Applicant tracking systems, colloquially referred to as ATS, have gradually emerged to be indispensable to the world of recruitment. ATS refers to software applications that enable the electronic handling of recruitment and hiring needs. The primary function of an ATS is to provide a centralized database for a company's recruitment efforts, streamlining the process and making it more efficient.

But, as with any technology, it is in a state of continuous evolution, influenced by other emerging technologies and changing market needs. As we look into the future, it is critical to examine and anticipate the future of ATS and the trends that are poised to shape it.

One of the most significant influences on the future of ATS is Artificial Intelligence (AI). AI is increasingly being integrated into ATS to automate routine tasks, thereby enhancing efficiency and effectiveness. For instance, AI can help in the automatic sorting and ranking of resumes based on specific parameters, reducing the workload on recruiters. AI can also facilitate advanced semantic search, which goes beyond simple keyword matching to understand the intent and contextual meaning of words, thereby improving the quality of matches.

However, the integration of AI is not without its caveats. AI systems are only as good as the data they are trained on, so any biases in that data can be reflected in the AI's operation. For instance, if the training data contains a bias towards candidates from certain universities, the AI might perpetuate that bias. Therefore, it is essential to ensure that the training data is diverse and unbiased.

Deep learning, a subset of AI, could potentially mitigate this issue. Deep learning algorithms can learn and improve from their mistakes, and therefore, over time, they can reduce the impact of any initial biases in the training data. However, deep learning requires vast amounts of data and computational resources, which might be a limiting factor for some organizations.

The next emerging trend is the integration of ATS with other HR systems. Traditionally, ATS has been standalone systems, but there is an increasing trend towards integrating them with other HR technologies like Human Resource Information Systems (HRIS) and Learning Management Systems (LMS). This can facilitate better data sharing and coordination between different HR functions, thereby enabling a more holistic approach to talent management.

On the horizon, we might see ATS integrating with technologies like Virtual Reality (VR) and Augmented Reality (AR). These technologies can provide innovative ways to interact with candidates and assess their skills. For instance, VR can be used to provide a virtual tour of the workplace to candidates, and AR can be used to administer practical tests during the interview.

However, the integration of such technologies raises questions about privacy and data security. For instance, VR and AR applications can collect a wealth of data about the user, including their movements and interactions. This data needs to be handled responsibly to respect the privacy of candidates and comply with data protection regulations.

The future of ATS is also likely to be influenced by broader societal and economic trends. For instance, the COVID-19 pandemic has led to a massive shift towards remote work. This change might lead to new requirements for ATS, such as the need to manage a geographically distributed talent pool and facilitate remote interviews.

In conclusion, the future of ATS is likely to be shaped by a confluence of technological, societal, and economic factors. It's a future that promises greater efficiency and effectiveness, but also brings new challenges and considerations. As we move towards this future, it is crucial to keep these emerging trends in sight and prepare for them. After all, to quote Wayne Gretzky, "I skate to where the puck is going to be, not where it has been."