drawbacks of ai

3 Drawbacks Of AI & How to Handle Them the Best You Can?

Although with some drawbacks of AI, it is still the future of basically everything. With its ability to transform business operations and streamline corporate functions to aid business executives in making crucial decisions using facts, data and statistics, AI is completely revolutionizing how we worked before. Surely, the productivity has quadrupled and the amount of money that is being saved is in billions if not in trillions. 

However, as all good things can come with a catch, AI comes with its own set of issues and limitations which can make certain processes a piece of work. Although, with adequate assistance, these issues can be easily resolved. Various tech companies are working round the clock to ensure that the disadvantages of ML and DL remain minimal and the pros of the technology heavily outweigh the cons. Before you adopt the ways of AI, it’s important to familiarize yourself with the general problems that the technology comes with.  

  1. System manipulation: ML systems are significantly prone to false predictions if they receive harmful inputs from malicious elements. If the machine receives malicious intel, then the output it provides would be false and tampered with as well. This could result in harmful decision-making since the data based on which the ML was making decisions was unverified, incorrect, or straight-up dangerous. If there’s system manipulation, not only can it dent the present working of the company, but also have a far-reaching impact on the future endeavors of the firm. Thankfully, there are several companies working to resolve this issue, and numerous have also made significant strides in that regard.
  2. Data corruption: Corporations and board members rely heavily on big data to run their companies, make decisions, set objectives and formulate plans to achieve those goals. This proves just how crucial data is for any data-driven company, and how important it is to maintain the reliability of data by protecting it against harmful elements such as hackers. If the datasets are corrupted by malicious elements, which is another limitation of AI/ML, then the data output of the company would also be poisoned. PAM policies can help in preventing such a horrifying eventuality. 
  3. Data privacy: One of the biggest limitations of anything digital is the issue of data privacy. It’s important for companies to be able to safeguard the confidentiality and the privacy of the data that it has collected over time. The data could also include the personal information of various clients and customers.

      The leakage of data in big corporations such as Marriott International, and LinkedIn has been a wake-up call for corporate executives and the general public alike. While using AI, the data is built on the model of machine learning itself. If any hacker attacks the data for extraction, the effect would be felt throughout the machine learning system. For this reason, board members would have to come up with ways to protect their data from breaches. 

While AI/ML has its own flaws, it’s nothing that can’t be fixed. Before you adopt the technology for your company, it’s important to look for security and cybersecurity solutions that provide safe computing environments. For complete end-to-end protection for AI applications, the right kind of guidance and solutions should be sought to prevent the eventuality of data corruption, system manipulation, and breach of data.   

Apart from these limitations, the usage of AI and ML can come with several issues. Companies may need contingency plans to be able to deal with such problems as and when the effects of the same begin to slow down the productivity in the offices.  

  • Lack of technical know-how: It’s important for the company to have employees who have in-depth knowledge of the functioning and implementation of AI, otherwise things could backfire.  
  • The Cost: A technology is as expensive as it can get. It’s paramount for the company to figure out the cost factor before splurging on AI.  
  • Ethical issues: There are numerous ethical issues attached to AI, since it’s a practice of training machines to be humans. It would become tricky for customers to know whether they are speaking to a human customer service agent or just a bot.  
  • Expensive workforce: Not only would you have to consider the cost factor of the AI hardware and software, but also the cost of hiring employees such as data engineers and data scientists to operate the mechanism.  


Questions To Ask Before Adopting AI/ML 

After understanding the benefits and risks of AI, here are some important questions that businesses need to ask before employing AI into their current workflow: 

  • What are some aspects of our business that AI, machine learning, and increased automation that technologies provide can help with? 
  • Can AI complement the existing technologies that our company uses, or work well with emerging technologies that are still under development but we might later adopt at some point down the line? 
  • Do we have the required resources and manpower to maintain the use of AI for the foreseeable future? 
  • Can we successfully gain the trust of stakeholders and potential investors with the use of AI to make crucial decisions in our company, provided that we fully, or partially delegate the role of decision-maker to the technology? 
  • Do we know how we will harness big data using AI to achieve the collective goals of the company? Have we taken into account the privacy issues, and cyber risks that the use of AI can pose and know how we will deal with these? 

Before you adopt any new technology in the market, it’s important to consider the factors influencing its adoption, and what are some challenges that the board members might face once the use of the technology kicks off. It’s important to analyze your present situation, and gauge how the addition of an AI system can benefit your company, or how well it can fit with the present framework. It’s also crucial to have the right people working on making the AI a success. Make sure that you have the foot soldiers for the job as well.  

How ANAI Can Help?  

ANAI can automate your business operations by providing you with AI and ML solutions to boost your company’s productivity and increase ROI. We use AI and ML models to help our clients solve problems and revolutionize their business processes and operations to meet the rising demands of today’s consumers. With AI in the front seat, physical labor is reduced significantly, which leaves the boardroom executives to deal with more pressing issues in the company.  

With ANAI’s eXplainable AI-based solutions, biases within your company’s data could be removed, making the system more accurate from the inside out. If you want to stay one step ahead of your customers in regards to market research and trend predictions, ANAI can help you. Get started with the digital transformation in your company today.  

Overcoming AI drawbacks, When AI can go wrong, Risks and Challenges in AI, Machine Learning Challenges

If you are interested in getting a demo to see if ANAI fits with your existing workflow, contact us at info@anai.io or visit www.anai.io. 

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We offer a comprehensive ecosystem that blends Data Engineering and Automated Machine Learning that enables the ‘Democratizing of AI and ML’. 


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ANAI - AI for AI


+1 646 699 8676

We offer a comprehensive ecosystem

that blends Data Engineering and Auto-

mated Machine Learning that enables the

‘Democratizing of AI and ML’.