Artificial intelligence has the potential to change the nature of work and the way we look at it. The definition of meaningful work is "the perception that one's work has worth, significance, or a higher purpose" (Michaelson et al 2014). To be considered meaningful work, Bankins and Formosa (2014) came up with 5 dimensions on which they focused. These dimensions include "task integrity, skill cultivation and use, task significance, autonomy, and belongingness".

Task integrity involves having strong principles and being honest in your work setting. This dimension is used to see if the work being done makes the workers become fully developed in their skills and show off their full potential as an employee. Skill cultivation and use is a dimension used to see if the workers are able to use the material that they were taught and put it to use for the establishment they are working for. The ability to grow and improve on that growth is necessary in order for you to be successful in the workforce, as no employer wants an employee who never learns or grows from their mistakes or actions. The task significance dimension is measured by seeing how much the work being done by the employee is beneficial and contributes to the success of the company. If a company notices that someone isn't doing well in their position, they can have the AI help them with the task or even take over their work for them. AI can help workers to be more productive and efficient, allowing them to do more work in less time and potentially even reduce work-related stress. By automating routine and repetitive tasks, AI technology will enable humans to focus on more creative, strategic, and fulfilling tasks. As a result, people may be able to take advantage of their skills and passions and pursue work that is personally meaningful to them.

 Autonomy is defined as “the quality or state of being independent, free, and self-directing” (Merriam-Webster). The reason why this is a dimension of meaningful work is that if someone believes in autonomy work, their ability to do work that aligns with their values and the values of the company will bring them greater success in the workforce. The 5th and final dimension being brought up in this article is belongingness, or “the quality or state of being an essential or important part of something” (Dictionary.com). If the employee doesn’t feel a sense of belongingness in their field, they will not do the job as well as someone who feels connected to the company. The sense of belongingness goes a long way in making a healthy and happy relationship with the people in the workforce. The impact of artificial intelligence on meaningful work will likely vary by industry and job type; however, it also has the potential to create new opportunities for people to engage in rewarding and fulfilling work.

Work as we know it is going to change in the coming years with the addition of AI being introduced into the workforce. Jobs will start to be taken by robots and people will have to learn a new craft in order to fully be ready for what is about to come. In an article from Hypertek Labs, they discussed some future challenges and opportunities of AI's being involved in the workplace. The challenges are what we are focusing on in this section and some of those being faced in the new world of AI technology can include job displacement, skill shortages, bias and discrimination, and privacy and security issues. We will go on to talk about how these challenges are taking a toll on the workplace and what is to come with them in the future 

Job displacement has been one of the biggest issues when it comes to the future of AI technology. According to a report from Goldman Sachs, people are starting to believe that around 300 million jobs could be affected by AI in the coming years, which tallies to about 18% of the world's work. If this is the case, people should start to look into what jobs may or may not have a chance of being taken by these AIs. An article written by Arianna Johnson of  Forbes states that jobs including "finance and banking, media and marketing, along with legal services" may all be jobs soon taken by our AI competitors. Talking more about job displacement, robots and AI as a whole are becoming cheaper than paying people. US News stated that the cost of producing machines has gone down over time, making humans more expensive than machines. Knowing this, AI and robots have been linked to quicker response time and have the ability to learn information fast than normal humans. Companies may not fully get rid of all humans when it comes to bringing in new AI technology, but they will make them learn how to work with AI to get their work done in a timely fashion, with no issues at hand.

Due to the rapid pace of technological advancements in fields needed for AI, there has become a shortage of skilled workers. This presents a significant challenge for AI in the workplace, as companies may struggle to find qualified personnel to develop and implement AI systems. Without skilled workers, companies may not be able to fully realize the potential benefits of AI and instead may develop some challenging issues in the future. Addressing the shortage of skilled workers in AI will be crucial for the continued growth and success of technology in the workplace. 

Bias and discrimination can become significant challenges for AI because they can lead to unfair and inaccurate decision-making. AI systems are completely reliant on the data they are trained on, and if that data contains biases, the AI system will learn those biases and possibly use them it in its decision-making processes. Discrimination can also occur when an AI system is designed or programmed in a way that disadvantages certain groups of people. This can become quite problematic in areas such as hiring, lending, and criminal justice, where AI systems are being used to make important decisions that can significantly impact people's lives as they know it. AI systems may also be susceptible to enhancing existing social inequalities since they often rely on data that reflects past discriminatory practices or reinforces stereotypes. Because of this, addressing bias and discrimination in AI is needed to ensure that AI systems are fair, just, and inclusive to all people.

Privacy and security has caused some uproar with the people when it comes in the new AI technology.  Ensuring privacy and security in the workplace is a challenging task due to the increasing frequency of digital technologies, the rise of remote work, and the amount of sensitive data that businesses collect and store. According to a study by IBM, a data breach caused by an insider or a criminal attack in 2022 grew 41% in the last year, highlighting the need for robust security measures to protect against such threats (IBM, 2022). Additionally, employees may compromise the privacy of sensitive information by sharing it with unauthorized parties, either intentionally or unintentionally. When people are doing this, it ends up leading to data breaches and reputational damage for the organization. Forbes reported that a study from Tessian found information that "over one-third (36%) of employees have made a mistake at work that compromised security and fewer are reporting their mistakes to IT." (Segal 2022) To address these challenges, organizations must implement effective security policies and training programs to ensure that employees are aware of the risks and best practices for protecting sensitive information