Mental health is integral to the well-being of the human species. Being in a good mental state enables individuals to cope with their demanding daily lives, realize their potential, and make contributions to society. However, the stresses of the modern world mean more and more people are now vulnerable to developing mental health conditions.
The traditional approaches to diagnosing mental health conditions have their own set of limitations. Artificial Intelligence (AI) has the potential to address several challenges associated with traditional mental health therapeutics. Continue reading as we detail the various benefits of AI in mental health and detail the top factors driving the Artificial Intelligence (AI) in mental health market forward. Stick with us!
AI in Mental Health Technologies
A number of AI technologies are used to treat mental health conditions. Below, we’ve given some of them:
Natural Language Processing: Natural language processing, commonly abbreviated as NLP, is a subfield of computer science that combines computational linguistics with machine learning models. NLP primarily deals with providing computing systems with the ability to support, understand, and manipulate human language.
Context-Aware Computing: This is essentially a type of computer operation that enables applications to discover and take advantage of contextual information. In other words, it can sense the physical environment and adapt to it accordingly.
Machine Learning: Machine learning is a branch of AI and computer science that deals with the development of AI algorithms that can learn from data and carry out tasks with explicit instructions. In the context of artificial intelligence (AI) in mental health market, machine learning can help during the diagnosis, prognosis, and treatment stages.
Computer Vision: Computer vision is a sub-field of AI that allows computers to gather, process, analyze, and understand information from digital images, videos, or other inputs. Computer vision systems can extract high-dimensional data to produce symbolic or numerical information.
What’s Propelling the Market Forward?
The market for AI in mental health is projected to witness rapid growth. The market size was valued at USD 921.53 million in 2023 and is projected to reach USD 10,334.09 million by 2032. The market is projected to exhibit a CAGR of 30.8% over the forecast period, 2024-2032.
The artificial intelligence (AI) in mental health market growth is primarily fueled by:
- Increasing number of complex datasets
- Rising prevalence of mental health disorders
Benefits of Using AI in Mental Health Treatment
There are numerous benefits of using AI in mental health treatment. Below, we’ve detailed some of them:
Affordability: The traditional approaches to mental health counseling require individuals to schedule appointments. But AI-based mental health apps allow users to access therapeutic whenever and wherever they want. Furthermore, they offer assistance at low to no cost, compared to the cost associated with in-person therapy or missed work.
Accessibility: AI-based mental health apps developed by artificial intelligence (AI) in mental health market key players take away the barriers associated with mental health treatment, such as staff shortages and lack of providers. This is important as several people currently live in areas that have a shortage of healthcare professionals.
Efficiency: AI algorithms for mental health have already been proven successful at detecting symptoms associated with mental health disorders like depression and PTSD. Also, these algorithms can spot behavioral symptoms of mental health conditions with a high level of accuracy.
Privacy and ease of opening up: AI-based therapists may make individuals feel less restrained when it comes to sharing uncomfortable information or details. This is highly crucial for people who can feel awkward in face-to-face conversations owing to stigma or other things.
Machine Learning Segment Accounted for a Significant Revenue Share
By technology analysis, the machine learning segment witnessed a significant share of the market. The segment’s dominance in the market can primarily be attributed to the widespread use of ML algorithms across diverse mental health applications. ML algorithms assist healthcare professionals in assessing whether an individual is at risk of developing any mental health condition. Besides, ML also aims at developing algorithms that can automatically find hidden patterns in data, thereby resulting in higher accuracy and better treatment outcomes in the artificial intelligence (AI) in mental health market.
End Note and Conclusion
The significant shortage of experienced healthcare professionals results in longer waiting times for mental health diagnosis and treatment. As such, the role of AI in healthcare becomes highly crucial as it has the potential to address several issues experienced by mental healthcare systems across the globe.