Are AI Bots Overtaking Human Web Activity and Creating Cyber Risks?

Article Highlights
Off On

The prevalence of automated bot traffic on the internet has been a rising concern, with recent reports indicating that bots have started to dominate web activity, surpassing human interactions. Bot traffic accounted for 51% of the total web activity last year. Among this, bad bot traffic grew significantly, from 32% to 37%, posing clear cyber risks. This surge can be attributed to advancements in artificial intelligence and large language models (LLMs), which now make it easier to create bots on a massive scale. Prominent bots like ByteSpider Bot, responsible for 54% of AI-enabled attacks, along with others such as Applebot, ClaudeBot, and the ChatGPT User Bot, are at the forefront of this alarming trend.

Rising Threat of Bad Bots in Key Industries

Certain sectors have been particularly targeted by bot attacks, with dramatic effects on their operations. In the travel industry, bot attacks accounted for 41% of total incidents, while the retail sector faced an even higher threat at 59%. The travel industry, having faced the most attacks last year, experienced a decline in the complexity of attacks but an increase in volume. This shift is largely due to AI, allowing less skilled threat actors to execute a higher number of less complex assaults, further stressing the security infrastructures of these sectors. Bad bots exhibit a high degree of versatility, being exploited for Distributed Denial of Service (DDoS) attacks, custom rules violations, and breaches of Application Programming Interfaces (APIs). A salient point from the report indicates that advanced bot traffic targeted APIs in 44% of recorded cases for executing automated payment fraud, account hijacking, and data exfiltration. Financial services, healthcare, and e-commerce sectors are especially vulnerable due to the sensitive nature of the data they manage. The vulnerabilities in APIs are primarily attributed to their intrinsic business logic, which can be easily manipulated by experienced attackers.

The adoption of cloud-based services and microservices architectures, while offering numerous operational advantages, also brings associated risks. It is essential for organizations to fully comprehend the risks related to APIs and take active measures to mitigate fraud and data breaches. Failing to secure these touchpoints can lead to significant harm, both financially and reputationally.

Conclusion and Future Considerations

The rise of automated bot traffic on the internet is causing increasing concern. Recent reports reveal that bots are now more active online than humans. Bot traffic made up 51% of total web activity last year. This includes a notable increase in bad bot traffic, which climbed from 32% to 37%, highlighting distinct cyber risks. This trend is linked to the progress in artificial intelligence and large language models (LLMs), which have simplified the mass production of bots. Major bots such as ByteSpider Bot, responsible for 54% of AI-driven attacks, and others like Applebot, ClaudeBot, and the ChatGPT User Bot are leading this troubling development. These bots have become highly sophisticated, making it challenging to distinguish between human and automated interactions online, thereby increasing threats to cybersecurity. As bots continue to advance, mitigation efforts must be enhanced to protect web integrity and user security.

Explore more

Trend Analysis: Agentic AI in Data Engineering

The modern enterprise is drowning in a deluge of data yet simultaneously thirsting for actionable insights, a paradox born from the persistent bottleneck of manual and time-consuming data preparation. As organizations accumulate vast digital reserves, the human-led processes required to clean, structure, and ready this data for analysis have become a significant drag on innovation. Into this challenging landscape emerges

Why Does AI Unite Marketing and Data Engineering?

The organizational chart of a modern company often tells a story of separation, with clear lines dividing functions and responsibilities, but the customer’s journey tells a story of seamless unity, demanding a single, coherent conversation with the brand. For years, the gap between the teams that manage customer data and the teams that manage customer engagement has widened, creating friction

Trend Analysis: Intelligent Data Architecture

The paradox at the heart of modern healthcare is that while artificial intelligence can predict patient mortality with stunning accuracy, its life-saving potential is often neutralized by the very systems designed to manage patient data. While AI has already proven its ability to save lives and streamline clinical workflows, its progress is critically stalled. The true revolution in healthcare is

Can AI Fix a Broken Customer Experience by 2026?

The promise of an AI-driven revolution in customer service has echoed through boardrooms for years, yet the average consumer’s experience often remains a frustrating maze of automated dead ends and unresolved issues. We find ourselves in 2026 at a critical inflection point, where the immense hype surrounding artificial intelligence collides with the stubborn realities of tight budgets, deep-seated operational flaws,

Trend Analysis: AI-Driven Customer Experience

The once-distant promise of artificial intelligence creating truly seamless and intuitive customer interactions has now become the established benchmark for business success. From an experimental technology to a strategic imperative, Artificial Intelligence is fundamentally reshaping the customer experience (CX) landscape. As businesses move beyond the initial phase of basic automation, the focus is shifting decisively toward leveraging AI to build