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"The only way to achieve the impossible is to believe it is possible." -- Charles Kingsleigh

When will browser agents do real work?

Vision-based agents treat the browser as a visual canvas. They look at screenshots, interpret them using , and output low-level actions like “click (210,260)” or “type “Peter Pan”.” This mimics how a human would use a computer—reading visible text, locating buttons visually, and clicking where needed. ... DOM-based agents, by contrast, operate directly on the Document Object Model (DOM), the structured tree that defines every webpage. Instead of interpreting pixels, they reason over textual representations of the page: element tags, attributes, ARIA roles, and labels. ... Running a browser agent once successfully doesn’t mean it can repeat the task reliably. The next frontier is learning from exploration: transforming first-time behaviors into reusable automations. A promising strategy starting to be deployed more and more is to let agents explore workflows visually, then encode those paths into structured representations like or code. ... With new large language models excelling at writing and editing code, these agents can self-generate and improve their own scripts, creating a cycle of self-optimization. Over time, the system becomes similar to a skilled worker: slower on the first task, but exponentially faster on repeat executions. This hybrid, self-improving approach—combining vision, structure, and code synthesis—is what makes browser automation increasingly robust.

Security Degradation in AI-Generated Code: A Threat Vector CISOs Can’t Ignore

LLMs have been a boon for developers since OpenAI’s was publicly released in November 2022, followed by other AI models. Developers were quick to utilize the tools, which significantly increased productivity for overtaxed development teams. However, that productivity boost came with security concerns, such as AI models trained on flawed code from internal or publicly available repositories. Those models introduced vulnerabilities that sometimes spread throughout the entire software ecosystem. One way to address the problem was by using LLMs to make iterative improvements to code-level security during the development process, under the assumption that LLMs, given the job of correcting mistakes, would amend them. The study, however, turns that assumption on its head. Although previous studies (and extensive real-world experience, including our own data) have demonstrated that an LLM can introduce vulnerabilities in the code it generates, this study went a step further, finding that iterative refinement of code can introduce new errors. ... The security degradation introduced in the feedback loop raises troubling questions for developers, tool designers and . The answer to those questions, the authors write, involves human intervention. Developers, for instance, must maintain control of the development process, viewing AI as a collaborative assistant rather than an autonomous tool.

Are We in the Quantum Decade?

It would be prohibitively expensive even for a Fortune 100 company to own, operate and maintain its own . It would require a quantum ecosystem that includes government, academia and industry entities to make it accessible to an enterprise. In most cases, the push and funding could come from the government or through cooperation among nations. Historically, new computing technology was rented and used as a service. Compute resources financed by government were booked in advance. Processing occurred in batches using resource-sharing techniques such as . Equivalent models are expected for quantum processing. ... The era of looms large, but enterprises and IT teams should be thinking about it today. Infrastructure needs to be deployed and algorithms need to be written for executing business use cases. "For several years to come, CIOs may not have much to do with quantum computing. But they need to know what it is, what it can do and how much it costs," said Lawrence Gasman, president of . "Quantum networks and cybersecurity will become necessary for secure communications by 2030 or even earlier." Quantum computing will not replace classical computing, but data center providers need to be thinking about how they will integrate the two architectures using interconnects like co-packaged optics.

When Data Gravity Meets Disaster Recovery

Data starts to pull everything else toward it: apps, analytics, integrations, even people and processes, the more it aggregates in one place. That environment becomes a tightly woven web of dependencies, over time. While it may be fine for day-to-day operations, it becomes a nightmare when something breaks. At that point, DR turns into a delicate task of relocating an entire ecosystem, not just a matter of simply copying files. You have to think about relationships, which systems rely on which datasets, how permissions are mapped, and how applications expect to find what they need. Of course, the bigger that web gets, the heavier the “gravitational field.” Moving petabytes of interconnected data across regions or clouds isn’t fast or easy. It takes time, bandwidth, and planning, and every extra gigabyte adds friction – in other words, the more gravity your data has, the harder it is to recover from disaster quickly. ... To push back against gravity, organizations are rethinking their architectures. Instead of forcing all data into one environment, they’re distributing it intelligently, keeping mission-critical workloads close to where they’re created, while replicating copies to nearby or complementary environments for protection. Hybrid and have become the go-to solution for this. They blend the best of both worlds: the low-latency performance of local infrastructure with the flexibility and geographic reach of cloud storage.

What’s Driving the EU’s AI Act Shake-Up?

The move to revise the AI Act follows sustained lobbying from US tech giants. In October, the Computer and Communications Industry Association (CCIA), whose members include , launched a campaign pushing for simplification not only of the AI Act but of the EU’s entire digital rulebook. Meanwhile, EU officials have reportedly engaged with the Trump administration on these issues. ... The potential delay reflects pressure from national authorities. Denmark and Germany have both pushed for a one-year extension. A spokesperson from Germany’s Federal Ministry for Digital Transformation and Government Modernization said that a delay “would allow sufficient time for the practical application of European standards by AI providers, with standards still currently being elaborated.” ... Another major reform under consideration is expanding and centralizing oversight powers within the Commission’s AI Office. Currently responsible for general-purpose AI models (GPAI), the office would gain new authority to oversee all AI systems based on GPAI and conduct conformity assessments for certain high-risk systems. The Commission would also gain new authority to perform conformity assessments for certain high-risk systems and supervise online services deemed to pose “systemic risk” under the . This would shift more power to Brussels and expand the mandate of the Commission’s AI Office beyond its current role supervising GPAI.

BITS & BYTES : The Foundational Lens for Enterprise Transformation

BITS serves as high-level strategic governance—ensuring balanced maturity assessments across business alignment, information-centric decision-making, technology enablement, and security resilience—while leveraging BDAT’s detailed sub-domains (layers and components) for tactical implementation and operational oversight. This allows organizations to maintain BDAT’s precision in decomposing complex IT landscapes (e.g., mapping specific data architectures or application portfolios) within BITS’s overarching pillars, fostering adaptive governance that scales from atomic “bits” of change to enterprise-wide transformations ... If BITS defines what must be managed, BYTES (Balanced Yearly Transformation to Enhance Services) define how change must be processed. BYTES is more than a set of principles; it is a derivative of the core architectural lifecycle: Plan (Balanced Yearly), Design& Build (Transformation Enhancing) , and Run (Services). Each component of BYTES directly maps to the mandatory stages of a continuous transformation framework, enabling architects to manage change at its source. ... The BITS & BYTES framework is not intended to replace existing architecture frameworks (e.g., ). Instead, it acts as a meta-framework—a simplified, high-level matrix that accommodates and contextualizes the applicability of all existing models.

Unlocking GenAI and Cloud Effectiveness With Intelligent Archiving

Unlike tiering, which functions like a permanent librarian selectively fetching individual files from deep storage, true archiving is a one-time event that moves files based on defined policies, such as last access or modification date. Once archived, files are stored on a long-term platform and remain accessible without reliance on any intermediary system or application. In this context, one of the main challenges is that most enterprise data is unstructured, including everything from images and videos to emails and social media content. Collectively, these vast and diverse data lakes present a formidable management challenge, and without rigorous control, organizations risk falling victim to the classic “garbage in, garbage out” problem. ... Modern archiving technologies that connect directly to both primary and archive storage platforms eliminate the need for a middleman, drastically improving migration speed, accuracy, and long-term data accessibility. This means organizations can migrate only what’s necessary, ensuring high-value data is cloud-ready while offloading cold data to cost-efficient archival platforms. This not only reduces cloud storage costs but also supports the adoption of cloud-native formats, enabling greater scalability and performance for active workloads. ... For modern enterprises, where more than 60% of enterprise data is typically inactive and often goes untouched for years, organizations are still consuming high-performance (and high-cost) storage.

Why 60% of BI Initiatives Fail (and How Enterprises Can Avoid It)

Many fail because goals and outcomes aren’t clearly defined. While enterprises may be confident that they understand BI gaps, often their goals are vague, lacking proper detailing and no internal consensus. ... Poor project management practices, vague processes, and changing responsibilities create even more confusion. In many failed BI projects, BI is viewed as “just another IT initiative,” whereas it should be treated as part of a business transformation program. Without active sponsorship and accountability, the technology may be delivered, but its adoption and impact suffer. ... Agile and iterative methods are often preferred since they are effective for BI. Whereas, the is not recommended for BI projects since it lacks the necessary agility to adapt to changing requirements, iterative data exploration, and continuous business feedback. Under the waterfall approach, the users are engaged only in the beginning of the project and during the end, which leaves gaps for development or data analysis incase of issues. ... A system is only as good as the users who use it; research has shown that 55% of users lack confidence in BI tools due to insufficient training. Enterprises often expend considerable resources on deployment, but neglect enablement. If employees can’t find how to navigate dashboards, understand the data quality, data visualizations, or use insights to make daily decisions, the adoption rates suffer.

Authentication in the age of AI spoofing

Unlike traditional malware, which may find its way into networks through a compromised software update or downloads, utilize machine learning to analyze how employees authenticate themselves to access networks, including when they log in, from which devices, typing patterns and even mouse movements. The AI learns to mimic legitimate behavior while collecting login credentials and is ultimately deployed to evade basic detection. ... Beyond the statistics, AI’s effectiveness is driven by its exponentially improving abilities to — replicating writing style, voice cadence, facial expressions or speech with subtle nuance and adding realistic context by scanning social media and other publicly available references. The data is striking and reflects the crucial need for a multi-layer approach to help sidestep the exponentially escalating ability for AI to trick humans. ... Cryptographic protection complements biometric authentication, which verifies “Is this the right person?” at the device level, while passkeys are used to verify “Is this the right website or service?” at the network level. Multi-modal biometrics, such as plus or biometrics plus , further strengthen this approach. As AI-powered attacks make credential theft and impersonation attacks more sophisticated, the only sustainable line of defense is a form of authentication that cannot be tricked or must be cryptographically verified.

Why your security strategy is failing before it even starts

The biggest mistake I see among organizations is initiating cybersecurity efforts with technology rather than prioritizing risk and business alignment. Cybersecurity is often mischaracterized as a technical issue, when in reality it’s a business risk management function. Failure to establish this connection early often results in fragmented decision-making and limited executive engagement. Effective cybersecurity strategies should be embedded into business objectives from the outset. This requires identifying the business’s critical assets, assessing potential threats and motivations, and evaluating the impact of assets becoming compromised. Too often, CISOs jump straight into acquiring cybersecurity tools without addressing these questions. ... First, the threat landscape shifted dramatically. Cybersecurity attacks today target . In food manufacturing, those systems run production lines, refrigeration, and safety processes. A cyber incident in these areas extends beyond data loss, it can disrupt production and even compromise food safety, introducing a far more complex level of risk. Second, it became evident to me that cybersecurity cannot operate in isolation. It must support and enable business operations and growth. Today, my approach is risk-based and aligned with our business prioritizes, while still built on . We focus on resilience, not just compliance, and OT security is a core pillar of that strategy.

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Daily Tech Digest - November 14, 2025