Daily Tech Digest - May 12, 2025


Quote for the day:

"Our greatest fear should not be of failure but of succeeding at things in life that don't really matter." -- Francis Chan



The rise of vCISO as a viable cybersecurity career path

Companies that don’t have the means to hire a full-time CISO still face the same harsh realities their peers do — heightened compliance demands, escalating cyber incidents, and growing tech-related risks. A part-time security leader can help them assess their state of security and build out a program from scratch, or assist a full-time director-level security leader with a project. ... In some of these ongoing relationships this could be to fill the proverbial chair of the CISO, doing all the traditional work of the role on a part-time basis. This is the kind of arrangement most likely to be referred to as a fractional role. Other retainer arrangements may just be for an advisory position where the client is buying regular mindshare of the vCISO to supplement their tech team’s knowledge pool. They could be a strategic sounding board to the CIO or even a subject-matter expert to the director of security or newly installed CISO. But vCISOs can work on a project-by-project or hourly basis as well. “It’s really what works best for my potential client,” says Demoranville. “I don’t want to force them into a box. So, if a subscription model works or a retainer, cool. If they only want me here for a short engagement, maybe we’re trying to put in a compliance regimen for ISO 27001 or you need me to review NIST, that’s great too.”


Why Indian Banks Need a Sovereign Cloud Strategy

Enterprises need to not only implement better compliance strategies but also rethink the entire IT operating model. Managed sovereign cloud services can help enterprises address this need. ... The need for true sovereignty becomes crucial in a world where many global cloud providers, even when operating within Indian data centers, are subject to foreign laws such as the U.S. Clarifying Lawful Overseas Use of Data Act or the Foreign Intelligence Surveillance Act. These regulations can compel disclosure of Indian banking data to overseas governments, undermining trust and violating the spirit of data localization mandates. "When an Indian bank chooses a global cloud provider with U.S. exposure, they're essentially opening a backdoor for foreign jurisdictions to access sensitive Indian financial data," Rajgopal said. "Sovereignty is a strategic necessity." Managed sovereign clouds not only align with India's compliance frameworks but also reduce complexity by integrating regulatory controls directly into the cloud stack. Instead of treating compliance as an afterthought, it is incorporated in the architecture. ... "Banks today are not just managing money; they are managing trust, security and compliance at unprecedented levels. Sovereign cloud is no longer optional. It's the future of financial resilience," said Pai.


Study Suggests Quantum Entanglement May Rewrite the Rules of Gravity

Entanglement entropy measures the degree of quantum correlation between different regions of space and plays a key role in quantum information theory and quantum computing. Because entanglement captures how information is shared across spatial boundaries, it provides a natural bridge between quantum theory and the geometric fabric of spacetime. In conventional general relativity, the curvature of spacetime is determined by the energy and momentum of matter and radiation. The new framework adds another driver: the quantum information shared between fields. This extra term modifies Einstein’s equations and offers an explanation for some of gravity’s more elusive behaviors, including potential corrections to Newton’s gravitational constant. ... One of the more striking implications involves black hole thermodynamics. Traditional equations for black hole entropy and temperature rely on Newton’s constant being fixed. If gravity “runs” with energy scale — as the study proposes — then these thermodynamic quantities also shift. ... Ultimately, the study does not claim to resolve quantum gravity, but it does reframe the problem. By showing how entanglement entropy can be mathematically folded into Einstein’s equations, it opens a promising path that links spacetime to information — a concept familiar to quantum computer scientists and physicists alike.


Maximising business impact: Developing mission-critical skills for organisational success

Often, L&D is perceived merely as an HR-led function tasked with building workforce capabilities. However, this narrow framing extensively limits its potential impact. As Cathlea shared, “It’s time to educate leaders that L&D is not just a support role—it’s a business-critical responsibility that must be shared across the organisation. By understanding what success looks like through the eyes of different functions, L&D teams can design programmes that support those ambitions — and crucially, communicate value in language that business leaders understand. The panel referenced a case from a tech retailer with over 150,000 employees, where the central L&D team worked to identify cross-cutting capability needs, such as communication, project management, and leadership, while empowering local departments to shape their training solutions. This balance of central coordination and local autonomy enabled the organisation to scale learning in a way that was both relevant and impactful. ... The shift towards skill-based development is also transforming how learning experiences are designed and delivered. What matters most is whether these learning moments are recognised, supported, and meaningfully connected to broader organisational goals.


What software developers need to know about cybersecurity

Training developers to write secure code shouldn’t be looked at as a one-time assignment. It requires a cultural shift. Start by making secure coding techniques are the standard practice across your team. Two of the most critical (yet frequently overlooked) practices are input validation and input sanitization. Input validation ensures incoming data is appropriate and safe for its intended use, reducing the risk of logic errors and downstream failures. Input sanitization removes or neutralizes potentially malicious content—like script injections—to prevent exploits like cross-site scripting (XSS). ... Authentication and authorization aren’t just security check boxes—they define who can access what and how. This includes access to code bases, development tools, libraries, APIs, and other assets. ... APIs may be less visible, but they form the connective tissue of modern applications. APIs are now a primary attack vector, with API attacks growing 1,025% in 2024 alone. The top security risks? Broken authentication, broken authorization, and lax access controls. Make sure security is baked into API design from the start, not bolted on later. ... Application logging and monitoring are essential for detecting threats, ensuring compliance, and responding promptly to security incidents and policy violations. Logging is more than a check-the-box activity—for developers, logging can be a critical line of defense.


Why security teams cannot rely solely on AI guardrails

The core issue is that most guardrails are implemented as standalone NLP classifiers—often lightweight models fine-tuned on curated datasets—while the LLMs they are meant to protect are trained on far broader, more diverse corpora. This leads to misalignment between what the guardrail flags and how the LLM interprets inputs. Our findings show that prompts obfuscated with Unicode, emojis, or adversarial perturbations can bypass the classifier, yet still be parsed and executed as intended by the LLM. This is particularly problematic when guardrails fail silently, allowing semantically intact adversarial inputs through. Even emerging LLM-based judges, while promising, are subject to similar limitations. Unless explicitly trained to detect adversarial manipulations and evaluated across a representative threat landscape, they can inherit the same blind spots. To address this, security teams should move beyond static classification and implement dynamic, feedback-based defenses. Guardrails should be tested in-system with the actual LLM and application interface in place. Runtime monitoring of both inputs and outputs is critical to detect behavioral deviations and emergent attack patterns. Additionally, incorporating adversarial training and continual red teaming into the development cycle helps expose and patch weaknesses before deployment. 


Finding the Right Architecture for AI-Powered ESG Analysis

Rather than choosing between competing approaches, we developed a hybrid architecture that leverages the strengths of both deterministic workflows and agentic AI: For report analysis: We implemented a structured workflow that removes the Intent Agent and Supervisor from the process, instead providing our own intention through a report workflow. This orchestrates the process using the uploaded sustainability file, synchronously chaining prompts and agents to obtain the company name and relevant materiality topics, then asynchronously producing a comprehensive analysis of environmental, social, and governance aspects. For interactive exploration: We maintained the conversational, agentic architecture as a core component of the solution. After reviewing the initial structured report, analysts can ask follow-up questions like, “How does this company’s emissions reduction claims compare to their industry peers?” ... By marrying these approaches, enterprise architects can build systems that maintain human oversight while leveraging AI to handle data-intensive tasks – keeping human analysts firmly in the driver’s seat with AI serving as powerful analytical tools rather than autonomous decision-makers. As we navigate the rapidly evolving landscape of AI implementation, this balanced approach offers a valuable pathway forward.


The Rise of xLMs: Why One-Size-Fits-All AI Models Are Fading

To reach its next evolution, the LLM market will follow all other widely implemented technologies and fragment into an “xLM” market of more specialized models, where the x stands for various models. Language models are being implemented in more places with application- and use case-specific demands, such as lower power or higher security and safety measures. Size is another factor, but we’ll also see varying functionality and models that are portable, remote, hybrid, and domain and region-specific. With this progression, greater versatility and diversity of use cases will emerge, with more options for pricing, security, and latency. ... We must rethink how AI models are trained to fully prepare for and embrace the xLM market. The future of more innovative AI models and the pursuit of artificial general intelligence hinge on advanced reasoning capabilities, but this necessitates restructuring data management practices. ... Preparing real-time data pipelines for the xLM age inherently increases pressure on data engineering resources, especially for organizations currently relying on static batch data uploads and fine-tuning. Historically, real-time accuracy has demanded specialized teams to complete regular batch uploads while maintaining data accuracy, which presents cost and resource barriers. 


Ernst & Young exec details the good, bad and future of genAI deployments

“There is a huge skills gap in data science in terms of the number of people that can do that well, and that is not changing. Everywhere else we can talk about what jobs are changing and where the future is. But AI scientists, data scientists, continue to be the top two in terms of what we’re looking for. I do think organizations are moving to partner more in terms of trying to leverage those skills gap….” The more specific the case for the use of AI, the more easily you can calculate the ROI. “Healthcare is going to be ripe for it. I’ve talked to a number of doctors who are leveraging the power of AI and just doing their documentation requirements, using it in patient booking systems, workflow management tools, supply chain analysis. There, there are clear productivity gains, and they will be different per sector. “Are we also far enough along to see productivity gains in R&D and pharmaceuticals? Yes, we are. Is it the Holy Grail? Not yet, but we are seeing gains and that’s where I think it gets more interesting. “Are we far enough along to have systems completely automated and we just work with AI and ask the little fancy box in front of us to print out the balance sheet and everything’s good? No, we’re a hell of a long way away from that.


How Human-Machine Partnerships Are Evolving in 2025

“Soon, there will be no function that does not have AI as a fundamental ingredient. While it’s true that AI will replace some jobs, it will also create new ones and reduce the barrier of entry into many markets that have traditionally been closed to just a technical or specialized group,” says Bukhari. “AI becoming a part of day-to-day life will also force us to embrace our humanity more than ever before, as the soft skills AI can’t replace will become even more critical for success in the workplace and beyond.” ... CIOs and other executives must be data and AI literate, so they are better equipped to navigate complex regulations, lead teams through AI-driven transformations and ensure that AI implementations are aligned with business goals and values. Cross-functional collaboration is also critical. ... AI innovation is already outpacing organizational readiness, so continuous learning, proactive strategy alignment and iterative implementation approaches are important. CIOs must balance infrastructure investments, like GPU resource allocation, with flexibility in computing strategies to stay competitive without compromising financial stability. “As the enterprise landscape increasingly incorporates AI-driven processes, the C-suite must cultivate specific skills that will cascade effectively through their management structures and their entire human workforce,” says Miskawi. 


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