©2026 Business Next Media Corp. All Rights Reserved. No.102, Guangfu S. Rd., Da'an Dist., Taipei City 106, Taiwan
In 2024, a New Era of AI Unfolds: Knowledge Management and Employee Empowerment as the Decisive Keys to Enterprise Success.
The year 2023 witnessed an unprecedented surge in AI development, with the advent of ChatGPT underscoring the vast potential of AI technology. This ignited a fierce competition among tech giants in the AI arms race.
In the latter part of the year, major tech players strategically honed their AI focus on their respective domains, such as Google's concentration on enterprise applications, developers, and the smartphone ecosystem; Amazon's integration of AI in the enterprise cloud domain, and Meta's emphasis on social media, deploying more precise advertising through AI. In the broader landscape of the digital economy, the next pivotal battleground will be established on AI channels.
Simultaneously, Large Language Models (LLMs) showcased significant advancements in vision and interpretive capabilities. GPT-4 not only recognizes landmarks but also calculates consumption tax based on invoice content. AI applications are gradually becoming ingrained in daily life, demonstrating near-human capabilities in diverse fields. Google's recent unveiling of AlphaCode 2, surpassing 80% of programmers, highlights the impact of AI progress on software engineers.
The future trajectory involves AI models transitioning toward miniaturization, with large models disaggregating into smaller, lightweight counterparts—easier to deploy on terminal devices and with lower operational costs.
Strategic Incorporation of AI: How iKala do?
In the face of continuous advancements in AI technology, how should companies formulate effective AI strategies? Taking iKala as an example, let's explore how we strategically incorporate AI internally, adding value to existing business models and empowering internal staff for enhanced productivity.
Three years ago, iKala initiated a "Central Kitchen" model to manage all internal AI models. By collecting and integrating scattered internal and external public data for analytics, coupled with 140 in-house AI models applied to precision marketing and enterprise transformation, we provide different departments and enterprises with essential business insights.
These models specialize in discerning customer emotions, estimating ad values, detecting fan preferences—akin to the functions of listening, speaking, reading, and writing, each serving a unique purpose. This represents the future knowledge management model for companies—an internal "corporate AI brain," centrally managing AI models for operations and customer needs.
Innovations in Knowledge Management with AI Integration
Since the latter half of last year, there has been a noticeable increase in enterprise customer demands for knowledge management. Frequent queries such as "How should knowledge management be done?" In fact, iKala's AI influencer data marketing platform, KOL Radar, just serves as a practical application of knowledge management.
KOL Radar centrally provides globally sourced influencer data, helping enterprises identify genuinely influential influencers aligned with brand and product tones. Through real-time data updates via the data pipeline, closely integrating with social media trends, we achieve fully automated, real-time data analysis, providing enterprises with valuable insights. Simultaneously, we continue to optimize search methods, transitioning from keyword searches to natural language searches, fostering more natural interactions between users and products.
By analyzing historical data, we predict the future performance of influencers, combining generative AI with predictive AI to create powerful new applications. Traditionally, knowledge management was internal to large enterprises. Now, using generative AI with database technology, it can assist in making searches and interactions more flexible.
Advancements in AI Technology
Furthermore, we have developed an AI for automatic tagging, capable of categorizing diverse human knowledge categories on social platforms. When AI classifies these different areas of knowledge, we find it has the ability to exhaustively enumerate these knowledge categories.
In addition to automatic tagging, it can also generate new categories on its own, which is crucial inspiration for the database behind the development of the influencer search engine. Formerly, it took a lot of time and effort for humans to build new knowledge systems. Now, through supervised and unsupervised learning of AI, it can be done, and with changes in the external environment, AI can automatically adapt. This is the underlying technology we have developed, and in the future, improving, shrinking, and specializing language model efficiency will be key technologies we continuously develop.
In the era of significant AI advancements, businesses should concentrate on three key aspects when formulating AI strategies: a robust data strategy, the internal and external value AI contributes to the enterprise, and treating AI as a utility like electricity. A solid data strategy, involving the collection, organization, and safeguarding of exclusive enterprise data, forms the bedrock of AI strategies. Identifying how AI enhances existing business models and empowers employee productivity is the subsequent step.
Recent experiments integrating AI within our organization revealed a remarkable 100% boost in productivity, halving the time required for AI development projects and increasing software update frequency from bi-weekly to weekly. Regarding cloud and edge computing power, adopting a hybrid approach for an optimal computing power mix is recommended, treating AI as an indispensable utility in shaping business strategies.
Future Trends and Challenges in AI Development
Looking into 2024, the future of AI development centers around trust, user experience, and business models. As AI becomes more ubiquitous, concerns regarding black-box scenarios escalate, prompting a surge in research on AI interpretability.
The recent approval of the Artificial Intelligence Act by the European Union underscores the need for global AI regulation, signifying rising operational costs for businesses worldwide. Navigating AI compliance will pose both a significant challenge and opportunity, requiring a blend of technical expertise and legal adherence. User experience considerations persist as AI applications diversify, with continual market exploration to identify widely embraced applications.
In the realm of business models, intensified competition accompanies the growing affordability of AI technology. I strongly advise businesses to fortify data protection, as data emerges as a unique and enduring competitive advantage.
©2026 Business Next Media Corp. All Rights Reserved. No.102, Guangfu S. Rd., Da'an Dist., Taipei City 106, Taiwan