Virtual Assistants and Text-Based Assistants Understanding the Differences

By: Pinaki Sahu, International Centre for AI and Cyber Security Research and Innovations (CCRI), Asia University, Taiwan,


Imagine talking with a voice-activated virtual assistant, such as Siri or Alexa, or with a text-based assistant in a messaging app. This article discusses the distinctions between these two technological companions. Virtual assistants adore your voice and are best friends with particular devices, whereas text-based assistants are the companions with whom you can converse at any time. Your choice between them will depend on your personal preferences, location, and requirements. As technology advances, both companions promise to make your life more convenient and personalised.


The modern digital age has created a range of intelligent assistants designed to make our lives easier. Added virtual assistants and text-based assistants. Both features streamline operations, provide information, and improve the user experSience. In this article, we will explore the differences between virtual assistants and text-based assistants, focusing on their unique characteristics and impact on consumers and various aspects of our daily lives.

Virtual Assistant

Voice-enabled virtual assistants are entities powered by artificial intelligence that can perform tasks with voice interaction. Google’s Assistant, Amazon’s Alexa, Apple’s Siri and Microsoft’s Cortana are popular virtual assistants[1]. They are found on smart speakers, smartphones, and additional devices. The primary features of virtual assistants include:

Voice interaction: virtual assistants respond to spoken commands and queries, allowing for hands-free operation. This is particularly useful for accessing information, setting reminders, and controlling connected home appliances.

Device integration: Virtual assistants are frequently pre-installed on mobile devices and are tightly incorporated with their ecosystem. Alexa is a key feature of Amazon’s Echo devices, whereas Siri functions well with Apple products.

Understanding context: Context can be maintained within a conversation, allowing users to ask follow-up questions or more complex questions.

Task automation: Virtual assistants excel in tasks such as setting alarms, sending messages, playing music and providing instructions.

Fig.1.Virtual Assistance workflow[1]

Text based Chatbot assistance : Helpers based on information

On the other hand, text based assistance operate primarily through text or conversational interfaces. They are commonly found in messaging apps, websites, and other text-based sites. Some well-known examples include customer service chatbots, shopping assistants, and personal productivity tools[3]. Key characteristics of text-based assistants include:

Text conversation: People talk to text-based assistants through text messages, which means they can be used when voice communication isn’t possible or acceptable.

Text-based helpers are flexible because they can be built into digital platforms and help people through web chat, messaging apps, or even email.

Available 24 hours: Text-based helpers can help customers and people who buy things online at all times.

Customization: It can be changed to fit specific needs, which lets businesses talk to their customers in the best way possible.

Fig.2 Text-Based Chatbot Assistance[3]

Differences and Utilisation Scenarios

Virtual assistants and text-based assistants have the same goal of providing assistance, but their usage and contextual application are distinct. Depending on the user’s preferences, a virtual assistant or a text-based assistance may be chosen. Individual preferences for communication methods vary, with some individuals preferring verbal conversations and others preferring text-based communication. Voice commands facilitate the accessibility of virtual assistants, making them particularly suitable for situations in which manual dexterity is limited or when driving. Text-based virtual assistants provide a simple alternative for individuals who are unable or unwilling to speak. Virtual assistants are exceptionally adept at engaging in complex and multifaceted conversations and performing tasks that require a comprehensive understanding of context. Text-based assistants are versatile in their ability to answer brief queries, provide customer service, and provide website-related information.

Conclusion with a concern of cyber-security

Virtual and text-based AI assistants have significantly improved our daily lives by managing tasks and enhancing experiences. As advances are made in AI and natural language processing, these assistants provide increasingly personalized interactions. However, cybersecurity is a major concern. The protection of sensitive data handled by AI assistants is very essential. Necessary security measures are needed which consist of encryption and vigilant threat monitoring for securing our private data[4]. Moreover, AI algorithms must be continuously strengthened to remain ahead of cyber threats. While these assistants are here to stay and will continue to positively influence our lives, a concurrent focus on cybersecurity is necessary to ensure the safety and security of our digital interactions.


  1. Tulshan, A. S., & Dhage, S. N. (2019). Survey on virtual assistant: Google assistant, siri, cortana, alexa. In Advances in Signal Processing and Intelligent Recognition Systems: 4th International Symposium SIRS 2018, Bangalore, India, September 19–22, 2018, Revised Selected Papers 4 (pp. 190-201). Springer Singapore.
  2. Borah, B., Pathak, D., Sarmah, P., Som, B., & Nandi, S. (2019). Survey of text based chatbot in perspective of recent technologies. In Computational Intelligence, Communications, and Business Analytics: Second International Conference, CICBA 2018, Kalyani, India, July 27–28, 2018, Revised Selected Papers, Part II 2 (pp. 84-96). Springer Singapore.
  3. Nembhard, F. D., & Carvalho, M. M. (2023, July). Teaming Humans with Virtual Assistants to Detect and Mitigate Vulnerabilities. In Science and Information Conference (pp. 565-576). Cham: Springer Nature Switzerland.
  4. Wang, L., Li, L., Li, J., Li, J., Gupta, B. B., & Liu, X. (2018). Compressive sensing of medical images with confidentially homomorphic aggregations. IEEE Internet of Things Journal6(2), 1402-1409.
  5. Stergiou, C. L., Psannis, K. E., & Gupta, B. B. (2021). InFeMo: flexible big data management through a federated cloud system. ACM Transactions on Internet Technology (TOIT)22(2), 1-22.
  6. Gupta, B. B., Perez, G. M., Agrawal, D. P., & Gupta, D. (2020). Handbook of computer networks and cyber security. Springer10, 978-3.
  7. Bhushan, K., & Gupta, B. B. (2017). Security challenges in cloud computing: state-of-art. International Journal of Big Data Intelligence4(2), 81-107.

Cite As

Sahu P. (2024) Virtual Assistants and Text-Based Assistants Understanding the Differences, Insights2Techinfo, pp.1

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