Why did Uplus invite AI startup representatives?

Business transformation through AI is now a global phenomenon, and LG U+ is at the forefront of this movement. As part of our strategic initiative, we recently had the privilege of engaging with CEOs from leading AI startups. This interaction was a testament to our commitment to staying ahead of industry trends and shaping the future of AI. As your editor, I was eager to share the insights from this meeting, providing you with a first-hand account of the discussions and outcomes.

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On the morning of Friday, April 24, 2020, the auditorium of U+ headquarters was the stage for a significant event- the 2nd quarter executive/manager workshop. This workshop, comprising several sessions, kicked off with a pivotal panel discussion. The discussion, featuring CEOs from three prominent AI startups, was a platform to gain deep insights into the AI industry trends and explore the strategic direction that U+ should adopt in this dynamic market.

• Genesis Lab CEO Youngbok Lee ('Genesis Lab' - 'ViewinterHR' service)
• Selectstar CEO Kim Seyeop ('Selectstar' - 'Cashmission')
• NationA CEO Yoo Soo-yeon ('NationA' - 'Neuroid')

There was also a special connection. The fact that U+ was the first B2B customer of Genesis Lab's AI video interview service 'ViewinterHR' and that the father of Selectstar CEO Kim Seyeop was an employee of U+ made it all the more remarkable, especially since LG Group has been a grateful customer who has been the first to request the introduction of new features of ViewinterHR since it was introduced to solve various problems in the recruitment process.

• Learn more about LG U+'s use of ViewinterHR: LG U+ Advanced Recruitment with Customized AI Competency Interviews!

The session started with three AI startup CEOs introducing their companies and businesses. Suppose you are curious about Genesis Lab's work culture or ViewinterHR. You have already read a lot about it on the ViewinterHR blog, so we will briefly introduce Selectstar and Nation's vision/mission and services below.

• SelectStar
  • Overview: AI startup that helps companies that want to collect and process data for AI training and improve the performance of their AI.
  • Mission: Selectstar is an SQL command that means "call all data." Our mission and name reflect our belief that our business will lead the development of the IT industry and benefit the world.
  • CashMission: a program that brings together multiple workers to label simple data
• NATIONAI
  • Overview: AI startup that operates Neuroid, a global software-as-a-service (SaaS) that enables anyone to create 3D content quickly and easily with generative AI technology.
  • Vision: We are driven by a revolutionary vision to revolutionize how humanity works, learns, and communicates. With a solid commitment to innovation, we strive to push the boundaries of what is possible and unleash humanity's unlimited potential.
  • Neuroid: SaaS software that creates 3D content of your choice in seconds.

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Panel discussion with AI startup CEO

The panel discussion was Q&A-driven, and we're sharing a summary of the stories we covered below.

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Q 01 : What were the expectations and visions of the CEO who started AI-related businesses relatively early? Did you initially expect the products you have today?

Learning about the expectations and visions of the founders who started AI-related businesses from the beginning was exciting. Their initial expectations and dreams are generally reflected in the current industry, and based on this, the industry is evolving according to changes in technology and the market.

Initial Expectations and Visions: Consistency of Technical Vision & Evolution of Vision and Reality

The founders started the business with the vision of utilizing AI to innovate in their respective industries from a technical perspective. Youngbok Lee, Seyeop Kim, and Suyeon Yoo all aimed to automate business processes and enhance data-driven decision-making through AI technology.

Initially, they aimed to provide essential AI solutions but gradually added more advanced features as the market demanded and technology evolved. Genesis Lab's ViewinterHR is another example, starting as a simple video interview solution and changing into a more complex system that uses AI to assist with analysis and evaluation.

Evolution of the business direction: Continuous sophistication of technology & expansion of the business model

The technical vision aligns with the initial direction and continues to evolve. The core elements of AI technology - machine learning models, algorithms, and data processing methods - are constantly being improved.

The business direction also constantly adds to the technical foundation we set at the beginning, meaning that we have not transitioned to a completely new business but are in the process of expanding and diversifying our existing business model.

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Q 02 : What challenges have you faced in AI-related business, and how did you overcome them?

Businesses based on AI technology have great potential, but they also face many challenges. There are three main business areas in AI: infrastructure, models, and applications, and the challenges in each area and the process of overcoming them stand out.

Significant Challenges of AI Business: Infrastructure/Model/Application 3 elements of AI Business

ⓐ Large-scale investment and technical foundation are required in the initial infrastructure business area, which requires huge capital and resources. Most startups find it difficult to secure this scale of investment.

ⓑ In the model development phase, it is essential to increase the accuracy and efficiency of the technology. Models have only recently started to gain ground in the market, and this is directly related to the speed of technological advancement.

Applications are the areas of AI technology applied to specific use cases. Many startups are active in this area, but gaining a competitive edge is difficult when the actual market is not sufficiently developed. 

How to overcome: Strengthening technology credibility >>> Close cooperation with customers

The biggest challenge has been to secure the credibility of our technology and add customers one by one. This process is time-consuming, and the initial results may need to be visible. Therefore, building trust by adjusting and improving our AI solution to each customer's needs is essential. This will gradually expand our customer base and increase the sustainability of the business.

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Q 03: What do you think your customers' real needs are, and how did you recognize them?

Identifying customers' real needs can be complex and challenging. Since customer needs are only sometimes precise, startups face many challenges due to unpredictable market reactions. To solve these problems, you must genuinely converse with your customers to understand their needs and expectations. 

The complexity of customer needs: the difference between surface and real needs and unconscious desires

In many cases, customers initially present surface needs or general pain points. However, these needs often mask more complex requirements that can only be uncovered through more profound conversations. And usually, customers need to recognize their needs themselves. Discovering what they want to gain is essential, especially if they have an "I'll just have to use it" attitude when adopting new technology.

Approaches to understanding customer needs: problem-solving-focused approach, case studies, and feedback

Talking to customers allows you to understand more about their day-to-day problems, technology expectations, and business goals. In this process, startups should go beyond simply pitching their product or service and look for ways to solve their problems. Solving customers' problems will naturally reveal their deepest needs.

Observing customer reactions through real-world use cases and asking for regular feedback is crucial to uncovering hidden needs. This feedback will help you continuously improve your product or service and contribute to customer satisfaction.

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Q 04: How do you get ideas for utilizing and implementing AI technology?

The first step in generating ideas for utilizing and implementing AI technology is to research and gather information on the latest technology trends. Startup founders use specialized sites to stay abreast of the latest trends and tools in AI and use this information to explore new possibilities.

Understand the real market and scale your idea.

Interacting with people who run other businesses is vital to gaining a first-hand understanding of market needs and problems. Together, they discuss how AI technology can be incorporated into their business direction and generate ideas that can be applied in practice. 

This approach is crucial for AI startups to push technological boundaries and become more competitive in the marketplace. This continuous research and dialogue process lays the foundation for realizing technology's tangible business value and developing innovative solutions to solve problems in various industries.

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Q 05 : Since data is essential when utilizing AI, how do the delegates feel about data?

As AI technology advances, data becomes increasingly important, so organizations are strengthening their data management and security strategies. This is a critical factor in driving business transformation through AI. Effective internalization of data will allow companies to innovate more securely and autonomously.

A data-driven AI strategy

The use of AI in the modern business environment is expanding rapidly, and data has become an essential resource in this process. Advances in large language models (LLMs) and generative AI technologies, in particular, require organizations to think about data in new ways. These technological advances aim to process and learn from vast amounts of data efficiently. How you manage your data can make or break the success of your AI strategy.

The trend toward internalizing data

With increased awareness of data security worldwide, many organizations want to manage their data in-house rather than rely on external service providers (such as SaaS). The growing importance of "data-centric AI" and "security-centric AI" among global tech companies, including Silicon Valley, reflects this shift. This movement, which started with large enterprises, will likely lead companies to minimise data leakage to the outside world and develop AI solutions that better leverage data internally.

Predicting and responding with caution

The delegates made some cautious predictions about how companies will manage and utilize data in the future. As data moves inside the enterprise, companies process and analyze more data to make AI more effective. This shift will also significantly impact companies' data governance structures and security protocols.

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Q 06: What are the most critical aspects of organizational culture and ways of working to incorporate AI effectively into your business?

Integrating AI technology into the business requires engaging all members of the organization. By normalizing the understanding and use of technology, you can maximize the business potential of AI technology. Stripe's story is an excellent example of how this approach can work across the organization.

The importance of company-wide engagement

Integrating AI technology into the business requires more than just the efforts of the technology department or IT team. Everyone needs to understand AI technology and be able to apply it to their work, which will increase AI literacy across the organization, reduce resistance to the technology, and uncover creative use cases.

The case of Stripe's LLM Explorer

Stripe, a global payments company, introduced the "LLM Explorer" program to familiarize employees with AI technology by using large language models (LLMs). The program allowed employees to incorporate AI into their daily work, increasing AI literacy across the organization. As with Stripe, when employees experience and use AI technology first-hand, they better understand how it can contribute to real business improvements.

Integrating AI technology with organizational culture

Successful adoption of AI technology is about the technology itself and making your culture and ways of working more AI-friendly. A culture that fosters a positive perception of AI within the organization and encourages experimental and innovative approaches is critical, as well as collaboration between different departments and teams to create opportunities for the broader use of AI technologies.

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Q 07: How do you see AI evolving in this era, and what should we do to prepare?

In conclusion, advances in AI technology offer many opportunities, but they also present challenges and risks. To address them, we need to be technologically, ethically, and socially prepared, which requires all stakeholders' active participation and collaboration.

Future developments in AI

Current and future advances in AI technology are primarily centred on the evolution of generative AI and AI Agents. These technologies will likely evolve to reduce direct human involvement, especially in clerical and other automatable tasks. They will replace routine office work, maximizing the efficiency of online work.

Economic and social impact

AI agents will benefit businesses economically through reduced labour costs and increased efficiency. However, it can also have negative social consequences, such as mass layoffs, making corporate social responsibility and ethical considerations crucial. The public sector and governments will have a role to play in devising practical responses to these changes and building the appropriate social consensus.

The role and need for humans.

Despite advances in technology, some tasks remain that only humans can perform. For example, AI can make decisions, but final approval will still rely on human judgment. In addition, offline interactions between humans, such as networking and social skills, are essential areas AI cannot replace. These unique human capabilities will be crucial assets in a future society that coexists with AI.

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Q 08: How did you feel after participating in the panel discussion? What suggestions do you have as an AI expert for LG Innotek to move forward as a digital innovation company?

The participating delegates commented that the panel discussions at this workshop were meaningful dialogues. These sessions were beneficial for exchanging thoughts between businesses and discussing practical innovations. Everyone hoped this type of discussion would happen more often and helpfully.

Recommendations for Uplus' Digital Transformation Strategy

• Strengthening global market presence: Participants suggested that Uplus needs to improve its competitiveness worldwide, which means the opportunity to build a successful business beyond the domestic market.
• Promote collaboration with technology startups: Technology startups need opportunities to grow through collaboration with large companies. Upless should collaborate with these startups to leverage each other's strengths and find ways to develop mutually.
• Foster substantive conversations: Events like this should encourage more substantive and concrete discussions, which can further promote digital transformation.
• Pursue common interests: Collaboration between large enterprises and startups should go beyond mere technical cooperation and aim to create synergies and pursue shared interests, which can ultimately benefit both parties.

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Uplus gained a better understanding of the AI startup ecosystem through this workshop and laid the groundwork for more practical discussions on utilizing AI technology. This was an opportunity for startups to gain a foothold for growth through collaboration with large companies, and it was also beneficial for large companies to understand the AI ecosystem. Such win-win collaborations will continue, sharing expertise in different fields.