Language
Let AI Assistants pinpoint what you need, prep materials, and streamline your workflow
The aging of the population is a common issue in all countries around the world. A United Nations report states that by 2050, people over 65 will make up more than 16% of the global population, leading to a labor shortage crisis that will impact all industries.
Japan's Yoshinoya store in Nishi-Shinjuku was forced to close for 10 days last year, due to a staffing shortage. Such situations are expected to become increasingly common in the near future. According to a report by consulting firm Korn Ferry, the world is projected to face a talent shortage of over 85 million people by 2030, with artificial intelligence (AI) emerging as a key solution.
ChatGPT’s launch in the winter of 2022 marked the beginning of a new era in generative AI, and since then, such technologies have proven to significantly boost human work efficiency. For example, Japanese media outlet Nikkei Asia reported that an animation company recently adopted AI to handle highly repetitive tasks, reducing the time required to produce background art from seven days to just five minutes. This not only addresses labor shortages but also improves work quality.
At a conference in March this year (2024), AI expert Andrew Ng highlighted AI Agents as the year's standout trend. An AI agent, or AI assistant, is an autonomous system designed to achieve specific tasks through iterative reasoning and adaptation. By developing workflows in which multiple AI agents collaborate to simulate human thinking, we move closer to artificial general intelligence (AGI), where AI can autonomously handle increasingly complex tasks and potentially surpass human capabilities.
While it may take decades to fully realize AGI, advancements in machine learning, natural language processing, and content generation are already delivering prominent value in our daily lives. Moreover, AI is evolving from simple content generation to integrating planning, memory, and action capabilities. By mimicking human behavioral patterns, AI Assistants can accurately capture user needs, take proactive actions, and adjust outcomes based on the situation, functioning much like a real-life assistant.
Let’s explore various scenarios where Enterprise AI Assistants can be applied to modernize today’s business operations. For example, introducing AI-powered knowledge management is an excellent starting point for businesses across different sectors aiming to enhance operational efficiency and productivity.
Consider the corporate database of a technology company, which stores a vast array of information, including onboarding training for new hires, payment details, standard operating procedures (SOPs), security policies, product introduction, project information, meeting minutes, and more.
We often underestimate the amount of work required for “simple” tasks such as searching for specific information, creating documents or classifying and assigning tasks to appropriate departments. In reality however, these tasks can be much more complex and time-consuming than they appear, given the various sources employees need to reference in order to complete them.
On the other hand, the biggest challenge for enterprise knowledge management is consolidating and organizing the sheer volume of information accumulated over the years across various databases. Enterprise AI Assistants offer an effective solution to address these challenges and substantially save employees’ valuable time.
Not long ago, the primary source for obtaining information was through search engines, whether for external or internal queries. We are all familiar with the process of typing in a few seemingly relevant keywords and clicking through multiple pages, at times in vain.
Today, an AI Assistant, or more precisely an AI Chatbot, provides an alternative to search engines. Employees can use their natural language to ask questions in an intuitive way and receive instant and actionable responses with a source link where applicable. Additionally, AI Assistants leverage vector databases to understand user intentions and provide guided prompts to help users clearly articulate their needs. This solution is highly versatile, making it beneficial for enterprise-wide use, back-office operations, customer service, and more.
Document creation can be cumbersome due to all the manual steps involved. But it doesn’t have to stay that way! Let’s take a look at a product team in a manufacturing company. Whenever they get a request to create a specification document—whether for a new product or a revision—they typically start by searching for past samples, copying and pasting, modifying the content, adjusting the layout, and so on.
AI Assistants can streamline the majority of these processes, reducing the time spent on document creation potentially by up to 90%. This efficiency not only allows team members to focus on adding the final touches to the auto-generated content (as needed), but also helps ensure consistency in document creation, maintaining a uniform style and format across all specifications.
As companies grow, helpdesk queries multiply, especially during events like organizational changes or system upgrades. This influx can overwhelm staff, as managing numerous processes and setting priorities often slows down resolution times.
AI Assistants can automatically analyze, classify, and route these queries to the appropriate teams through a query-matching system. By integrating with existing ticketing systems or communication tools, this automation enhances efficiency and reduces the likelihood of human error, resulting in faster, more accurate query resolution.
For enterprises, AI operates like an experienced workplace expert, adept at coordinating logistics, swiftly identifying problems, proposing solutions, and executing them. Enterprise AI Assistants serve as companions to employees, significantly enhancing efficiency and enabling optimal resource allocation.
The implementation of AI is no longer a matter of if but how. Across all industries, the impact and significance of AI are poised to expand, as its adoption has become integral to the digital transformation journey and industrial advancement. Without it, gaining a competitive edge in the market will be increasingly difficult.
Enterprises can pursue AI transformation through three key approaches depending on their circumstances:
1. Hire in-house talent or reskill existing staff: If a company anticipates two to three AI projects annually, hiring data scientists and AI engineers makes sense. This allows for full control and flexibility to customize, integrate, and scale using internal resources. However, annual salary costs can accumulate without ongoing projects, so this route is best for companies fully committed to AI. Additionally, the high demand for data scientists can make finding the right candidate challenging. Reskilling existing talent is another valid option, but this transition requires a longer-term plan for effective resource allocation.
2. Buy off-the-shelf solutions: For companies without data scientists but willing to experiment with AI and data analysis, purchasing off-the-shelf solutions may be viable. However, prepackaged solutions may not exist for specific scenarios and often come with limitations concerning accuracy or flexibility for integration, given that these solutions are often generalized for broader use. While this option appears convenient, its feasibility and suitability should be carefully evaluated. Moreover, if integration or customization is needed, hiring a data scientist or engineer may become necessary.
3. Hire external consultants: For businesses looking to upgrade their platforms with tailored AI solutions, hiring experienced consultants may be the most efficient method. This approach is often cost-effective for one-off projects, considering the unique needs and challenges of every business and system environment.
Going Cloud prides itself on digital integration capabilities centered around AWS cloud, data, and AI technologies. We deliver tailored AI solutions with flexible large language model (LLM) options, leveraging pre-built modules that cover a wide range of use cases, including data management, chatbots, recommendations, forecasting, content generation, and more. Combined with the expertise of our AI/ML professionals, we enable fast and practical implementation of Enterprise AI Assistants.
In light of the aging global population, adopting AI Assistants as companions to employees is key to improving work efficiency, reducing labor costs, and increasing economic output. Regardless of the industry or region, this has become a critical issue that all businesses must address.