According to the report “Artificial Intelligence Market Forecast, 2022-2029” by Fortune Business Insights™, the global AI technology market size is predicted to increase from 387.45 billion USD in 2022 to 1,394.30 billion USD in 2029 with a compound annual growth rate (CAGR) of 20.1%. The appeal of AI is obvious. This technology is applied to many areas of life, including business, and brings many significant achievements such as improving performance, predicting, automating processes, recognizing and managing diverse data of text, images, sounds, etc. 

What Companies Need to Know Before Investing in AI

This appeal has led many businesses to want to invest in AI or add AI technology to their business processes. However, this is a difficult problem if AI has never been a part of your company before. It is difficult to determine exactly what type of AI your company should invest in or adopt, where it should be applied, the potential benefits and potential risks of using AI. Or to put it more simply: What value will AI create for the company?

To answer this question, you need to clarify the following:

• Does your company really need AI technology?
• Choose a task as the starting point of your AI project
• Identify additional data and systems required to implement AI technology
• Adjust expectations appropriately
• Don't Rush to Enterprise-Wide AI Deployment
• Assess whether human resources skills are sufficient to sustain AI
• Consider the return and cost of investment

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Does your company really need AI technology?

“Does your company really need AI technology?”. “Why do you think this investment in AI is worth it?” are the first questions you need to answer. That means you have noticed the difficulties in your company’s operations and know the source of those problems. For example: redundancy in specific tasks, overload of operating systems, bottlenecks in operating processes… These are the problems you are trying to solve or improve to increase operational efficiency and competitive advantage. 

What value will AI bring to your company?

AI projects are often deployed to address process pain points, which can have a significant impact on costs, revenue streams, or resource allocation… and ultimately impact the bottom line you want to improve.

Different forms of AI provide different values. Common values ​​that many businesses apply include:

• Assist or replace humans in performing time-consuming and labor-intensive activities, such as reading extensive documentation to categorize actionable items.
• Support workflows and activities that require intensive image scanning.
• Speech analytics to improve efficiency or enhance workflows, such as speech analytics to help route customer support.
• Quite similar to the human brain, AI technology can base on data to predict future trends, improve the accuracy of predictions, and has been applied in many industries such as insurance, finance, marketing, and even agriculture....

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Choose a task as the starting point of your AI project

AI is typically task-oriented, not project-oriented. To be clear, an AI project is typically initiated to accomplish a task that will add new value, deliver new efficiencies, and become a part of the company’s long-term operations, rather than deploying AI just to participate in a short-term project. So, for your company’s first AI experiment, identify a high-value, data-driven task for the AI.

Choose a task as the starting point of your AI project

Here is an example of an AI application in healthcare: The task of identifying patients who may be in the “high risk of falling” group. This is a valuable task because it is difficult for medical staff to monitor all patients 24/7 to provide timely emergency care in case of a patient falling, leading to injury, more complicated care, and even legal implications. Therefore, the AI ​​project will study the patient’s medical data to identify the high risk group, flagging this group of patients when they are admitted to inpatient care. As a result, the medical team can allocate resources to pay more attention to this group of patients, adding additional preventive procedures to reduce the risk of falling for this group of patients. 

Identify additional data and systems needed to implement AI

In an AI project, the results, analysis, and predictions of AI are the outputs, while data is the input. Therefore, good data is the lifeblood of a successful AI project.

Before implementing an AI project, you need to investigate, collect, synthesize and verify all data related to that project. Missing or incorrect data will affect AI's judgment, giving wrong results. On the contrary, good data sources are the first basis for hoping for a successful AI project.

After collecting and validating the data, you need to check if there are any restrictions on the use of that data, such as whether the data format is compatible for AI to read, privacy regulations, data usage rules such as only using the data provided or can get more data from external sources... This step is to ensure that the AI ​​can definitely read and analyze its task data area, and not analyze too much or too little information.

Once you have identified the data that the AI ​​will process, you need to ensure that the AI ​​output can be integrated with your company’s existing systems to achieve its goals. If it cannot be integrated, do any system changes or additions need to be made? This step requires IT experts to research and implement. 

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Adjust expectations appropriately

AI is a smart and powerful technology that brings about huge efficiencies, but it is not magic. 

How well you achieve your goals depends on a lot of factors: the type of AI, the method of implementing AI, the data you have available, the level of human resources implementing the technology, other resources related to the project and the tasks you are trying to focus on, all can determine the accuracy rate and return on investment. 

Therefore, it is important to understand the type of AI you are implementing and the results that will be used to estimate the impact on your bottom line.

Don't Rush to Enterprise-Wide AI Deployment

Just because AI works well for one task doesn’t mean it will work well for others. Plus, not every activity in a company needs AI. Insisting on adding AI to areas where it’s not needed can be a waste of resources, costly, and even disruptive or inefficient. Consider the second caveat: pick a task as the starting point for your AI project, not a project and then add AI.

Read more: EDUTO's AI Library

Assess whether human resources skills are sufficient to sustain AI

AI is an intelligent technology. However, as a technology, AI still needs to be controlled, monitored and tested regularly to avoid errors and achieve optimal efficiency. 

Just as processes evolve and change over time, so does the data needed to drive an AI model, which can change the effectiveness or accuracy of the AI. Therefore, AI implementations need to be re-optimized over time. This requires a combination of data engineers, data scientists, and IT staff to keep the system running smoothly and efficiently. 

Therefore, you need to consider whether the current company's human resources are sufficient in number and capacity to operate AI. Investment in human resources is one of the decisive criteria for the success or failure of an AI project.

Consider the benefits and costs of investing in AI technology

Many people who are new to AI technology often make the mistake of deifying AI, thinking that AI has the ability to make highly accurate decisions, so they decide to invest in AI instead of high-quality human resources. However, the reality is that AI is still a technology that helps support decision making . 

It must be acknowledged that AI has many outstanding capabilities such as accurate image recognition, effective natural language processing (NLP), etc. However, AI initiatives will often enhance, optimize, and shorten stages of the process without often changing the final result. 

For example, let’s say you apply NLP to a process to improve document classification. This allows you to reduce the number of people working on this task, or focus resources on more knowledge-intensive tasks in the organization. The results are certainly positive, but the ROI is unclear.

Therefore, you need to carefully consider the cost issue, how effective AI will be in helping you achieve profits, and whether it is worth the investment.

With the right AI, companies can let the technology do the heavy lifting of routine-based processes or identify seemingly unknown patterns in massive data sets. But to get there, you need to figure out the right approach for your company. When you do, you may find new opportunities opening up all around you.

Investing in AI technology is an inevitable trend for businesses in the 4.0 era. AI is a powerful tool that helps businesses optimize, improve the efficiency of production and business operations, and increase competitive advantages in the market. However, you should not add AI to your company's processes just to follow the trend, but clearly define what value AI will bring to your company.