Due to its ability to automate repetitive tasks and enhance decision-making capabilities, artificial intelligence has been gathering the attention of organizations around the world. Big corporations and universities used to be the only places where artificial intelligence could be used. Companies are seeing a decline in the price of artificial intelligence.
There is a reduction in the cost of hardware, software, and services related to the use of artificial intelligence. A decrease in the cost of computational resources is the main driver of the decline. The cost of computation used to be $200,000 per month in the 1950s, but has dropped in recent years due to cloud computing.
Business leaders can take advantage of declining artificial intelligence costs. Business leaders should carefully consider the challenges of the artificial intelligence domain. This idea can be explored in more detail below.
Major Challenges Faced While Investing In AI
Getting their hands on relevant datasets is one of the major challenges faced by business leaders. One by one, let's look at them
1. Data Quality
High-quality data is needed for the purpose of artificial intelligence. There's a lot of it. It is difficult to collect high- value data since most of the data in enterprises is not written.
The primary goal of the life cycle is to identify and collect raw data sources, transform them into high-quality formats, and build robust models.
It is necessary for business leaders to have a data strategy that can be used to integrate artificial intelligence into their business. It's not a good idea to invest in an artificial intelligence venture if there isn't relevant data.
2. Computationally Expensive
It can be difficult for small organizations to get access to the computational capacity needed to execute artificial intelligence. Depending on the complexity of the models, there is a high cost. It costs about $3 million a month for Openai to run the chatgppt.
To fulfill the computational needs, specialized and expensive hardware are needed.
Reducing the model size and memory footprint is one of the things that researchers are working on.
Capitalizing on AI Price Decline
Software, hardware, research, and investment are just some of the things that have improved in the last few years. Many challenges related to artificial intelligence have been overcome.
Accelerated Development of AI Applications
Most artificial intelligence tools offer free variations. The paid model is also reasonable. These applications are being used to increase efficiency, improve decision-making, automate repetitive tasks, and enhance customer experience.
The GPT-4 can assist users in generating new ideas and writing different types of content, such as product summaries, marketing copies, and blog posts.
There are many examples in other areas. Transfer learning techniques are being used for medical image classification Customer relationship management can analyze data, predict customer behavior, and deliver personalized experiences with the help of a generative artificial intelligence platform.
Greater Investment in AI
Mass technology adoption is a result of the decline in the price of artificial intelligence. The market size of the artificial intelligence was $387 billion in 2002. It is expected to grow at a compound annual growth rate of 20.1% to reach $1395 billion in 2029.
Major industries, like healthcare, education, finance, etc., are using artificial intelligence to improve.
Key Considerations For Business Leaders Before Capitalizing on AI Price Decline
Understand Business Goals and Evaluate How AI Fits In
It's important to identify your business strategy and goals before you take advantage of the price decline of artificial intelligence. Artificial intelligence project failure is caused by unrealistic expectations According to a report, almost all of the artificial intelligence initiatives don't make it to production. Assessing your data strategy and how artificial intelligence can be integrated into business to enhance efficiency are important aspects to consider before investing in Artificial Intelligence.
Build a High-Quality AI Team & Equip Them With the Right Tools
Identifying the required hardware and software resources for your artificial intelligence team is important before you invest in it. They can use the right data to build better products. Provide them with the training they need to succeed. Lack of expertise in employees and non-availability of high-quality data are some of the main reasons for the failure of artificial intelligence ventures.
Estimate AI Cost & Return On Investment (ROI)
Many artificial intelligence projects fail because they can't deliver on their promises. In 2012 IBM received funding for its artificial intelligence software for cancer research. It was designed to diagnose and suggest treatments for cancer patients based on the patient's personal data.
The project was criticized for being unreliable and accurate. It cost a lot to set up the software in the hospital. IBM stopped sellingWatson for cancer in 2021. It's important to evaluate the cost of building or acquiring an artificial intelligence technology.
Evaluate AI Regulations
Business leaders need to make sure that their initiatives comply with the rules. Global watchdogs have become more focused on artificial intelligence regulations. Data privacy and security are addressed by these regulations.
The general data protection regulation came into effect in the EU. Personal data collection, processing, and usage are regulated by it.
All of UNESCO's member countries agreed to adopt common values and principles of artificial intelligence ethics to ensure risk-free development.
The Right Time To Invest In AI Is NOW!
Global tech giants are investing a lot of money in artificial intelligence. Microsoft has invested $10 billion in artificial intelligence while Google has invested $400 million in that field.
It is important for businesses to take advantage of the falling prices of artificial intelligence. At the same time, it's important for them to address and overcome the challenges of artificial intelligence.
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