AI Traffic Is Growing 6.5x Faster Than Human Traffic, Fastly Reports

AI Traffic Is Growing 6.5x Faster Than Human Traffic, Fastly Reports

Friday, June 26, 2026

Artificial intelligence is no longer just changing how people search, shop, and work online. It's also transforming the very nature of internet traffic.

According to new research from edge cloud platform Fastly, AI-generated traffic is growing significantly faster than human traffic, creating new challenges and opportunities for businesses managing websites, applications, and digital services. As AI assistants, autonomous agents, and machine-driven systems become more common, organizations may need to rethink how they handle automated requests and protect their digital infrastructure.

Fastly Finds AI Traffic Growing at a Rapid Pace

Fastly's latest analysis of activity across its global network found that AI-generated requests increased by approximately 30% between January and May 2026. During the same period, AI traffic expanded 6.5 times faster than human traffic, highlighting how machine-driven interactions are becoming an increasingly important part of the internet.

While the volume of AI requests continues to rise, Fastly says the bigger shift lies in how these systems interact with online content, applications, and business services.

Rather than viewing AI traffic simply as another form of bot activity, organizations are beginning to recognize it as a new layer of internet activity that requires its own management strategy.

AI Is Changing How Businesses Think About Web Traffic

For years, companies have focused primarily on identifying and blocking malicious bots.

Today, however, businesses face a more nuanced challenge.

Some AI systems help surface company content in AI-powered search experiences, answer customer questions, compare products, or retrieve real-time information on behalf of users. Others may place additional strain on infrastructure or access sensitive data without delivering meaningful business value.

This means organizations increasingly need to decide which AI systems should be welcomed, monitored, limited, or blocked altogether.

According to Artur Bergman, Founder and Chief Technology Officer at Fastly, the internet is entering a new era.

"AI traffic is fundamentally changing how the internet operates."

He explained that businesses are moving beyond a world where humans are the primary users of digital experiences.

"The challenge is no longer simply blocking bots, it's understanding which machine interactions should be accelerated, managed, challenged, or stopped."

Understanding the Different Types of AI Traffic

Fastly's research identifies two major categories of AI-generated traffic that organizations should understand.

AI Crawlers

AI crawlers systematically scan websites to collect information that can be used to build, train, or update AI models.

These systems typically browse large volumes of online content and operate similarly to traditional search engine crawlers, although their objectives differ.

AI Fetchers and AI Agents

AI fetchers retrieve information in response to specific user requests made through AI assistants or emerging autonomous AI applications.

These requests often involve real-time tasks such as:

• Answering user questions
• Comparing products or services
• Verifying information
• Retrieving live data
• Completing digital tasks on behalf of users

As AI assistants become more capable, fetchers are expected to play an increasingly important role in how consumers discover brands and access online information.

AI Requests Place Greater Demands on Infrastructure

The study also found that AI traffic affects backend infrastructure differently than traditional user traffic.

Based on Fastly's May 2026 data:

• More than 51% of AI requests required origin server access
• Less than 9% of human requests required origin access

This means AI-generated traffic often bypasses cached content and directly interacts with an organization's servers, potentially increasing infrastructure costs and resource usage.

Fastly also observed particularly strong growth in AI assistant activity.

Traffic associated with Claude increased by more than 555% compared with its January 2026 baseline, demonstrating how quickly AI-powered applications are scaling.

AI Traffic Management Is Becoming a Business Strategy

Fastly believes organizations should no longer treat AI traffic solely as an IT or cybersecurity issue.

Instead, decisions about AI access increasingly influence brand visibility, digital distribution, customer acquisition, and how organizations appear within AI-powered experiences.

The company observed different approaches among large enterprises.

One organization chose to block a sudden increase in AI fetcher activity, likely to retain greater control over its content.

Another allowed AI agents continued access, resulting in sustained growth in AI fetcher traffic and potentially increasing visibility across AI-powered platforms.

These contrasting strategies highlight that AI traffic decisions may directly influence how businesses are discovered in the future.

Three Elements of an Effective AI Traffic Strategy

As AI-generated internet activity continues to expand, Fastly recommends organizations build a more intentional machine traffic strategy centered around three key capabilities.

Visibility

Organizations need clear insight into which AI systems are interacting with their websites, APIs, and digital services.

Context

Understanding why AI systems access digital resources helps distinguish beneficial activity from potentially harmful or unnecessary requests.

Precision

Businesses should be able to apply different policies based on an AI system's intent, behavior, and business value rather than relying on one-size-fits-all rules.

Fastly says its edge cloud platform enables organizations to balance performance, security, bot management, and infrastructure protection while making real-time decisions about AI-generated requests.

Preparing for an AI-Driven Internet

As AI assistants and autonomous agents become increasingly integrated into everyday digital experiences, organizations will likely encounter more machine-generated interactions than ever before.

Managing these requests effectively will require more than simply blocking bots. Businesses must evaluate how AI systems influence customer discovery, online visibility, operational costs, and digital strategy.

Fastly's latest findings suggest that AI traffic is no longer an emerging trend. It is becoming a permanent part of the internet's evolution, and organizations that develop thoughtful machine traffic strategies today may be better positioned to compete in an increasingly AI-driven digital landscape.

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Saviynt Unveils AI Identity Security With Intent-Aware Runtime Authorization

Saviynt Unveils AI Identity Security With Intent-Aware Runtime Authorization

As artificial intelligence moves beyond chatbots and into autonomous agents capable of making decisions and executing tasks, organizations are facing a new cybersecurity challenge: how do you control what AI agents are allowed to do in real time?

To address this growing concern, identity security company Saviynt has introduced new capabilities for its Identity Security for AI platform, including Intent-Aware Runtime Authorization (IARA), a technology designed to monitor and control AI agent behavior while actions are taking place. The latest enhancements also strengthen identity verification to help organizations reduce impersonation and fraud risks as AI adoption accelerates.

Why AI Agents Need a New Approach to Identity Security

AI agents are becoming increasingly capable of performing complex business tasks with minimal human intervention. From accessing company applications to interacting with APIs, databases, and other AI systems, these digital workers can complete thousands of actions within seconds.

While this creates significant productivity gains, it also introduces new security concerns.

Traditional identity and access management systems were designed primarily for human users and conventional software applications. They often rely on static permissions that may not accurately assess whether an AI agent's action is appropriate in a specific situation.

As enterprises deploy AI agents into production environments, organizations need security tools that evaluate access decisions dynamically rather than relying solely on predefined permissions.

Saviynt Introduces Intent-Aware Runtime Authorization

To meet this need, Saviynt has enhanced its Agent Access Gateway with Intent-Aware Runtime Authorization (IARA).

Rather than simply checking whether an AI agent has permission to perform a task, IARA evaluates several factors at the exact moment an action is requested, including:

• The identity of the AI agent
• The surrounding context
• Organizational security policies
• The agent's intended objective

If an action falls outside approved policies or appears inconsistent with its intended purpose, the system can immediately block the request while generating an audit record for security teams.

This runtime approach allows organizations to respond to AI behavior as it happens instead of relying solely on permissions granted beforehand.

Moving Beyond Static Access Controls

According to Vibhuti Sinha, Chief Product Officer at Saviynt, AI agents should now be viewed as a new category of enterprise identity.

"AI agents are becoming a new class of enterprise identity, autonomous, powerful, and capable of taking action across critical business systems."

He explained that Agent Access Gateway enables organizations to make security decisions at the point where AI actions occur.

"With IARA, organizations can move beyond static permissions and make access decisions based on what an agent is trying to do, why it is doing it, and whether that action should be allowed."

This approach aims to give enterprises greater confidence as they automate increasingly sensitive business processes.

How Runtime Authorization Protects Business Systems

One of the biggest challenges with AI agents is that technical authorization alone does not always guarantee appropriate behavior.

For example, a sales support AI may legitimately access customer relationship management (CRM) data to summarize a sales opportunity.

However, if that same AI suddenly attempts to export customer records, alter pricing information, or initiate customer communications without approval, organizations need a way to determine whether those actions align with the user's original intent.

Saviynt's runtime authorization engine is designed to identify these mismatches instantly and stop unauthorized actions before they can impact sensitive systems or data.

Expanded Governance Across the AI Ecosystem

Alongside runtime authorization, Saviynt has expanded governance capabilities throughout its broader Identity Security for AI platform.

Organizations can now manage:

Runtime access control for AI agents

Policies can evaluate and regulate AI agent behavior dynamically while tasks are being executed.

Tool and application permissions

Security teams can define both static and adaptive policies that determine which tools, applications, APIs, and resources AI agents are permitted to use.

AI delegation tracking

The platform can distinguish whether an AI agent is acting independently, operating on behalf of a human user, or carrying out requests from another AI agent, providing greater accountability across automated workflows.

These controls help organizations enforce least-privilege access while improving visibility into autonomous AI activity.

Stronger Identity Verification to Reduce AI-Driven Fraud

As AI-generated content and impersonation techniques become increasingly sophisticated, verifying human identities is also becoming more important.

To address this, Saviynt has introduced new identity verification capabilities directly within its platform.

The enhanced verification process includes:

• Biometric scanning
• Selfie photo verification
• Liveness detection
• Support for more than 4,000 government-issued identity documents across over 177 countries

These features are designed to strengthen identity assurance during certification processes while helping reduce impersonation, unauthorized access, and social engineering attacks.

Broader Integration Across Enterprise AI Platforms

Saviynt also continues to expand compatibility across enterprise AI ecosystems.

The latest release introduces additional native integrations with platforms including:

• Microsoft Foundry
• N8N
• Snowflake Cortex

These integrations help organizations manage AI identities consistently across where agents are built, deployed, and interact with enterprise applications.

Addressing the Next Generation of AI Security Challenges

As organizations increasingly rely on autonomous AI systems, securing those systems will require more than traditional identity management.

By combining runtime authorization, AI governance, and advanced identity verification, Saviynt aims to help enterprises address two rapidly emerging security priorities: controlling AI agent behavior during execution and reducing the risk of identity impersonation.

As AI continues to reshape business operations, solutions that provide real-time visibility and policy enforcement are becoming essential for organizations seeking to innovate without compromising security.

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How Filipino Data Scientists at RELX Are Driving Global AI and Analytics Innovation

How Filipino Data Scientists at RELX Are Driving Global AI and Analytics Innovation

Sunday, June 14, 2026

The rise of artificial intelligence, predictive analytics, and data-driven decision-making has created unprecedented demand for skilled data professionals worldwide. As organizations increasingly rely on data to guide critical business, legal, scientific, and healthcare decisions, the need for talent capable of turning information into action has never been greater.

In the Philippines, one company is placing Filipino data science professionals at the forefront of this transformation. RELX | Reed Elsevier is strengthening its presence in the country as a strategic hub where local talent contributes to global innovations in analytics, AI, and decision intelligence.

From powering legal research platforms to supporting scientific discoveries and risk management solutions, Filipino teams are helping shape technologies used by millions of professionals around the world.

Filipino Talent at the Heart of Global Data Innovation

As industries become more data-centric, organizations are looking beyond technical expertise alone. They need professionals who can combine analytics, business understanding, and problem-solving skills to create practical solutions.

At RELX | Reed Elsevier, data scientists, analysts, and digital professionals in the Philippines work on high-impact projects spanning multiple industries, including:

• Legal intelligence
• Scientific research
• Risk analytics
• Healthcare solutions
• Business operations and optimization

Their work contributes directly to products and platforms that help professionals make informed decisions in environments where accuracy and reliability are essential.

Building Solutions That Create Real-World Impact

What sets data science work apart at RELX | Reed Elsevier is its direct connection to real-world applications.

Teams in the Philippines help develop and refine solutions that support legal professionals navigating complex cases, researchers accelerating scientific breakthroughs, and organizations identifying potential financial risks before they become major challenges.

This work is powered by RELX's extensive foundation of authoritative data and content, built over more than 150 years across legal, scientific, and risk intelligence sectors.

For data professionals, this means working with trusted, high-quality datasets that serve as the backbone of products relied upon by millions of users globally.

Data Science Beyond Dashboards and Reports

While data analysis often brings to mind charts, reports, and dashboards, the role of data professionals at RELX extends much further.

According to Digital Solutions Partner Rhina Jae Arcala, data becomes valuable when it uncovers opportunities and drives meaningful improvements.

"I find working with data exciting because it helps us uncover what we might otherwise overlook — hidden opportunities, unexpected patterns, and the stories behind the numbers," Arcala shared.

"It's not just about reports or dashboards; it's about driving meaningful change. When we use data to refine our processes, eliminate inefficiencies, and empower better decision-making, we're not just optimizing operations, we're opening doors for innovation and progress."

This perspective reflects a growing trend in modern data science, where success is measured not by the volume of data collected but by the value generated from it.

Why Translating Complexity Is a Critical Skill

As organizations adopt increasingly sophisticated technologies, one skill has become especially important: the ability to translate complexity into actionable solutions.

Within RELX | Reed Elsevier, data professionals are expected to bridge the gap between technical outputs and business needs.

Rather than simply building models, teams focus on ensuring insights can be understood, adopted, and applied effectively by stakeholders.

"Data science here is about translating the complex into solutions," Arcala explained.

This ability to connect data, business objectives, and operational realities often determines whether an analytics project succeeds in delivering real-world value.

Turning Insights Into Operational Efficiency

Another defining characteristic of data science work at RELX is its close connection to operational improvement.

Teams design solutions that help reduce manual effort, streamline workflows, and surface the most relevant information for decision-makers.

Examples include:

• Enhancing editorial processes
• Supporting enterprise-wide query management
• Improving workflow automation
• Delivering intelligent information retrieval
• Reducing repetitive tasks through data-driven systems

The goal is not to replace human expertise but to empower professionals to focus on higher-value activities while technology handles routine processes.

A Responsible Approach to High-Stakes Data

Working in industries such as legal intelligence, healthcare, and risk management requires more than technical accuracy. It demands responsibility, context, and trust.

At RELX | Reed Elsevier, teams are trained to begin with the decision being made rather than the technology being used.

This approach ensures that data science initiatives are aligned with real-world outcomes and consider the potential implications of how information is interpreted and applied.

In high-stakes environments, even small insights can influence important decisions, making responsible data practices a critical part of the development process.

How AI Is Reshaping the Role of Data Scientists

Artificial intelligence is transforming how data professionals work, but RELX views this evolution as an opportunity rather than a threat.

As AI tools become increasingly capable of supporting coding, analysis, and experimentation, the role of the data scientist is shifting toward higher-level decision-making and strategic thinking.

Arcala explained that AI is changing how professionals allocate their time and expertise.

"It's changing the 'center of gravity' from just producing output to producing outputs that move us toward better decisions."

In this environment, judgment, critical thinking, and business understanding become even more valuable than technical execution alone.

Investing in the Future of Data Science

To keep pace with rapidly evolving technologies, RELX | Reed Elsevier continues to invest heavily in employee development.

Teams are given access to enterprise AI platforms, advanced development environments, and structured training programs covering areas such as:

• Generative AI
• Prompt engineering
• Predictive modeling
• Responsible AI practices
• Advanced analytics
• Machine learning development

These learning opportunities are reinforced through collaboration with global teams, allowing Filipino professionals to exchange knowledge and contribute to international projects.

The Philippines as a Growing Analytics and AI Hub

The Philippines continues to strengthen its reputation as a destination for high-value technology, analytics, and AI work. As businesses around the world accelerate their digital transformation efforts, Filipino professionals are playing an increasingly important role in shaping the future of data-driven innovation.

At RELX | Reed Elsevier, that contribution goes beyond supporting global systems. Local teams are actively helping design, improve, and scale solutions that influence how professionals make decisions across industries worldwide.

By combining deep domain expertise, responsible innovation, and continuous learning, the company is creating an environment where Filipino data scientists can thrive while contributing to some of today's most important technological advancements.

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TP Philippines Says AI Success Depends on Execution, Not Just Technology

TP Philippines Says AI Success Depends on Execution, Not Just Technology

Artificial intelligence is no longer a future concept. Today, businesses across industries are investing heavily in AI tools, platforms, and automation solutions in hopes of improving efficiency, reducing costs, and delivering better customer experiences.

But as AI adoption accelerates, one question remains: Why do some organizations achieve meaningful results while others struggle to unlock real value?

According to TP in the Philippines, the answer lies not in access to technology but in the ability to execute. During the recent GenAI Summit Philippines 2026, the company highlighted how operational expertise, strategic implementation, and orchestration capabilities are becoming the true differentiators in the AI era.

The Real AI Advantage Is Execution

Many businesses now have access to the same generative AI platforms, large language models, and automation technologies. However, simply deploying AI tools does not automatically translate into business success.

Speaking at the GenAI Summit Philippines 2026, Vishnu Raj, Vice President for AI at TP in the Philippines, emphasized that organizations need what he calls "execution muscle" to transform AI investments into measurable outcomes.

"Everyone has access to the same technologies today, but not everyone has the same processes and expertise," Raj explained.

He noted that orchestration intelligence has become increasingly important as businesses seek to integrate AI into real-world operations.

"The real differentiator is orchestration intelligence. At TP, we have decades of domain expertise, and rich and deep experience in AI, both in deployment and optimization, to maximize value in every customer interaction. Our orchestration capabilities ensure that AI isn't just a tool, but a driver of specific business outcomes."

Operational Expertise in AI Deployment

As organizations race to adopt AI, many overlook the operational challenges that come with implementation.

Raj explained that TP's extensive experience in customer experience management gives the company a unique advantage when identifying where AI can create the most value across the customer journey.

Rather than treating AI as a standalone technology, TP focuses on integrating automation into existing workflows while maintaining smooth collaboration between AI systems and human agents.

This operational perspective helps ensure that AI initiatives are aligned with business objectives, customer expectations, and measurable performance outcomes.

TP Showcases AI-Powered Customer Experience Solutions

One of the highlights of TP's presentation was a live demonstration of an AI-powered customer service agent designed to manage multiple stages of the customer support journey.

The solution demonstrated the ability to:

• Identify customer concerns and requests
• Authenticate customer information
• Perform troubleshooting tasks
• Detect upselling and cross-selling opportunities
• Recommend relevant offers
• Escalate complex cases to human representatives when needed

The technology is powered by TP's proprietary Foundational AI Backbone framework, which enables seamless coordination between AI agents and human support teams.

The result is a more efficient and connected customer experience that balances automation with personalized service.

The Role of the TP.ai FAB Solution Suite

At the center of TP's AI strategy is its TP.ai FAB Solution Suite, which brings together multiple technologies to support enterprise-scale customer engagement.

During the summit, Raj demonstrated how the company orchestrates a combination of autonomous AI agents, machine learning systems, large language models, and customer relationship management (CRM) platforms to deliver end-to-end support experiences.

This integrated approach allows organizations to streamline operations while maintaining service quality across customer touchpoints.

By connecting different AI capabilities within a unified framework, businesses can improve responsiveness, increase efficiency, and create more seamless interactions.

Human Expertise Still Plays a Critical Role

Despite the rapid advancement of AI, TP maintains that human oversight remains essential.

Raj emphasized that successful AI implementation requires close collaboration with frontline teams who understand customer behavior and operational realities.

"We work closely with the people on the production floor, the agents, quality analysts, and subject matter experts who understand customer concerns deeply," Raj said.

"That operational knowledge is critical in identifying where AI can deliver the greatest value, including the objective of reducing the total cost of operations."

This combination of technology and human expertise helps organizations deploy AI responsibly while ensuring that sensitive or complex customer interactions continue to receive appropriate support.

A Phased Approach to Scaling AI

Another key takeaway from TP's presentation was the importance of adopting AI gradually rather than attempting large-scale deployment all at once.

Raj outlined a phased implementation strategy that begins with high-volume, lower-complexity interactions before expanding into more sophisticated use cases.

This approach allows organizations to generate measurable returns sooner while minimizing operational risk.

By proving value early, businesses gain the confidence and insights needed to scale AI initiatives more effectively across the organization.

The Future of AI Is About Outcomes

As generative AI becomes increasingly accessible, competitive advantage will depend less on the technology itself and more on how organizations apply it.

TP in the Philippines believes that successful AI transformation requires a combination of advanced technology, operational expertise, strategic orchestration, and human oversight.

By leveraging decades of experience in customer experience management and AI deployment, the company continues to help brands navigate digital transformation while creating customer experiences that are simpler, faster, and safer.

As discussions at the GenAI Summit Philippines 2026 demonstrated, the future of AI is not just about innovation. It is about execution, measurable outcomes, and the ability to turn technology into real business value.

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