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4 Major Advantages and 3 Key Challenges for Implementing AI in Businesses
"Artificial Intelligence (AI) is the electricity of the new era; no modern industry will remain untouched by AI in the future."--Former CEO of Taiwan AI Academy, Chen Sheng-Wei.
The emergence of OpenAI’s ChatGPT in the winter of 2022, initiated a new era of Generative AI. Following this breakthrough, in March 2024, the video-generative AI model Sora was launched, capable of generating highly realistic videos from just a text prompt. Then, in May of the same year, the latest model, GPT-4o, was released. This model can "understand" human tones and expressions, providing real-time interpretation and engaging in smooth conversations in different languages, much like the real-life version of the movie "Her."
AI is no longer just following human instructions; it can now create unique images, text, music, and conversations on its own. But how exactly is AI changing the way industries operate? What challenges do businesses face? And are the solutions to overcoming these challenges? This article explains it all.
AI is already revolutionizing the way businesses operate. Both McKinsey & Company (McKinsey) and the Artificial Intelligence Foundation (AIF) indicate that Generative AI tools significantly lower the barrier for AI adoption. More than half of the companies worldwide have already begun implementing AI internally. The major applications currently in use include content generation, behavior prediction, recommendation engines, and large language models (LLM).
Here’s how it’s transforming various sectors:
According to McKinsey's latest "2024 McKinsey Taiwan Banking GenAI Survey" published in May this year, the global banking industry has the potential to unlock an annual value of USD 200 billion to 340 billion by adopting Generative AI. In Taiwan alone, this technology could nearly double annual profits for the banking sector, increasing from NT$36 to 60 billion. Banks can utilize monthly credit card records to predict when customers are likely to travel, enabling them to time their promotions of credit card offers effectively. Additionally, AI ChatBots can handle simple customer service issues, freeing up human resources to concentrate on enhancing sales efforts.
Japanese convenience store chain 7-Eleven announced plans to use Generative AI to create new product images and text starting this spring. This innovation could reduce the time needed to develop new products by 90%, allowing employees to focus more on product improvements.
Generative AI can generate optimized protein sequences, accelerating the development of new drugs.
In the tech industry, the startup Cognition has developed the virtual engineer Devin AI, which can not only provide programming suggestions but also independently complete entire software development projects.
AI, without exception, will play a pivotal role in cross-industrial business transformations, akin to the criticality of water, gas, electricity, internet and telecommunications in our daily lives today.
Here are the four representative advantages that businesses can gain through the adoption of AI.
Despite the many advantages, businesses still face numerous challenges in the journey to AI implementation.
Implementing AI isn't just about digitizing data; the biggest concern for businesses is addressing the complexity of their owned data.
The data design within a company varies across departments, and likewise the formats and systems used for storage may differ as well. Therefore, it is necessary to standardize data formats and ensure complete data storage without omissions. Otherwise, computers and machines won't be able to interpret and learn correctly. However, the lack of data processing talent within the company is one of the most common challenges.
Companies require personnel with AI development skills, including model training and prompt engineering, to develop products that meet internal needs. Most companies may need to invest incrementally in AI training or hire relevant talent.
This challenge prompts many companies to currently opt for ready-made tools like ChatGPT, Midjourney, or to integrate external APIs (Application Programming Interfaces), as noted by the AIF.
AI requires significant initial investment in manpower and equipment costs. System conversion not only takes time but also requires substantial funds for subsequent training and managing Generative AI models. Moreover, integrating with the company's existing systems and combining multiple different AI solutions is also a complex process.
Starting an AI project involves numerous cumbersome processes, including problem identification, data collection, model training, and going live. Therefore, companies wanting to implement AI solutions with success must first clearly understand what they want AI to achieve, what problems they want to solve, and whether AI is the best solution. Implementing AI should be driven by clear objectives and strategic benefits, not merely for the sake of adoption.
Once the direction and objectives are clear, companies can select suitable vendors and technical consultants to accelerate the process. According to the "2023 Taiwan Industry AI Survey" by the AIF, up to 70% of manufacturing, government agencies, and other enterprises believe that less than 25% of their employees have sufficient basic AI knowledge.
By cooperating with external vendors and consultants, companies can receive help in later stages of maintenance, employee training, and can smoothly transition through the conversion period.
Going Cloud is a one-stop provider of cloud services, data management, and AI solutions, helping clients leverage advanced IT structures to drive business growth through data empowerment. With over 15 years of technical experience as part of the KKCompany Technologies group, our team of experts provides support for businesses across diverse industries and at all levels of AI maturity. This includes assisting with data cleansing and integration, whether structured or unstructured, applying AI solutions such as chatbots, content generation, and recommendation engines, and operationalizing a tailored AI system that aligns with business needs.
At Going Cloud, we leverage our AI/ML expertise to support customers in achieving seamless AI adoption and realizing their business objectives. Explore use cases that have led to successful AI implementations and applications:
Furthermore, Going Cloud’s solutions can be deployed in the customer’s environment, allowing businesses to retain full data ownership while ensuring security, flexibility, and scalability according to usage scenarios and needs.
The benefits of AI for businesses have been well-documented, and its value will only continue to grow. With rapid technological advancements and widespread commercial adoption, AI will soon become integral to every industry.
However, as businesses begin their AI journey, they often face three major challenges: finding talent, developing AI skills, and managing conversion costs. Each industry and business operates in a unique environment with specific challenges. Evaluating internal needs and data conditions is crucial, but partnering with specialized experts can provide additional clarity on technical architecture, optimal AI model selection, and implementation. This kind of partnership is also crucial to reduce errors, accelerate the process, and significantly increase the success rate of AI integration.