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Security Research

Analysis of Generative AI Trends and ChatGPT Usage

September 26, 2023 - 8 min read


The release of ChatGPT underscores the potential of artificial intelligence to revolutionize the daily operations of organizations. This paradigm shift is compelling businesses to reevaluate their conventional approaches and embrace the transformative capabilities offered by AI. Among the noteworthy facets of AI’s evolution, Large Language Models (LLMs) have emerged as a dominant force, reshaping user interactions and communication. The driving force behind this transformation is the pursuit of vast datasets, enabling machine learning algorithms to analyze patterns and generate responses in a seamlessly natural language. 

In this blog, we aim to provide a comprehensive perspective on the impact of AI-powered applications and offer guidelines for the responsible integration of AI tools within organizational contexts.

Key Takeaways

- stands out as the preeminent domain for AI and ML enthusiasts, offering a wealth of resources, research, and interactive AI models. Notably, over half of the website’s traffic is attributed to ChatGPT, underlining its significant impact on user engagement and AI exploration. 

- Drift has secured its position as the most popular AI/ML application, specifically excelling in language processing through LLM-based SaaS solutions. Drift’s popularity rivals ChatGPT, which came in just under Drift by less than 1%. 

- ChatGPT experienced a substantial surge in usage during the initial months of this year, indicative of its growing relevance and adoption. However, the upward trajectory reached a plateau in August.

- The lion’s share of AI/ML traffic is predominantly generated from the United States and India. The primary use case for this global traffic surge is the exploration and implementation of generative AI applications.

AI vs LLMs

AI and LLMs are two interconnected but distinct concepts in the field of computer science. AI represents the broader umbrella term, encompassing a wide array of techniques and technologies designed to simulate human intelligence and problem-solving. It includes machine learning, generative artificial intelligence models, natural language processing, computer vision, robotics, and deep learning, among others. LLMs are a specific subset of AI, focused primarily on natural language understanding and processing.1

How ChatGPT, and similar generative AI modules like GPT-3 and GPT-4, operate within the realm of AI applications has garnered significant attention in recent years. While AI has been in development for decades and encompasses a diverse range of technologies, LLMs have gained prominence relatively recently due to their remarkable ability to generate human-like text.2

Securing AI/ML Transactions

Significantly, the majority of AI/ML-related transactions undergo thorough scrutiny so 10% of all AI/ML-related transactions are blocked using URL filtering policies. The technology sector takes the lead in blocking AI/ML transactions, closely followed by the finance and manufacturing sectors.

A breakdown of which industries are blocking the most AI/ML-related transactions.Figure 10: A breakdown of which industries are blocking the most AI/ML-related transactions.

Drift holds the unique distinction of being both the most used and most frequently blocked application.

A pie chart showing how the overwhelming majority of blocked AI/ML transactions originate from Drift - a conversational AI application.Figure 11: A pie chart showing how the overwhelming majority of blocked AI/ML transactions originate from Drift - a conversational AI application.

AI/ML Best Practices Guide

Considering the rapid advancement and adoption of AI-powered applications, it is crucial to establish and follow best practices to ensure the responsible and secure use of these transformative technologies.

- Organizations must proactively adapt their AI usage and security policies to stay ahead of potential risks and challenges. 

- Recognize that AI-powered applications come with risk and continually assess and mitigate risks to protect intellectual property, personal data, and customer information. 

- Ensure that the use of AI tools complies with all relevant laws and ethical standards. This includes data protection regulations and privacy laws.

- Establish clear accountability for the development and deployment of AI tools. Define roles and responsibilities within your organization to oversee AI projects.

- Maintain transparency when using AI tools, Justify their use and communicate their purpose clearly to stakeholders.


- Do not provide non-public information, personally identifiable information (PII), proprietary company data, or any confidential information to AI models.

- AI cannot replace a human being. It should not be used to make decisions without appropriate human intervention. 

- AI-generated content should not be used without human review and approval, especially in cases where the content represents your organization.

- The development and integration of AI tools should follow a Secure Product Lifecycle Framework to guarantee the highest level of security.

- Perform thorough product due diligence before implementing AI solutions. Make sure to evaluate their security and ethical implications.


From the release of ChatGPT and the prominence of AI-powered applications like Drift, to the pivotal role of LLMs and the services hosted on, we’re witnessing a dynamic AI revolution. The global interest, particularly from the United States and India, in generative AI applications highlights the transformative possibilities these technologies bring. As exciting as these changes are, it’s important to incorporate best practices and guidelines into your AI/ML strategy to ensure the responsible and ethical use of such AI-powered applications. As the technological landscape continues to shift, it’s essential to remain vigilant, responsible, and adaptive as we utilize AI/ML to shape the future. Zscaler's ThreatLabz team continuously monitors for new threats and shares its findings with the wider community.



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