The days when only hard work was the key to success are long gone. In today’s world, it’s all about combining hard work with smart work.
In recent years, we all have witnessed how efficient artificial intelligence or AI is in doing smart work. Many businesses are leveraging the power of AI. Statista estimates that the value of AI in marketing is likely to grow to more than 107.5 billion by 2028.
From giving shoppers recommendations based on their preferences, browsing history, and interests, to allowing businesses to employ chatbots that can provide customer service 24*7, AI can do it all. Users can also get accurate directions with GPS technology. Further, AI technology is used by companies to show you content based on your preferences on social media channels. Because of its widespread use in various fields, people have shown great interest in AI.
But like any other technology, there are some challenges businesses face when using artificial intelligence or AI. To utilize the full potential of AI to your advantage, one needs to address these challenges.
What are the Challenges of Using AI in 2023?
No matter the field, one is bound to face challenges, and the field of AI is no different. For the seamless implementation of AI across various fields, human intervention is needed to address any problems. The sooner strategies are made and implemented to take on these challenges; the better one will be able to explore the potential of AI.
Let’s talk about the AI challenges that are creating a hurdle for organizations trying to encompass AI in their operations.
1. Privacy Concerns Regarding Sensitive Data
AI gets training on a vast amount of data, including personal and sensitive data. Upon a request by the user, it uses that data to share results and work efficiently. However, being a reactive machine, AI responds to all types of requests by the user, even if it compromises a user’s sensitive data. It can’t differentiate which data is personal and sensitive and should not be shared. As a result, many organizations feel that AI may compromise their sensitive data.
If you are using AI, you can protect your as well as the data of your partners by putting robust privacy measures in place, like choosing secure data storage and going for data anonymity. Another way to alleviate the privacy concerns of those working with you is to comply with all necessary data protection regulations and have transparent data usage policies.
2. Unreliable Results
Due to its data limitations, incomplete datasets, or sometimes the difficulty level of specific tasks, the AI system produces unreliable results. To ensure reliable, consistent, and accurate results, rely on rigorous testing and a strict validation process.
Another way to get accurate results is to keep humans in the loop. For example, even if you use AI in web development, it may help you get the code instantly, but you will need a web developer to check if it’s usable.
3. Need for High Processing Power
Artificial intelligence can help carry out easy tasks smoothly. However, one must fulfill the AI’s requirement for substantial processing power to perform complex tasks. Higher processor power and high storage requirements mean high infrastructure as well as power bill costs. The high cost can be reduced by using cloud computing services and hardware technology like distributed computing systems and specialized AI chips.
4. Irrelevant Results Due to Unclear Goals
Sometimes companies use AI because everyone else is using it. But they don’t know what AI can do for their business. In such cases, they end up using AI the wrong way by giving it an unclear set of instructions and don’t get the results they desire.
To overcome this challenge, businesses must set clear goals and specific key performance indicators that matter to them. They can monitor their AI systems regularly to ensure they effectively meet their goals. Further, they need to analyze certain areas where AI can bring maximum value to them and adjust and optimize their strategy accordingly.
5. Biased Algorithms
AI is fed with data that it uses to provide answers to all kinds of problems. Bias, preferences, and assumptions can be present in that dataset, giving flawed or unfair outcomes and even perpetuating inequalities in society. It can adversely affect companies that involve AI in their decision-making processes and depend on it for fair results.
If you are planning to introduce it in your business or already leveraging it to make crucial decisions, make sure to minimize biased patterns in your training data and audit it regularly to ensure fairness in the AI software you use. Additionally, you can develop bias detection methods and implement mitigation techniques. Companies having the budget can also collaborate and partner with third parties to get access to relevant, unbiased, and diverse datasets.