The Major Barriers To AI Adoption For Organizations
“Artificial intelligence” (AI) describes any computer program that can learn, plan, and solve problems in humanlike ways. According to research by the World Economic Forum, by 2022, artificial intelligence will have eliminated the need for approximately 75 million human jobs.
Meanwhile, it will generate an additional 133 million jobs, debunking the fear that the extensive use of AI will lead to increased unemployment. With all the excitement surrounding artificial intelligence right now, it’s hard to believe any company would resist implementing it.
AI is projected to add $15.7 trillion to the global economy by 2030. However, despite AI’s clear advantages, many businesses and employees are anxious about the technology’s potential effects on their businesses and careers. So, if AI has the potential to deliver enormous profits quickly, what might be the significant barriers to its widespread adoption?
The Resistant Mindset
One of the biggest problems with AI adoption is that people don’t want to accept the new culture that comes with strategic AI implementation. Keep in mind that some employees will resist changes in policy or procedure, especially if they involve newer technologies like AI automation.
Some employees don’t like change, especially if it means learning and using new technologies, and would rather keep doing things the same way they always have. In addition, workers are worried about losing their jobs and “Terminators” taking over routine tasks in the workplace. Finally, some employees worry that they will be laid off if their jobs become obsolete due to these changes.
However, you can lessen the impact of such resistance with transparency and proper coordination. Communicating with workers is one of the most efficient ways to prepare them for technological change. Explain the features and benefits of your new cloud service or AI software to them. Motivate your staff to actively assist in the transition and provide them with a forum for their thoughts and concerns.
Many businesses also have doubts regarding the safety of their collected data. The heart of modern AI is based on machine learning algorithms, which are notoriously insecure. Because of these flaws, we may risk experiencing an invasion of privacy and other risks.
Numerous facets of modern life have been revolutionized by machine learning. However, AI can be hacked just like any other computer system. AI developers and users will need to learn how to mitigate the dangers inherent to AI systems. It would be best to assume that your competitors are skilled in identifying and exploiting vulnerabilities. It would help if you took precautions to protect your network from their intrusions.
Shortage of Talents
Experts believe that organizations will only be able to benefit from the expansion opportunity that AI provides partially. This is because there is a lack of data and a scarcity of trained IT professionals who can implement the new framework.
Data science becomes crucial to winning strategies as businesses increase their investments in machine learning and artificial intelligence. However, your current workforce may lack the necessary expertise in data science. As an alternative, your company can engage consultants, and increasingly, businesses are turning to third-party providers to carry out these tasks.
Cost of Implementation
Using AI is expensive, especially if a tailored solution needs to be developed. For example, Analytics Insights reports that the minimum cost to create a prototype is $2,500, while the cost to develop a Minimum Viable Product (MVP) using the client’s data ranges from $8,000 to $15,000.
However, costs associated with putting a complete AI solution could range from $20,000 to $1,000,000. Therefore, a thorough cost analysis is essential before committing to an AI solution. Then, take advantage of an AI that can cater to your requirements while staying within your financial capacity. Investment in AI innovation may have some upfront costs, but its benefits will quickly pay for themselves.
Weak Security Infrastructure
The advent of AI may exacerbate existing concerns about data security in cyberspace. There will always be potential security risks with new technologies such as AI. Accepting these risks is an inevitable consequence of utilizing machine learning.
However, this is not a reason to limit the use of AI. The AI implementation team must establish strict guidelines for handling sensitive data at every process stage, from collection to disposal. Before implementing AI in your company, you should determine whether the potential gains justify the possible risk.
AI is the Future of Business
AI has the potential to aid businesses in three main ways: process automation, data analysis, and consumer and employee engagement. For example, using the RPA cloud, you can automate tasks through a user-friendly online interface accessed from a web browser. In addition, you can be assured that a team is constantly monitoring and updating your automation platform to ensure its safety and optimal performance.