We are witnessing in real time as AI fundamentally changes how people work across every industry. Customer support agents can respond to ten times the tickets. Software engineers are reviewers of AI generated code instead of spending hours pounding out boiler plate code. Salespeople can get back to focusing on building relationships instead of tedious follow up and administration.
This technology feels magical, and Cloudflare is committed to helping companies build world class AI-driven experiences for their employees and customers.
There is a but, however. Any time a brand new technology with such widespread appeal emerges, the technology often outpaces the tools in place to govern, secure and control the technology. We’re already starting to see stories of vibe coded apps leaking all their users’ details. LLM chats that were intended to only be shared between colleagues, are actually out on the web, being indexed by search engines for all the world to see. AI Agents are being given the keys to the application kingdom, enabling them to work autonomously across an organization — but without proper tracking and control. And then there’s the risk of a well-meaning employee uploading confidential company or customer data into an LLM, which then uses it to train future models.
Beyond internal data used for LLM training, content creators and media companies are also faced with a decision about how they want LLM scrapers and information retrieval bots to interact with their content. Cloudflare has found that it can be hundreds, or even thousands, of times harder to generate site traffic (and therefore ad revenue) from an AI response versus a search engine result.
We’re hearing more and more of these stories from CISOs, CIOs, Creators, and even CEOs. These leaders are faced with a difficult choice: clamping down on all AI usage and bots — or letting them run wild. There needs to be something in between. And for that to be a real option, the tools to manage and secure AI need to catch up to AI itself.
This week, that’s what Cloudflare is focused on. Welcome to AI Week! Over the coming week, we will focus on four core areas to help companies secure and deliver AI experiences safely and securely:
Securing AI environments and workflows: AI is incredibly powerful. The problem is, innovation is outpacing control — we want to change that. And as one of the few zero trust providers also building out AI infrastructure for the web, we’re uniquely positioned to be able to do so.
Protecting original content from misuse by AI: AI Companies are devouring organic content as quickly as it’s created… and creators aren’t seeing any benefit. We want to give content creators control over the content that they have worked so hard to develop.
Helping developers build world-class, secure, AI experiences: the possibilities for developers to create new applications on top of (or even building with) AI are endless. We want to allow developers to create AI driven applications that are as close to users as possible, with security controls built-in from day one.
Making Cloudflare better for you with AI: AI is changing the nature of interfaces. For example, finding and mitigating issues buried in thousands and millions of logs and events across website, employee, and email usage is something that used to be tedious — but now with AI, it can be made easy. We’re working day and night to integrate AI into Cloudflare itself to make things more efficient for ourselves and our customers.
Securing AI environments and workflows
As Artificial Intelligence innovation continues to accelerate at an unprecedented pace, the speed of its development is increasingly outpacing the implementation of robust security controls. This rapid advancement, while promising immense benefits, simultaneously introduces novel and complex security challenges that traditional measures are often ill-equipped to address. Organizations are finding themselves grappling with the inherent risks of adopting powerful AI tools without adequate safeguards, leading to vulnerabilities such as Shadow AI and the uncontrolled proliferation of AI models, making the development of specialized AI security paramount.
As we look around the zero trust space, none of the other providers are moving fast enough to keep up with AI’s pace of innovation. This is something we know a thing or two about — and after this week, if you’re worried about governing AI usage inside your organization, we will have you covered.
We will be announcing new and powerful controls to detect Shadow AI and control unauthorized AI usage. Additionally, we’ve built options for teams to establish the “paved path” of AI tooling in an organization to supercharge employee productivity without sacrificing security. Finally, we’ll be announcing new ways of protecting your own models from poisoning or attacks.
Protecting original content from AI
The explosion of Large Language Models (LLMs) has also created a new challenge for content creators: the unauthorized scraping and training of their valuable content. Cloudflare recognizes the critical need for creators to maintain control over their intellectual property. That’s why we’ve introduced Crawl Control, a groundbreaking initiative designed to empower content owners to manage how their content is accessed and used by AI models.
In the past two months, we’ve seen incredible progress with Crawl Control. We’ve significantly expanded the number of participating content providers, allowing more creators to leverage this innovative protection. We’ve also refined our detection mechanisms to more accurately identify AI crawlers and ensure that only authorized access occurs. Furthermore, we’ve streamlined the integration process, making it easier for new publishers to onboard and begin protecting their content within minutes. Our goal remains to provide content creators with the tools they need to thrive in the age of AI, ensuring they are compensated and acknowledged for the content they produce.
Helping you build world-class, secure, AI experiences
We believe that AI experiences should have security controls by default. This is why we are heavily investing in both our developer platform’s AI Gateway and the associated security controls for those products. This two pronged approach allows developers to iterate and test new ideas without the fear of painful or embarrassing security issues.
The Cloudflare AI Gateway allows developers to deploy AI-driven applications with unparalleled speed and efficiency, ensuring that these applications are as close to end-users as possible. This proximity minimizes latency and maximizes performance, delivering a seamless and responsive user experience that is critical in today’s fast-paced digital landscape.
This week, we’re announcing significant enhancements to the AI Gateway, further solidifying its position as the premier platform for AI application deployment. These improvements include advanced caching mechanisms that reduce redundant model calls, leading to faster response times and lower operational costs. We are also introducing expanded observability features, providing developers with deeper insights into their AI model’s performance and usage patterns, which will enable more effective debugging and optimization. Furthermore, new integrations with popular AI frameworks and services will simplify the development workflow, allowing developers to leverage the AI Gateway’s benefits with even greater ease. Our commitment is to provide developers with the tools to innovate and deliver cutting-edge AI experiences to their users.
Making Cloudflare better with AI
We’re integrating AI across our entire product suite to enhance the Cloudflare experience itself. From intelligent threat detection that adapts to emerging attack patterns, to AI-powered optimizations that fine-tune network performance, our goal is to leverage AI to make our platform more intuitive, efficient, and secure. We envision a future where Cloudflare’s products proactively anticipate user needs, automate complex tasks, and deliver unparalleled insights, all powered by seamlessly embedded AI. This commitment to internal AI integration ensures that as the digital landscape evolves, Cloudflare remains at the forefront of innovation, continuously delivering superior value to our users.
We cannot wait to share these updates and announcements with you. Follow our AI Week hub page for all the latest releases from our blog and CloudflareTV.
FILE PHOTO: Nvidia said it would launch a new AI chip by the end of next year, designed to handle complex functions like creating videos and software.
| Photo Credit: Reuters
Nvidia said on Tuesday it would launch a new artificial intelligence chip by the end of next year, designed to handle complex functions such as creating videos and software.
The chips, dubbed “Rubin CPX”, will be built on Nvidia’s next-generation Rubin architecture — the successor to its latest “Blackwell” technology that marked the company’s foray into providing larger processing systems.
As AI systems grow more sophisticated, tackling data-heavy tasks such as “vibe coding” or AI-assisted code generation and video generation, the industry’s processing needs are intensifying.
AI models can take up to 1 million tokens to process an hour of video content — a challenging feat for traditional GPUs, the company said. Tokens refer to the units of data processed by an AI model.
To remedy this, Nvidia will integrate various steps of the drawn-out processing sequence such as video decoding, encoding, and inference — when AI models produce an output — together into its new chip.
Investing $100 million in these new systems could help generate $5 billion in token revenue, the company said, as Wall Street increasingly focuses on the return from pouring hundreds of billions of dollars into AI hardware.
The race to develop the most sophisticated AI systems has made Nvidia the world’s most valuable company, commanding a dominant share of the AI chip market with its pricey, top-of-the-line processors.
As AI evolves from simple automation to sophisticated autonomous agents, HR executives face one of the most significant workforce transformations in modern history. The challenge isn’t just understanding the technology — it’s navigating culture change, skills development and workforce planning when AI capabilities double every six months.
Simon Brown, EY’s global learning and development leader, has spent nearly 2 years helping the firm’s 400,000 employees prepare for an AI-driven future. With his past experience as chief learning officer at Novartis and his work with Microsoft, Brown offers critical insights on positioning organizations for success in an autonomous AI world.
What are the top questions C-suite executives need to ask their teams about agentic AI initiatives?
Are people aware of what’s possible with agents? Are we experimenting to find ways agents can help us? Do we have the skills and knowledge to do that properly?
But the most critical question is: Is the culture there to support this? Most organizations are feeling their way through which tools work, what the use cases are, what drives value. There’s a lot of ambiguity. Some organizations manage well through uncertainty; others need clear answers and can’t fail — that’s hard when there’s no clear path and people need to experiment.
How can leaders assess whether their organization has the right culture for agentic AI?
Look at how AI tools like Microsoft Copilot are being embraced. Are people experimenting and finding productivity value, or are they threatened and not using it? If leaders are role modeling use and encouraging their people, that comes through in adoption metrics. Culture shows through communication, leadership role modeling, skill building and time to learn.
What are common blind spots when executives evaluate AI readiness?
Two major issues. First, executives often aren’t aware of what’s possible with the latest AI systems due to security constraints and procurement processes that create 6-to-12-month lags.
Second, the speed of improvement. If I tried an AI tool a month ago versus today, I may get a completely different experience because the underlying model improved. Copilot now has GPT-5 access, giving it a significant overnight boost. Leaders need to shift from thinking about AI as static systems upgraded annually to something constantly improving and doubling in power every six months.
How should leaders approach change management with AI agents?
Change management is essential. When OpenAI releases new capabilities, everyone has access to the technology. Whether organizations get the benefit depends entirely on change management — culture, experimentation ability, skills and whether people feel encouraged rather than fearful. We’re addressing this through AI badges, curricula, enterprise-wide learning — all signaling the organization values building AI skills.
What’s your framework for evaluating whether AI investment will drive real business value?
I think about three loops. First, can I use this to do current tasks cheaper, faster, better? Second, can I realize new value — serving more customers, new products and services? Third, if everyone’s using AI, how do we reinvent ourselves to create new value? It’s moving beyond just doing the same things better to what AI helps us do differently.
How should HR leaders rethink workforce planning given AI’s potential to automate job functions?
Understand which skills AI will impact, which remain uniquely human and what new roles get created. The World Economic Forum predicts significant reduction in certain roles but net increase overall. We’re seeing new, more sophisticated roles created that move people higher up the value chain.
From HR’s perspective, are our processes still fit for AI speed? How are we incentivizing reskilling? Are we ensuring learning access and time? How are we signaling which skills are in demand versus at risk of automation?
How should HR measure success after implementing agentic AI?
Tie back to why it was implemented — business value. Use similar metrics as before but look at what changed. Maybe same output but cheaper, faster, better. Or new capabilities — our third-party risk team uses agents to provide much more extensive supplier analysis than before. Same team size, more client value.
What’s your timeline perspective on when agentic AI becomes competitive necessity versus advantage?
That’s the ultimate question. I’m amazed daily by what I achieve using AI and agents. ChatGPT-5’s recent capabilities are mind-blowing, suggesting dramatic impact quickly. But when deep AI experts have vastly different views — from AGI around the corner to decades away — it’s understandable why leaders struggle to navigate this landscape.
