demands not just technical solutions but organizational culture changes.
Building New Competitive Advantages
What creates competitive advantage in the AI era? Oh Soon-young offers an unexpected answer: UI/UX. While AI technology's performance is important, the key lies in how easily and conveniently users can interact with it.
Another crucial point is the importance of AI literacy. This goes beyond technical ability to use AI—it's about understanding AI's possibilities and limitations and being able to utilize it effectively. This AI literacy will become a core competency for both companies and individuals in the future.
The introduction of AI will inevitably bring changes to work environments and job functions. However, this doesn't simply mean job losses. Rather, it's an opportunity to focus on more creative and valuable work by moving away from repetitive tasks.
Preparing for the AI Future
The key is preparing for these changes. Companies need to invest in employee retraining and job reassignment. They also need to improve employee perceptions of AI. It's important to create an organizational culture where AI is seen as a helpful partner rather than a threat.
AI is no longer optional—it's essential. However, successful AI adoption depends not on the technology itself but on how it's utilized and managed. Oh Soon-young's lecture provides both a big picture of the changes AI will bring and a practical roadmap for how companies should respond to these changes.
Moving forward, companies need to recognize AI not just as a tool but as a core element of a new business paradigm, and build appropriate strategies and organizational cultures accordingly. To become winners in the AI era, companies need technical preparation, organizational transformation, and, most importantly, learning how to work alongside AI. This is the core message Oh Soon-young aims to convey.
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