What are the Challenges of Using Artificial Intelligence?


Artificial intelligence is known to bring tremendous revolution in the way humans perform and work. The integration of AI into numerous modern-day machines has resulted in dramatic improvement, from workplace efficiency to the augmentation of human potential.  However, these manifold advancements also come with limitations and more importantly with the fear and concern of AI taking over humans and not just mechanizing human efforts. Through this blog let us explore the varied challenges of artificial intelligence and how it may prove to be negatively impacting the world in the future at large. 

Top Challenges of Artificial Intelligence

Data Paucity:

One of the biggest challenges of AI is the paucity of data. AI is only effective and functional when they are fed with the input of data. They are only as efficient as the quality of data. AI-powered machines to give the best results rely on data. Companies are facing the challenges of aggregating the right set of data to generate accurate results as they do not have access to the desired quantity of data. Big tech moguls like Apple, Facebook, and Google are challenged with the issues of exploiting local data to develop applications for the entire world, as many countries employ strict IT rules restricting the flow of data. The imbalance thus will result in discrepancy and biased results.



The higher efficiency of Artificial Intelligence demands supercomputers. The innovations in AI like Machine learning and Deep learning demand and relies on the efficiency of GPUs and a number of cores to work efficiently. Often, AI requires the computing power of supercomputers and they are expensive. The services that the cloud offers to developers such as parallel processing systems and cloud computing are expensive. While a few numbers can access and afford such supercomputers, not everyone has the capacity to afford them.

Given the inflow of colossal amounts of data and the rapid amplification of complex algorithms. This presents one of the significant challenges of AI for businesses to implement as many of them are still relying on outdated machines and equipment that lack the capacity to perform such operations and processes. It requires companies to invest heavily in revolutionizing their methods, tools, applications, and infrastructure for implementing the superpower of disruptive machine learning and deep learning advances.


Talent Deficit:

This ranks top among the major challenges of artificial intelligence. While the advances of Artificial intelligence are growing rapidly, the field itself is new, there is a huge gap in knowledge of AI. Only a few numbers of people including researchers, IT enthusiasts, and college students have the appropriate knowledge of the potential of AI. This renders the challenges of finding people with the necessary skills and knowledge for organizations to engage in the revolutionary implementation of AI.


Lack of Trust:

The nature of the prediction provided by the deep learning models is unknown. This presents one of the most critical challenges in AI. The general layman is illiterate about a certain set of inputs devising a solution for a particular program. They are oblivious to how AI is largely integrated into the devices and items that are used in our everyday lives. The mechanisms by which AI integration works with smart devices like phones, TVs, and even cars are still unknown to ordinary people.


Lack of Human Touch:

While artificial intelligence is known to automate operations providing greater task efficiency, it fails to provide accuracy of 100 percent. This forms one of the most significant challenges of AI. This instance keeps most researchers apprehensive. When it comes to accuracy, AI fails to deliver at the level that humans can.


Issues of Privacy and Security:

AI drives and sustains data as discussed above. The data however are generated from varied sources from millions of users all around the world. There is a high possibility of these data being exploited for malicious intent. Cyber security risks and the dark web is a reality today. The data collected are in numerous industries from banking institutions to healthcare services. A single data breach may result in the compromising of millions of users' confidential information. From medical history to financial savings credentials. The surge in digitization has resulted in almost every industry jumping on the bandwagon. The world now is challenged by the humungous scale of data and there is a high possibility of data leakage in any of the sources of these data. Several organizations are now working to overcome these top AI challenges by implementing security measures. Yet no organization can escape the threats that are looming large constantly.


AI is Biased:

The nature of good or bad AI systems wholly relies on the nature and the amount of data that is used to train their AI algorithm. The only way to gain efficient services of AI is to aggregate good data. The data that organizations aggregate on a daily basis holds no significance unless they are put to train on an AI algorithm. A small amount of data that organizations collect only reflects that of a specific number confined to a certain group of people.


Ethical Issues:

This is again another one of the significant AI challenges. With the surging uses and integration of AI  and the increasing independence of AI systems, there is a growing concern about its accountability and privacy. It is a pressing concern for organizations to ensure that AI machines operate fairly and responsibly. 


Fear of Job Disruption:

One of the biggest AI challenges is how the general populace is concerned about the fear of losing jobs on machines and how it can significantly replace humans. The rate at which AI-powered machines are automating tasks reflects the potential of reshaping the job market. This is a constant debate that is buzzing in the tech world and among ordinary people as well. There may be cases of eliminating jobs characterized by routine tasks. Yet, the phenomenon will be accompanied by the creation of new job roles. The creation of new job roles will require new skills and knowledge, which may considerably require a time commitment for learning and training. Workforces of every organization will be required to take proactive measures of upskilling and reskilling to fit into the new-age roles. 


Those are the major challenges of AI that are limiting the potential of artificial intelligence. The world will need to strike a balance that allows for careful and intelligent use of Artificial intelligence and equally working on the AI challenges to embrace and be ready for evolving technological landscape.

Post a Comment