Daily Tech Digest by Kannan Subbiah: cyber crime

Showing posts with label cyber crime. Show all posts

Daily Tech Digest - May 05, 2026

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

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Duration: 25 mins • Perfect for listening on the go.

The fake IT worker problem CISOs can’t ignore

The article "The fake IT worker problem CISOs can’t ignore" highlights a burgeoning cybersecurity threat where thousands of fraudulent IT professionals, often linked to state-sponsored actors like North Korea, infiltrate organizations by exploiting remote hiring vulnerabilities. These sophisticated adversaries utilize advanced artificial intelligence to craft fabricated resumes, generate convincing deepfake identities, and master scripted interviews, successfully bypassing traditional background checks that typically verify provided information rather than detecting outright fraud. Once integrated as trusted insiders, these malicious actors can facilitate data exfiltration, industrial sabotage, or the funneling of corporate funds to foreign governments. The piece underscores that this is no longer just a recruitment issue but a critical insider risk management challenge. CISOs are urged to implement more rigorous vetting processes, such as multi-stage panel interviews and project-based technical evaluations, to identify inconsistencies that automated screenings miss. Furthermore, the article advises organizations to adopt a "least privilege" approach for new hires, restricting access to sensitive systems until identities are definitively verified. Beyond immediate security breaches, the presence of fake workers creates substantial business and compliance risks, potentially leading to regulatory penalties and the erosion of client trust, making it imperative for leadership to coordinate across HR and security departments to mitigate this evolving threat.

Three Pillars of Platform Engineering: A Virtuous Cycle

In the article "Three Pillars of Platform Engineering: A Virtuous Cycle," Pratik Agarwal challenges the notion that reliability and ergonomics are opposing trade-offs, arguing instead that they form a mutually reinforcing feedback loop. The framework is built upon three foundational pillars: automated reliability, developer ergonomics, and operator ergonomics. The first pillar treats reliability as a managed state where a centralized "control plane" or "brain" continuously reconciles the system’s actual state with its desired state, automating complex tasks like shard rebalancing and self-healing. The second pillar, developer ergonomics, focuses on providing opinionated SDKs that enforce safe defaults—such as environment-aware configurations and sophisticated retry strategies—to prevent cascading failures and reduce cognitive load. Finally, operator ergonomics emphasizes building internal tools that encode tribal knowledge into automated commands and layered observability, allowing even novice engineers to resolve incidents effectively. Together, these pillars create a virtuous cycle where ergonomic interfaces produce predictable traffic patterns, which in turn stabilize the infrastructure and reduce the operational burden. This stability grants platform teams the bandwidth to further refine their tools, building a foundation of trust that allows organizational scaling without the friction of "sharp" interfaces or manual interventions.

Why Humans Are Still More Cost-Effective Than AI Compute

The article explores a significant study by MIT’s Computer Science and Artificial Intelligence Laboratory regarding the economic viability of AI compared to human labor. Despite intense hype surrounding automation, researchers discovered that for many visual tasks, humans remain far more cost-effective than computer vision systems. Specifically, the research indicates that only about twenty-three percent of worker wages currently spent on tasks involving visual inspection are economically attractive for AI replacement today. This financial gap is primarily due to the massive upfront costs associated with implementing, training, and maintaining sophisticated AI infrastructure. While AI performance is technically impressive, the capital investment required often yields a poor return on investment compared to versatile human workers who are already integrated into existing workflows. Furthermore, high energy consumption and specialized hardware needs contribute to the financial burden of AI compute. The study suggests that while AI capabilities will inevitably improve and costs may eventually decrease, there is no immediate "job apocalypse" for roles requiring visual discernment. Instead, human intelligence provides a level of flexibility and affordability that current technology cannot yet match at scale. Ultimately, the transition to AI-driven labor will be gradual, dictated more by cold economic feasibility than by pure technical capability.

Leading Without Forecasts: How CEOs Navigate Unpredictable Markets

In his May 2026 article for the Forbes Business Council, CEO Yerik Aubakirov argues that traditional long-term forecasting is no longer viable in a global landscape defined by rapid geopolitical, regulatory, and technological shifts. Aubakirov advocates for a fundamental change in leadership, suggesting that CEOs must replace rigid five-year plans with agile, hypothesis-driven strategies. Drawing a parallel to modern meteorology, he recommends layering broad seasonal outlooks with rolling monthly and quarterly updates to maintain operational relevance. A critical component of this adaptive approach involves rethinking capital allocation; instead of committing massive upfront investments to unproven initiatives, successful organizations now deploy capital in gradual tranches, scaling only when early signals confirm market viability. This staged investment model minimizes the risk of catastrophic failure while allowing for greater flexibility. Furthermore, the author emphasizes the importance of shortening internal decision cycles and cultivating a leadership team capable of operating decisively even with partial information. Ultimately, Aubakirov asserts that uncertainty is the new baseline for the 2020s. By treating strategic plans as fluid experiments rather than fixed commitments and diversifying strategic bets, modern leaders can ensure their organizations remain resilient, allowing their portfolios to "breathe" and evolve through market volatility rather than breaking under pressure.

Agentic AI is rewiring the SDLC

In the article "Agentic AI is rewiring the SDLC," Vipin Jain explores how autonomous agents are transforming software development from a procedural lifecycle into an intelligence-led delivery model. This shift moves AI beyond simple code suggestion to active participation across all stages, including planning, architecture, testing, and operations. In the planning phase, agents analyze existing codebases and refine user stories, though Jain warns that "vague intent" remains a primary bottleneck. Architecture evolves from static documentation to the definition of executable guardrails, making the role more operational and consequential. During the build and test phases, agents decompose tasks and generate reviewable work, shifting key productivity metrics from mere code volume to safe, reliable throughput. The human element also undergoes a significant transition; developers and architects move "up the value chain," spending less time on manual execution and more on high-level judgment, verification, and exception management. Furthermore, the convergence of pro-code and low-code platforms requires CIOs to prioritize clear requirements, robust observability, and rigorous governance to avoid software sprawl. Ultimately, the goal is not just more generated code, but a redesigned delivery system where AI acts as a trusted coworker within a secure, governed framework, ensuring quality and resilience in increasingly complex software ecosystems.

Opinions on UK Online Safety Act emphasize importance of enforcement

The UK’s Online Safety Act (OSA) has sparked significant debate regarding its actual effectiveness in protecting children, as detailed in a recent report by Internet Matters. While the legislation has made safety tools and parental controls more visible, stakeholders argue that the lack of robust enforcement undermines its goals. Surveys indicate that children frequently encounter harmful content and find existing age verification methods easy to circumvent through tactics like using fake birthdays or VPNs. Despite these gaps, there is high public and youth support for safety features, such as improved reporting processes and restrictions on contacting strangers. However, the report highlights that the OSA fails to address primary parental concerns, specifically the excessive time children spend online and the emerging psychological risks posed by AI-generated content. Industry experts emphasize that while highly effective biometric technologies like facial age estimation and ID scanning exist, they must be consistently deployed to meet regulatory standards. Furthermore, critiques of the regulator Ofcom suggest its focus on corporate policies rather than specific content moderation may limit its impact. Ultimately, the consensus is that for the Online Safety Act to move beyond being a "leaky boat," the government must prioritize safety-by-design principles and hold both platforms and regulators accountable through rigorous leadership and enforcement.

They don’t hack, they borrow: How fraudsters target credit unions

The article "They don’t hack, they borrow" highlights a sophisticated shift in cybercrime where fraudsters exploit legitimate financial workflows rather than bypassing security systems. Instead of technical hacking, threat actors utilize highly structured methods to "borrow" funds through fraudulent loans, specifically targeting small to mid-sized credit unions. These institutions are preferred because they often rely on traditional verification methods and lack advanced behavioral fraud detection. The criminal process begins with acquiring stolen personal data and assessing a victim's credit profile to ensure high approval odds. Fraudsters then meticulously prepare for Knowledge-Based Authentication (KBA) by gathering details from leaked datasets and social media, effectively turning identity checks into predictable hurdles. Once an application is submitted under a stolen identity, the attacker navigates the lending process as a genuine customer. Upon approval, funds are rapidly moved through intermediary accounts to obscure their origin before being cashed out. By mirroring normal financial behavior, these organized schemes avoid triggering traditional security alarms. Researchers from Flare emphasize that this evolution from intrusion to process exploitation makes detection increasingly difficult, as the line between legitimate activity and fraud continues to blur, requiring institutions to adopt more adaptive, data-driven defense strategies to mitigate rising risks.

The Cloud Already Ate Your Hardware Lunch

The article "The Cloud Already Ate Your Hardware Lunch," published on BigDataWire on May 4, 2026, details a fundamental disruption in the enterprise technology market where cloud hyperscalers have effectively rendered traditional on-premises hardware procurement obsolete. Driven by a volatile combination of skyrocketing memory prices and severe supply chain shortages, modern organizations are finding it increasingly difficult to justify the costs of owning and maintaining independent data centers. The piece emphasizes that industry leaders like Microsoft, Google, and Amazon are allocating staggering capital—often exceeding $190 billion—to dominate the procurement of GPUs and high-bandwidth memory essential for generative AI. This aggressive consolidation has created a "hardware lunch" scenario, where cloud giants have successfully captured the market share once dominated by traditional server manufacturers. Enterprises are transitioning from viewing the cloud as an optional convenience to recognizing it as the only scalable platform for deploying AI agents and managing the massive datasets central to 2026 operations. Consequently, the legacy hardware model is being subsumed by advanced cloud ecosystems that offer superior integration, security, and raw power. This seismic shift marks the definitive conclusion of the on-premises era, as the sheer economic weight and technological advantages of the cloud become the only viable choice for remaining competitive in an AI-first economy.

One in four MCP servers opens AI agent security to code execution risk

The article examines the critical security risks inherent in enterprise AI agents, highlighting a significant "observability gap" between Model Context Protocol (MCP) servers and "Skills." While MCP servers offer structured, loggable functions, Skills load textual instructions directly into a model’s reasoning context, making their internal processes invisible to traditional monitoring tools. Research from Noma Security reveals that one in four MCP servers exposes agents to unauthorized code execution, while many Skills possess high-risk capabilities like data alteration. These vulnerabilities often manifest in "toxic combinations," where untrusted inputs and sensitive data access lead to sophisticated attacks such as ContextCrush or ForcedLeak. Even without malicious intent, autonomous agents have caused severe damage, exemplified by Replit's accidental database deletion. To address these blind spots, the "No Excessive CAP" framework is proposed, focusing on three defensive pillars: Capabilities, Autonomy, and Permissions. By strictly allowlisting tools, implementing human-in-the-loop approval gates for irreversible actions, and transitioning from broad service accounts to scoped, user-specific credentials, organizations can mitigate the risks of high-blast-radius incidents. Ultimately, because Skill-driven reasoning remains opaque, security teams must compensate by tightening control over the execution layer to prevent agents from operating with excessive, unsupervised authority.

The Shadow AI Governance Crisis: Why 80% of Fortune 500 Companies Have Already Lost Control of Their AI Infrastructure

The article "The Shadow AI Governance Crisis" by Deepak Gupta highlights a critical security gap where 80% of Fortune 500 companies have integrated autonomous AI agents into their infrastructure, yet only 10% possess a formal strategy to manage them. This "agentic shadow AI" differs from simple tool usage because these autonomous agents possess API access, chain actions across services, and operate at machine speed without human oversight. Traditional governance frameworks, designed for stable human identities, fail because AI agents are ephemeral and dynamic, leading to "identity without governance" and excessive permission sprawl. Statistics from Microsoft’s 2026 Cyber Pulse report underscore the urgency, noting that nearly 90% of organizations have already faced security incidents involving these agents. To combat this, the article introduces a five-capability framework centered on creating a centralized agent registry, implementing just-in-time access controls, and establishing real-time visualization of agent behaviors. High-profile breaches at McDonald’s and Replit serve as warnings of the catastrophic risks posed by unmonitored AI autonomy. Ultimately, Gupta argues that enterprises must shift from human-speed approval workflows to automated, runtime enforcement to maintain control. Building this foundational governance is presented as a necessary prerequisite for safe innovation and long-term competitive advantage in an increasingly AI-driven corporate landscape.

Daily Tech Digest - April 23, 2026

Quote for the day:

“Every time you have to speak, you are auditioning for leadership.” -- James Humes

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Duration: 19 mins • Perfect for listening on the go.

How To Navigate The New Economics Of Professionalized Cybercrime

The modern cybercrime landscape has evolved into a professionalized industry where attackers prioritize precision and severity over volume. According to recent data, while the frequency of material claims has decreased, the average cost per ransomware incident has surged, signaling a shift toward more efficient targeting. This new economic reality is defined by three primary trends: the rise of data-theft extortion, the prevalence of identity attacks, and the long-tail financial consequences that follow a breach. Because businesses have improved their backup and recovery systems, criminals have pivoted from simple encryption to threatening the exposure of sensitive data, often leveraging AI to analyze stolen information for maximum leverage. Furthermore, the professionalization of these threats extends to supply chain vulnerabilities, where a single vendor compromise can cause cascading losses across thousands of downstream clients. Consequently, cyber incidents are no longer isolated technical failures but material enterprise risks with financial repercussions lasting years. To navigate this environment, organizational leaders must shift their focus from mere operational recovery to robust data exfiltration prevention. must collaborate to integrate cyber risk into broader enterprise frameworks, ensuring that financial planning and security investments account for the multi-year legal, regulatory, and reputational exposures that now characterize the threat landscape.

How Agentic AI is transforming the future of Indian healthcare

Agentic AI represents a transformative shift in the Indian healthcare landscape, transitioning from passive data analysis to autonomous, goal-oriented systems that proactively manage patient care. Unlike traditional AI, which primarily focuses on reporting, agentic systems independently execute tasks such as triaging, scheduling, and continuous monitoring to address India’s strained doctor-to-patient ratio. By integrating these intelligent agents, medical facilities can streamline outpatient visits—from digital symptom recording to automated post-consultation follow-ups—significantly reducing the administrative burden on overworked clinicians. The technology is particularly vital for chronic disease management, where it provides timely nudges for medication adherence and identifies early warning signs before they escalate into emergencies. Furthermore, Agentic AI acts as a crucial support layer for frontline health workers in rural regions, bridging the clinical knowledge gap through real-time protocol guidance and decision support. While these advancements offer a scalable solution for public health, the article emphasizes that human empathy remains irreplaceable. Successful adoption requires robust frameworks for data privacy and ethical transparency, ensuring that physicians always retain final decision-making authority. Ultimately, by evolving from a mere tool into essential digital infrastructure, Agentic AI is poised to democratize access and foster a more responsive, patient-centric healthcare ecosystem across the diverse Indian population.

What a Post-Commercial Quantum World Could Look Like

The article "What a Post-Commercial Quantum World Could Look Like," published by The Quantum Insider, explores a future where has moved beyond its initial commercial hype into a phase of deep integration and stabilization. In this post-commercial era, the focus shifts from the race for "quantum supremacy" toward the practical, ubiquitous application of quantum technologies across global infrastructure. The piece suggests that once the technology matures, it will cease to be a standalone industry of speculative startups and instead become a foundational utility, much like the internet or electricity today. Key impacts include a complete transformation of cybersecurity through and the optimization of complex systems in logistics, materials science, and drug discovery that were previously unsolvable. This transition will likely lead to a "quantum divide," where geopolitical and economic power is concentrated among those who have successfully integrated these capabilities into their national security and industrial frameworks. Ultimately, the article paints a picture of a world where quantum mechanics no longer represents a frontier of experimental physics but serves as the silent, invisible engine driving high-performance global economies and ensuring long-term technological resilience.

Continuous AI biometric identification: Why manual patient verification is not enough!

The article explores the critical transition from manual patient verification to continuous in modern healthcare. Traditional methods, such as verbal confirmations and physical wristbands, are increasingly deemed insufficient due to their susceptibility to human error and data entry inconsistencies, which often lead to fragmented medical records and life-threatening mistakes. To address these vulnerabilities, the industry is shifting toward a model of constant identity assurance using advanced technologies like , , and passive authentication. This continuous approach ensures real-time validation across all clinical touchpoints, significantly reducing the risks associated with duplicate electronic health records — currently estimated at 8-12% of total files. Furthermore, the integration of agentic AI and multimodal systems — combining fingerprints, voice, and device data — creates a secure identity layer that streamlines clinical workflows and protects patients from misidentification. With the healthcare biometrics market projected to reach $42 billion by 2030, the article argues that automating identity verification is no longer optional. Ultimately, by replacing episodic manual checks with autonomous, intelligent monitoring, healthcare organizations can enhance data integrity, safeguard financial interests against identity fraud, and, most importantly, ensure the highest standards of safety for the individuals in their care.

The 4 disciplines of delivery — and why conflating them silently breaks your teams

In his article for CIO, Prasanna Kumar Ramachandran argues that enterprise success depends on maintaining four distinct delivery disciplines: product management, technical architecture, program management, and release management. Each domain addresses a fundamental question that the others are ill-equipped to answer. Product management defines the "what" and "why," establishing the strategic vision and priorities. Technical architecture translates this into the "how," determining structural feasibility and sequence. Program management orchestrates the delivery timeline by managing cross-team dependencies, while release management ensures safe, compliant deployment to production. Organizations frequently stumble by treating these roles as interchangeable or asking a single team to bridge all four. This conflation "silently breaks" teams because it forces experts into roles outside their core competencies. For instance, an architect focused on product decisions might prioritize technical elegance over market needs, while program managers might sequence work based on staff availability rather than strategic value. When these boundaries blur, the result is often wasted effort, missed dependencies, and a fundamental misalignment between technical output and business goals. By clearly delineating these responsibilities, leaders can prevent operational friction and ensure that every capability delivered actually reaches the customer safely and generates measurable impact.

Teaching AI models to say “I’m not sure”

Researchers at MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) have developed a novel training technique called Reinforcement Learning with Calibration Rewards (RLCR) to address the issue of AI overconfidence. Modern large language models often deliver every response with the same level of certainty, regardless of whether they are correct or merely guessing. This dangerous trait stems from standard reinforcement learning methods that reward accuracy but fail to penalize misplaced confidence. RLCR fixes this flaw by teaching models to generate calibrated confidence scores alongside their answers. During training, the system is penalized for being confidently wrong or unnecessarily hesitant when correct. Experimental results demonstrate that RLCR can reduce calibration errors by up to 90 percent without sacrificing accuracy, even on entirely new tasks the models have never encountered. This advancement is particularly significant for high-stakes applications in medicine, law, and finance, where human users must rely on the AI’s self-assessment to determine when to seek a second opinion. By providing a reliable signal of uncertainty, RLCR transforms AI from an unshakable but potentially deceptive voice into a more trustworthy tool that explicitly communicates its own limitations, ultimately enhancing safety and reliability in complex decision-making environments.

Are you paying an AI ‘swarm tax’? Why single agents often beat complex systems

The VentureBeat article discusses a "swarm tax" paid by enterprises that over-engineer AI systems with complex . Recent Stanford University research reveals that single-agent systems often match or even outperform multi-agent swarms when both are allocated an equivalent "thinking token budget." The perceived superiority of swarms frequently stems from higher total computation during testing rather than inherent structural advantages. This "tax" manifests as increased latency, higher costs, and greater technical complexity. A primary reason for this performance gap is the "Data Processing Inequality," where critical information is often lost or fragmented during the handoffs and summarizations required in multi-agent orchestration. In contrast, a single agent maintains a continuous context window, allowing for much more efficient information retention and reasoning. The study suggests that developers should prioritize optimizing single-agent models—using techniques like SAS-L to extend reasoning—before adopting multi-agent frameworks. Swarms remain useful only in specific scenarios, such as when a single agent’s context becomes corrupted by noisy data or when a task is naturally modular and requires parallel processing. Ultimately, the article advocates for a "single-agent first" approach, warning that unnecessary architectural bloat can lead to diminishing returns and inefficient resource utilization in enterprise AI deployments.

Cloud tech outages: how the EU plans to bolster its digital infrastructure

The recent global outages involving in late 2025 and in 2024 have underscored the extreme fragility of modern digital infrastructure, which remains heavily reliant on a small group of U.S.-based hyperscalers. These disruptions revealed that the perceived redundancy of cloud computing is often an illusion, as many organizations concentrate their primary and backup systems within the same provider's ecosystem. Consequently, the European Union is shifting its strategy from mere technical efficiency to a geopolitical pursuit of "." To mitigate the risks of "digital colonialism" and the reach of the , European leaders are championing the 2025 European Digital Sovereignty Declaration. This framework prioritizes the development of a federated cloud architecture, linking national nodes into a cohesive, secure network to reduce dependence on foreign monopolies. Furthermore, the EU is investing heavily in homegrown semiconductors, foundational AI models, and public digital infrastructure. By establishing a dedicated task force to monitor progress through 2026, the bloc aims to ensure that European data remains subject strictly to local jurisdiction. This comprehensive approach seeks to bolster resilience against future technical failures while securing the strategic autonomy necessary for Europe’s long-term digital and economic security.

When a Cloud Region Fails: Rethinking High Availability in a Geopolitically Unstable World

In the InfoQ article "When a Cloud Region Fails," Rohan Vardhan introduces the concept of sovereign fault domains (SFDs) to address cloud resilience within an increasingly unstable geopolitical landscape. While traditional high-availability strategies focus on technical abstractions like multi-availability zone (multi-AZ) deployments to mitigate hardware failures, Vardhan argues these are insufficient against sovereign-level disruptions. SFDs represent failure boundaries defined by legal, political, or physical jurisdictions. Recent events, such as sudden cloud provider withdrawals or infrastructure instability in conflict zones, demonstrate how geopolitical shifts can trigger correlated failures across entire regions, rendering standard multi-AZ setups ineffective. To combat these risks, architects must shift their baseline for high availability from multi-AZ to multi-region architectures. This transition requires a fundamental rethink of distributed systems, moving beyond technical redundancy to include legal and political considerations in data replication and traffic management. The article advocates for the adoption of explicit region evacuation playbooks, the definition of geopolitical recovery targets, and the expansion of chaos engineering to simulate sovereign-level losses. Ultimately, achieving true resilience in the modern world necessitates acknowledging that cloud regions are physical and political assets, not just virtualized resources, requiring intentional design to survive jurisdictional partitions.

Inside Caller-as-a-Service Fraud: The Scam Economy Has a Hiring Process

The BleepingComputer article explores the emergence of "Caller-as-a-Service," a professionalized vishing ecosystem where cybercrime syndicates mirror the organizational structure of legitimate businesses. These industrialized fraud operations utilize a clear division of labor, employing specialized roles such as infrastructure operators, data analysts, and professional callers. Recruitment for these positions is surprisingly formal; underground job postings resemble professional LinkedIn ads, specifically seeking native English speakers with high emotional intelligence and persuasive social engineering skills. To establish credibility, recruiters often display verifiable "proof-of-profit" via large cryptocurrency balances to entice new talent. Once hired, callers are frequently subjected to real-time supervision through screen sharing to ensure strict adherence to malicious scripts and maximize victim conversion rates. Compensation models are equally sophisticated, ranging from fixed weekly salaries of $1,500 to success-based commissions of $1,000 per successful vishing hit. This service-driven model significantly lowers the barrier to entry for criminals, as it allows them to outsource the technical and interpersonal complexities of a cyberattack. Ultimately, the article emphasizes that the professionalization of the scam economy makes these threats more resilient and efficient, necessitating that defenders implement more robust identity verification and multi-factor authentication to protect individuals from these increasingly coordinated, data-driven vishing campaigns.

Daily Tech Digest - March 29, 2026

Quote for the day:

"The organizations that succeed this year will be the ones that build confidence faster than AI can erode it." -- 2026 Data Governance Outlook

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Duration: 17 mins • Perfect for listening on the go.

Google's 2029 Quantum Deadline Is a Wake-Up Call

Google has issued a significant "wake-up call" to the technology industry by accelerating its deadline for transitioning to (PQC) to 2029. This aggressive timeline positions the company well ahead of the 2035 target set by the National Institute for Standards and Technology (NIST) and the 2031 requirement for national security systems. By moving faster, Google aims to provide the necessary urgency for global digital transitions, addressing critical vulnerabilities such as "harvest now, decrypt later" attacks and the inherent fragility of current digital signatures. These threats involve adversaries collecting encrypted sensitive data today with the intention of unlocking it once cryptographically relevant quantum computers become available. Furthermore, the 2029 deadline aligns with industry shifts to reduce public TLS certificate validity to 47 days, emphasizing a broader move toward cryptographic agility. Experts suggest that because Google is a foundational component of many corporate technology stacks, its early migration forces dependent organizations to upgrade and test their systems sooner. Enterprise leaders are advised to immediately inventory their cryptographic assets, prioritize high-risk data, and collaborate with vendors to ensure their infrastructure can support rapid, automated algorithm rotations. The message is clear: the journey to quantum readiness is lengthy, and waiting until the next decade to act may be too late.

The one-model trap: Why agentic AI won’t scale in production

In "," Jofia Jose Prakash explains that relying on a single monolithic AI model is a strategic error that prevents agentic AI from scaling in production. While the "one-model" approach seems simpler to manage, it fails to account for the high variance in real-world workloads. Using high-capability models for routine tasks leads to excessive costs and latency, while the lack of isolation boundaries makes the entire system vulnerable to model outages and policy shifts. To build resilient agents, organizations must transition from a prompt-centric view to a system-centric architectural approach. This involves a multi-model strategy featuring "capability tiering," where tasks are routed based on complexity to fast-cheap, balanced, or premium reasoning tiers. Such an architecture allows for graceful degradation and easier governance, as policy updates become control-plane adjustments rather than complete system overhauls. Prakash outlines five critical stages for scalability: separating control from generation, implementing failure-aware execution with circuit breakers, and enforcing strict economic controls like token budgets. Ultimately, the author concludes that successful agentic AI is a control-plane challenge rather than a model-choice problem. By prioritizing orchestration and robust monitoring over model standardization, enterprises can achieve the reliability and cost-efficiency necessary for production-grade AI.

Are You Overburdening Your Most Engaged Employees?

The Harvard Business Review article, "Are You Overburdening Your Most Engaged Employees?" by Sangah Bae and Kaitlin Woolley, explores a critical paradox in workforce management. While senior leaders invest heavily in fostering employee engagement, new research involving over 4,300 participants reveals that managers often inadvertently undermine these efforts. When unexpected tasks arise, managers tend to assign approximately 70% of this additional workload to their most intrinsically motivated staff. This systematic bias stems from two flawed assumptions: that highly engaged employees find extra work inherently rewarding and that they possess a unique resilience against burnout. In reality, both beliefs are incorrect. This disproportionate burden significantly reduces job satisfaction and heightens turnover intentions among the very individuals organizations are most desperate to retain. By over-relying on "star" performers to handle unforeseen demands, companies risk depleting their most valuable human capital through an unintended "engagement tax." To combat this, the authors propose three low-cost interventions aimed at promoting more equitable work distribution. Ultimately, the research highlights the necessity for leaders to move beyond convenience-based task allocation and adopt strategic practices that protect their most dedicated employees from exhaustion, ensuring that high engagement remains a sustainable asset rather than a precursor to professional burnout.

When AI turns software development inside-out: 170% throughput at 80% headcount

The article "When AI turns software development inside-out" explores a transformative shift in engineering productivity where a team achieved 170% throughput while operating at 80% of its previous headcount. This transition marks a fundamental departure from traditional "diamond-shaped" development—where large teams execute designs—to a "double funnel" model. In this new paradigm, humans focus intensely on the beginning stages of defining intent and the final stages of validating outcomes, while AI handles the rapid execution in between. The shift has collapsed the cost of experimentation, enabling ideas to move from whiteboards to working prototypes in a single day. Consequently, roles are being redefined: creative directors maintain production code, and QA engineers have evolved into system architects who build AI agents to ensure correctness. This "inside-out" approach prioritizes validation over manual coding, treating software development as a control tower operation rather than an assembly line. By automating the middle layer of implementation, the organization has not only increased its velocity but also improved product quality and reduced bugs. Ultimately, AI-first workflows allow teams to focus on defining "good" while leveraging technology to handle the heavy lifting of execution and technical translation across dozens of programming languages.

4 Out of 5 Organizations Are Drowning in Security Debt

The reveals that approximately 82% of organizations are currently overwhelmed by significant , representing a concerning 11% increase from the previous year. Alarmingly, 60% of these entities face "critical" debt levels characterized by severe, long-unresolved vulnerabilities that could cause catastrophic damage if exploited by malicious actors. The study identifies a widening gap between the rapid, modern pace of software development and the capacity of security teams to manage remediation, noting a 36% spike in high-risk flaws. Several factors exacerbate this trend, including the unprecedented velocity of AI-generated code and a heavy reliance on complex third-party libraries, which account for 66% of the most dangerous long-lived vulnerabilities. To combat this escalating crisis, the report suggests moving beyond simple detection toward a comprehensive and strategic "Prioritize, Protect, and Prove" (P3) framework. By focusing resources specifically on the 11.3% of flaws that present genuine real-world danger and utilizing automated remediation for critical digital assets, enterprises can manage their debt more effectively. Ultimately, the report emphasizes that success in today's digital landscape requires a deliberate shift toward risk-based prioritization and rigorous compliance to stem the tide of vulnerabilities and safeguard essential infrastructure.

The agentic AI gap: Vendors sprint, enterprises crawl

The "agentic AI gap" highlights a stark disconnect between the rapid innovation of tech vendors and the cautious, often sluggish adoption of artificial intelligence within mainstream enterprises. While vendors are "sprinting" toward sophisticated agentic workflows and reasoning capabilities, most organizations are still "crawling," primarily focused on basic productivity gains and early-stage pilots. This hesitation is fueled by a combination of macroeconomic uncertainty—such as geopolitical tensions and fluctuating interest rates—and a lack of operational readiness. Currently, only about 13% of enterprises report achieving sustained ROI at scale, as hurdles like data governance, security, and integration remain significant barriers. The article suggests that a new four-layer software architecture is emerging, shifting the focus from application-centric models to intelligence-centric systems. Central to this transition is the "Cognitive Surface," a middle layer where intent is shaped and enterprise policies are enforced. As the industry moves toward an economic model based on tokenized intelligence, business leaders must evolve their operational strategies to manage digital agents effectively. Ultimately, bridging this gap requires more than just better technology; it demands a fundamental transformation in how enterprises secure, govern, and value AI to turn experimental pilots into scalable, revenue-generating business assets.

India’s Proposal for Age-verification Is a Blunt Response to a Complex Problem

and subsequent regulatory proposals introduce a stringent age-verification framework, mandating "" for users under eighteen. This article by Amber Sinha argues that such measures constitute a "blunt response" to the multifaceted challenges of online child safety, potentially compromising privacy and fundamental digital rights. By shifting toward a graded approach that includes screen-time caps and "curfews," the government risks creating massive "honeypots" of sensitive identification data—often tied to the Aadhaar biometric system—thereby enabling state surveillance and increasing vulnerability to data breaches. Furthermore, the reliance on official documentation and repeated parental consent threatens to deepen the gender digital divide; in many South Asian households, these barriers may lead families to restrict girls' access to shared devices entirely. Critics emphasize that these rigid mandates often drive minors toward riskier, unregulated corners of the internet while stifling their constitutional right to information. Rather than imposing a universal, one-size-fits-all age-gating mechanism, the author advocates for a more nuanced strategy. This alternative would prioritize "privacy by design" and leverage advanced cryptographic techniques like to verify age without compromising user anonymity, ultimately focusing on safety through empowerment rather than through restrictive control and pervasive data collection.

The Danger of Treating CyberCrime as War – The New National Cybersecurity Strategy

The article "The Danger of Treating CyberCrime as War – The New National Cybersecurity Strategy," published in March 2026, analyzes the fundamental shift in U.S. cybersecurity policy following the release of the "Cyber Strategy for America." This new approach moves away from traditional regulatory compliance and defensive engineering, instead prioritizing a posture of active disruption and the projection of national power. By treating cybersecurity as a contest against adversaries, the strategy leverages law enforcement, intelligence, and sanctions to impose significant costs on bad actors. However, the author warns that this "war-like" framing may be misaligned with the reality of most digital threats. While nation-states might respond to traditional deterrence, the vast majority of cyber harm is caused by economically motivated criminals—such as and fraudsters—who are highly elastic and adaptive. These actors often respond to increased pressure by evolving their tactics or shifting jurisdictions rather than ceasing operations. Consequently, the article suggests that over-emphasizing state-level power risks neglecting the underlying economic drivers of cybercrime. Ultimately, a successful strategy must balance the pursuit of geopolitical adversaries with the practical need to secure the private sector’s daily operations against profit-driven threats.

The AI Leader

In "The AI Leader," Tomas Chamorro-Premuzic explores the profound transformation of the professional landscape as artificial intelligence reaches parity with human cognitive capabilities. He argues that while AI has commoditized technical expertise and routine management—such as data processing and tactical execution—it has simultaneously increased the "leadership premium" on uniquely human qualities. As the distinction between human and machine intelligence blurs, the author posits that the essence of leadership must shift from traditional authority and information control to the cultivation of empathy, moral judgment, and a sense of purpose. Chamorro-Premuzic warns against the temptation for executives to abdicate their decision-making responsibility to algorithms, emphasizing that leadership is fundamentally a human-centric endeavor centered on motivation and cultural alignment. He suggests that the modern leader’s primary role is to serve as a filter for AI-generated noise, using intuition to navigate ambiguity where data falls short. Ultimately, the article concludes that the most successful organizations in the AI era will be those led by individuals who leverage technology to enhance efficiency while doubling down on the "soft" skills that foster trust and inspiration. In this new paradigm, leadership is not about competing with AI but about mastering the human elements that technology cannot replicate.

Data governance vs. data quality: Which comes first in 2026?

In 2026, the debate between data governance and data quality has shifted toward a unified framework, as the article "Data governance vs. data quality: Which comes first in 2026" argues that governance without quality is merely "bureaucracy dressed in corporate branding." While governance provides the essential structure—defining roles, policies, and accountability—it remains an act of faith unless validated by measurable quality metrics. The rise of AI has intensified this need, as models amplify underlying data inconsistencies, requiring governance to prioritize continuous quality rather than periodic "cleanup" projects. Leading organizations are moving away from treating these as separate silos; instead, they integrate governance as an enabler of quality at scale and quality as the evidence of governance effectiveness. This shift ensures that data owners have visibility into metrics, creating meaningful accountability. Ultimately, the article concludes that quality is the primary metric by which any governance program should be judged. Organizations that fail to unify these initiatives will likely face the overhead of complex frameworks without the benefit of trustworthy data, losing their competitive advantage in an increasingly AI-driven and regulated landscape. Successful firms will instead achieve a sustained state of trust, where governance and quality work in tandem to support innovation.

Daily Tech Digest - February 13, 2026

Quote for the day:

"If you want teams to succeed, set them up for success—don’t just demand it." -- Gordon Tredgold

Hackers turn bossware against the bosses

Huntress discovered two incidents using this tactic, one late in January and one early this month. Shared infrastructure, overlapping indicators of compromise, and consistent tradecraft across both cases make Huntress strongly believe a single threat actor or group was behind this activity. ... CSOs must ensure that these risks are properly catalogued and mitigated,” he said. “Any actions performed by these agents must be monitored and, if possible, restricted. The abuse of these systems is a special case of ‘living off the land’ attacks. The attacker attempts to abuse valid existing software to perform malicious actions. This abuse is often difficult to detect.” ... Huntress analyst Pham said to defend against attacks combining Net Monitor for Employees Professional and SimpleHelp, infosec pros should inventory all applications so unapproved installations can be detected. Legitimate apps should be protected with robust identity and access management solutions, including multi-factor authentication. Net Monitor for Employees should only be installed on endpoints that don’t have full access privileges to sensitive data or critical servers, she added, because it has the ability to run commands and control systems. She also noted that Huntress sees a lot of rogue remote management tools on its customers’ IT networks, many of which have been installed by unwitting employees clicking on phishing emails. This points to the importance of security awareness training, she said.

Why secure OT protocols still struggle to catch on

“Simply having ‘secure’ protocol options is not enough if those options remain too costly, complex, or fragile for operators to adopt at scale,” Saunders said. “We need protections that work within real-world constraints, because if security is too complex or disruptive, it simply won’t be implemented.” ... Security features that require complex workflows, extra licensing, or new infrastructure often lose out to simpler compensating controls. Operators interviewed said they want the benefits of authentication and integrity checks, particularly message signing, since it prevents spoofing and unauthorized command execution. ... Researchers identified cost as a primary barrier to adoption. Operators reported that upgrading a component to support secure communications can cost as much as the original component, with additional licensing fees in some cases. Costs also include hardware upgrades for cryptographic workloads, training staff, integrating certificate management, and supporting compliance requirements. Operators frequently compared secure protocol deployment costs with segmentation and continuous monitoring tools, which they viewed as more predictable and easier to justify. ... CISA’s recommendations emphasize phased approaches and operational realism. Owners and operators are advised to sign OT communications broadly, apply encryption where needed for sensitive data such as passwords and key exchanges, and prioritize secure communication on remote access paths and firmware uploads.

SaaS isn’t dead, the market is just becoming more hybrid

“It’s important to avoid overgeneralizing ‘SaaS,’” Odusote emphasized . “Dev tools, cybersecurity, productivity platforms, and industry-specific systems will not all move at the same pace. Buyers should avoid one-size-fits-all assumptions about disruption.” For buyers, this shift signals a more capability-driven, outcomes-focused procurement era. Instead of buying discrete tools with fixed feature sets, they’ll increasingly be able to evaluate and compare platforms that are able to orchestrate agents, adapt workflows, and deliver business outcomes with minimal human intervention. ... Buyers will likely have increased leverage in certain segments due to competitive pressure among new and established providers, Odusote said. New entrants often come with more flexible pricing, which obviously is an attraction for those looking to control costs or prove ROI. At the same time, traditional SaaS leaders are likely to retain strong positions in mission-critical systems; they will defend pricing through bundled AI enhancements, he said. So, in the short term, buyers can expect broader choice and negotiation leverage. “Vendors can no longer show up with automatic annual price increases without delivering clear incremental value,” Odusote pointed out. “Buyers are scrutinizing AI add-ons and agent pricing far more closely.”

When algorithms turn against us: AI in the hands of cybercriminals

Cybercriminals are using AI to create sophisticated phishing emails. These emails are able to adapt the tone, language, and reference to the person receiving it based on the information that is publicly available about them. By using AI to remove the red flag of poor grammar from phishing emails, cybercriminals will be able to increase the success rate and speed with which the stolen data is exploited. ... An important consideration in the arena of cyber security (besides technical security) is the psychological manipulation of users. Once visual and audio “cues” can no longer be trusted, there will be an erosion of the digital trust pillar. The once-recognizable verification process is now transforming into multi-layered authentication which expands the amount of time it takes to verify a decision in a high-pressure environment. ... AI’s misuse is a growing problem that has created a paradox. Innovation cannot stop (nor should it), and AI is helping move healthcare, finance, government and education forward. However, the rate at which AI has been adopted has surpassed the creation of frameworks and/or regulations related to ethics or security. As a result, cyber security needs to transition from a reactive to a predictive stance. AI must be used to not only react to attacks, but also anticipate future attacks.

Those 'Summarize With AI' Buttons May Be Lying to You

Put simply, when a user visits a rigged website and clicks a "Summarize With AI" button on a blog post, they may unknowingly trigger a hidden instruction embedded in the link. That instruction automatically inserts a specially crafted request into the AI tool before the user even types anything. ... The threat is not merely theoretical. According to Microsoft, over a 60-day period, it observed 50 unique instances of prompt-based AI memory poisoning attempts for promotional purposes. ... AI recommendation poisoning is a sort of drive-by technique with one-click interaction, he notes. "The button will take the user — after the click — to the AI domain relevant and specific for one of the AI assistants targeted," Ganacharya says. To broaden the scope, an attacker could simply generate multiple buttons that prompt users to "summarize" something using the AI agent of their choice, he adds. ... Microsoft had some advice for threat hunting teams. Organizations can detect if they have been affected by hunting for links pointing to AI assistant domains and containing prompts with certain keywords like "remember," "trusted source," "in future conversations," and "authoritative source." The company's advisory also listed several threat hunting queries that enterprise security teams can use to detect AI recommendation poisoning URLs in emails and Microsoft Teams Messages, and to identify users who might have clicked on AI recommendation poisoning URLs.

EU Privacy Watchdogs Pan Digital Omnibus

The commission presented its so-called "Digital Omnibus" package of legal changes in November, arguing that the bloc's tech rules needed streamlining. ... Some of the tweaks were expected and have been broadly welcomed, such as doing away with obtrusive cookie consent banners in many cases, and making it simpler for companies to notify of data breaches in a way that satisfies the requirements of multiple laws in one go. But digital rights and consumer advocates are reacting furiously to an unexpected proposal for modifying the General Data Protection Regulation. ... "Simplification is essential to cut red tape and strengthen EU competitiveness - but not at the expense of fundamental rights," said EDPB chair Anu Talus in the statement. "We strongly urge the co-legislators not to adopt the proposed changes in the definition of personal data, as they risk significantly weakening individual data protection." ... Another notable element of the Digital Omnibus is the proposal to raise the threshold for notifying all personal data breaches to supervisory authorities. As the GDPR currently stands, organizations must notify a data protection authority within 72 hours of becoming aware of the breach. If amended as the commission proposes, the obligation would only apply to breaches that are "likely to result in a high risk" to the affected people's rights - the same threshold that applies to the duty to notify breaches to the affected data subjects themselves - and the notification deadline would be extended to 96 hours.

The Art of the Comeback: Why Post-Incident Communication is a Secret Weapon

Although technical resolutions may address the immediate cause of an outage, effective communication is essential in managing customer impact and shaping public perception—often influencing stakeholders’ views more strongly than the issue itself. Within fintech, a company's reputation is not built solely on product features or interface design, but rather on the perceived security of critical assets such as life savings, retirement funds, or business payrolls. In this high-stakes environment, even brief outages or minor data breaches are perceived by clients as threats to their financial security. ... While the natural instinct during a crisis (like a cyber breach or operational failure) is to remain silent to avoid liability, silence actually amplifies damage. In the first 48 hours, what is said—or not said—often determines how a business is remembered. Post-incident communication (PIC) is the bridge between panic and peace of mind. Done poorly, it looks like corporate double-speak. Done well, it demonstrates a level of maturity and transparency that your competitors might lack. ... H2H communication acknowledges the user’s frustration rather than just providing a technical error code. It recognizes the real-world impact on people, not just systems. Admitting mistakes and showing sincere remorse, rather than using defensive, legalistic language, makes a company more relatable and trustworthy. Using natural, conversational language makes the communication feel sincere rather than like an automated, cold response.

Why AI success hinges on knowledge infrastructure and operational discipline

Many organisations assume that if information exists, it is usable for GenAI, but enterprise content is often fragmented, inconsistently structured, poorly contextualised, and not governed for machine consumption. During pilots, this gap is less visible because datasets are curated, but scaling exposes the full complexity of enterprise knowledge. Conflicting versions, missing context, outdated material, and unclear ownership reduce performance and erode confidence, not because models are incapable, but because the knowledge they depend on is unreliable at scale. ... Human-in-the-loop processes struggle to keep pace with scale. Successful deployments treat HITL as a tiered operating structure with explicit thresholds, roles, and escalation paths. Pilot-style broad review collapses under volume; effective systems route only low-confidence or high-risk outputs for human intervention. ... Learning compounds over time as every intervention is captured and fed back into the system, reducing repeated manual review. Operationally, human-in-the-loop teams function within defined governance frameworks, with explicit thresholds, escalation paths, and direct integration into production workflows to ensure consistency at scale. In short, a production-grade human-in-the-loop model is not an extension of BPO but an operating capability combining domain expertise, governance, and system learning to support intelligent systems reliably.

Why short-lived systems need stronger identity governance

Consider the lifecycle of a typical microservice. In its journey from a developer’s laptop to production, it might generate a dozen distinct identities: a GitHub token for the repository, a CI/CD service account for the build, a registry credential to push the container, and multiple runtime roles to access databases, queues and logging services. The problem is not just volume; it is invisibility. When a developer leaves, HR triggers an offboarding process. Their email is cut, their badge stops working. But what about the five service accounts they hardcoded into a deployment script three years ago? ... In reality, test environments are often where attackers go first. It is the path of least resistance. We saw this play out in the Microsoft Midnight Blizzard attack. The attackers did not burn a zero-day exploit to break down the front door; they found a legacy test tenant that nobody was watching closely. ... Our software supply chain is held together by thousands of API keys and secrets. If we continue to rely on long-lived static credentials to glue our pipelines together, we are building on sand. Every static key sitting in a repo—no matter how private you think it is—is a ticking time bomb. It only takes one developer to accidentally commit a .env file or one compromised S3 bucket to expose the keys to the kingdom. ... Paradoxically, by trying to control everything with heavy-handed gates, we end up with less visibility and less control. The goal of modern identity governance shouldn’t be to say “no” more often; it should be to make the secure path the fastest path.

India's E-Rupee Leads the Secure Adoption of CBDCs

India has the e-rupee, which will eventually be used as a legal tender for domestic payments as well as for international transactions and cross-border payments. Ever since RBI launched the e-rupee, or digital rupee, in December 2022, there has been between INR 400 to 500 crore - or $44 to $55 million - in circulation. Many Indian banks are participating in this pilot project. ... Building broad awareness of CBDCs as a secure method for financial transactions is essential. Government and RBI-led awareness campaigns highlighting their security capability can strengthen user confidence and drive higher adoption and transaction volumes. People who have lost money due to QR code scams, fake calls, malicious links and other forms of payment fraud need to feel confident about using CBDCs. IT security companies are also cooperating with RBI to provide data confidentiality, transaction confidentiality and transaction integrity. E-transactions will be secured by hashing, digital signing and [advanced] encryption standards such as AES-192. This can ensure that the transaction data is not tampered with or altered. ... HSMs use advanced encryption techniques to secure transactions and keys. The HSM hardware [boxes] act as cryptographic co-processors and accelerate the encryption and decryption processes to minimize latency in financial transactions.

Daily Tech Digest - January 14, 2026

Quote for the day:

"To accomplish great things, we must not only act, but also dream, not only plan, but also believe." -- Anatole France

Outsmarting Data Center Outage Risks in 2026

Even the most advanced and well-managed facilities are not immune to disruptions. Recent incidents, such as outages at AWS, Cloudflare, and Microsoft Azure, serve as reminders that no data center can guarantee 100% uptime. This highlights the critical importance of taking proactive steps to mitigate data center outage risks, regardless of how reliable your facility appears to be. ... Overheating events can cause servers to shut down, leading to outages. To prevent an outage, you must detect and address excess heat issues proactively, before they become severe enough to trigger failures. A key consideration in this regard is to monitor data center temperatures granularly – meaning that instead of just deploying sensors that track the overall temperature of the server room, you monitor the temperatures of individual racks and servers. This is important because heat can accumulate in small areas, even if it remains normal across the data center. ... But from the perspective of data center uptime, physical security, which protects against physical attacks, is arguably a more important consideration. Whereas cybersecurity attacks typically target only a handful of servers or workloads, physical attacks can easily disable an entire data center. To this end, it’s critical to invest in multi-layered physical security controls – from the data center perimeter through to locks on individual server cabinets – to protect against intrusion. ... To mitigate outage risks, data center operators must take proactive steps to prevent fires from starting in the first place.

Deploying AI agents is not your typical software launch - 7 lessons from the trenches

Across the industry, there is agreement that agents require new considerations beyond what we've become accustomed to in traditional software development. In the process, new lessons are being learned. Industry leaders shared some of their own lessons with ZDNET as they moved forward into an agentic AI future. ... Kale urges AI agent proponents to "grant autonomy in proportion to reversibility, not model confidence. Irreversible actions across multiple domains should always have human oversight, regardless of how confident the system appears." Observability is also key, said Kale. "Being able to see how a decision was reached matters as much as the decision itself." ... "AI works well when it has quality data underneath," said Oleg Danyliuk, CEO at Duanex, a marketing agency that built an agent to automate the validation of leads of visitors to its site. "In our example, in order to understand if the lead is interesting for us, we need to get as much data as we can, and the most complex is to get the social network's data, as it is mostly not accessible to scrape. That's why we had to implement several workarounds and get only the public part of the data." ... "AI agents do not succeed on model capability alone," said Martin Bufi, a principal research director at Info-Tech Research Group. His team designed and developed AI agent systems for enterprise-level functions, including financial analysis, compliance validation, and document processing. What helped these projects succeed was the employment of "AgentOps" (agent operations), which focuses on managing the entire agent lifecycle.

What enterprises think about quantum computing

Quantum computers’ qubits are incredibly fragile, so even setting or reading qubits has to be incredibly precise or it messes everything up. Environmental conditions can also mess things up, because qubits can get entangled with the things around them. Qubits can even leak away in the middle of something. So, here we have a technology that most people don’t understand and that is incredibly finicky, and we’re supposed to bet the business on it? How many enterprises would? None, according to the 352 who commented on the topic. How many think their companies will use it eventually? All of them—but they don’t know where or when, as an old song goes. And by the way, quantum theory is older than that song, and we still don’t have a handle on it. ... First and foremost, this isn’t the technology for general business applications. The quantum geeks emphasize that good quantum applications are where you have some incredibly complex algorithm, some math problem, that is simply not solvable using digital computers. Some suggest that it’s best to think of a quantum computer as a kind of analog computer. ... Even where quantum computing can augment digital, you’ll have to watch ROI according to the second point. The cost of quantum computing is currently prohibitive for most applications, even the stuff it’s good for, so you need find applications that have massive benefits, or think of some “quantum as a service” for solving an occasional complex problem.

Beyond the hype: 4 critical misconceptions derailing enterprise AI adoption

Leaders frequently assume AI adoption is purely technological when it represents a fundamental transformation that requires comprehensive change management, governance redesign and cultural evolution. The readiness illusion obscures human and organizational barriers that determine success. ... Leaders frequently assume AI can address every business challenge and guarantee immediate ROI, when empirical evidence demonstrates that AI delivers measurable value only in targeted, well-defined and precise use cases. This expectation reality gap contributes to pilot paralysis, in which companies undertake numerous AI experiments but struggle to scale any to production. ... Executives frequently claim their enterprise data is already clean or assume that collecting more data will ensure AI success — fundamentally misunderstanding that quality, stewardship and relevance matter exponentially more than raw quantity — and misunderstanding that the definition of clean data changes when AI is introduced. ... AI systems are probabilistic and require continuous lifecycle management. MIT research demonstrates manufacturing firms adopting AI frequently experience J-curve trajectories, where initial productivity declines but is then followed by longer-term gains. This is because AI deployment triggers organizational disruption requiring adjustment periods. Companies failing to anticipate this pattern abandon initiatives prematurely. The fallacy manifests in inadequate deployment management, including planning for model monitoring, retraining, governance and adaptation.

Inside the Growing Problem of Identity Sprawl

For years, identity governance relied on a set of assumptions tied closely to human behavior. Employees joined organizations, moved roles and eventually left. Even when access reviews lagged or controls were imperfect, identities persisted long enough to be corrected. That model no longer reflects reality. The difference between human and machine identities isn't just scale. "With human identities, if people are coming into your organizations as employees, you onboard them. They work, and by the time they leave, you can deprovision them," said Haider Iqbal ... "Organizations are using AI today, whether they know it or not, and most organizations don't even know that it's deployed in their environment," said Morey Haber, chief security advisor at BeyondTrust. That lack of awareness is not limited to AI. Many security teams struggle to maintain a reliable inventory of non-human identities, especially when those identities are created dynamically by automation or cloud services. Visibility gaps don't stop access from being granted, but they do prevent teams from confidently enforcing policy. "Without integration … I don't know what it's doing, and then I got to go figure it out. When you unify together, then you have all the AI visibility," Haber said, describing the operational impact of fragmented tooling. ... Modern enterprise environments rely on elevated access for cloud orchestration, application integration and automated workflows. Service accounts and application programming interfaces often require broad permissions to function reliably.

The Timeless Architecture: Enterprise Integration Patterns That Exceed Technology Trends

A strange reality is often encountered by enterprise technology leaders: everything seems to change, yet many things remain the same. New technologies emerge — from COBOL to Java to Python, from mainframes to the cloud — but the fundamental problems persist. Organizations still need to connect incompatible systems, convert data between different formats, maintain reliability when components fail, and scale to meet increasing demand. ... Synchronous request-response communication creates tight coupling and can lead to cascading failures. Asynchronous messaging has appeared across all eras — on mainframes via MQ, in SOA through ESB platforms, in cloud environments via managed messaging services such as SQS and Service Bus, and in modern event-streaming platforms like Kafka. ... A key architectural question is how to coordinate complex processes that span multiple systems. Two primary approaches exist. Orchestration relies on a centralized coordinator to control the workflow, while choreography allows systems to react to events in a decentralized manner. Both approaches existed during the mainframe era and remain relevant in microservices architectures today. Each has advantages: orchestration provides control and visibility, while choreography offers resilience and loose coupling. ... Organizations that treat security as a mere technical afterthought often accumulate significant technical debt. In contrast, enterprises that embed security patterns as foundational architectural elements are better equipped to adapt as technologies evolve.

From distributed monolith to composable architecture on AWS: A modern approach to scalable software

A distributed monolith is a system composed of multiple services or components, deployed independently but tightly coupled through synchronous dependencies such as direct API calls or shared databases. Unlike a true microservices architecture, where services are autonomous and loosely coupled, distributed monoliths share many pitfalls of monoliths ... Composable architecture embraces modularity and loose coupling by treating every component as an independent building block. The focus lies in business alignment and agility rather than just code decomposition. ... Start by analyzing the existing application to find natural business or functional boundaries. Use Domain-Driven Design to define bounded contexts that encapsulate specific business capabilities. ... Refactor the code into separate repositories or modules, each representing a bounded context or microservice. This clear separation supports independent deployment pipelines and ownership. ... Replace direct code or database calls with API calls or events. For example: Use REST or GraphQL APIs via API Gateway. Emit business events via EventBridge or SNS for asynchronous processing. Use SQS for message queuing to handle transient workloads. ... Assign each microservice its own DynamoDB table or data store. Avoid cross-service database joins or queries. Adopt a single-table design in DynamoDB to optimize data retrieval patterns within each service boundary. This approach improves scalability and performance at the data layer.

Firmware scanning time, cost, and where teams run EMBA

Security teams that deal with connected devices often end up running long firmware scans overnight, checking progress in the morning, and trying to explain to colleagues why a single image consumed a workday of compute time. That routine sets the context for a new research paper that examines how the EMBA firmware analysis tool behaves when it runs in different environments. ... Firmware scans often stretch into many hours, especially for medium and large images. The researchers tracked scan durations down to the second and repeated runs to measure consistency. Repeated executions on the same platform produced nearly identical run times and findings. That behavior matters for teams that depend on repeatable results during testing, validation, or research work. It also supports the use of EMBA in environments where scans need to be rerun with the same settings over time. The data also shows that firmware size alone does not explain scan duration. Internal structure, compression, and embedded components influenced how long individual modules ran. Some smaller images triggered lengthy analysis steps, especially during deep inspection stages. ... Nuray said cloud based EMBA deployments fit well into large scale scanning activity. He described cloud execution as a practical option for parallel analysis across many firmware images. Local systems, he added, support detailed investigation where teams need tight control over execution conditions and repeatability.

'Most Severe AI Vulnerability to Date' Hits ServiceNow

Authentication issues in ServiceNow potentially opened the door for arbitrary attackers to gain full control over the entire platform and access to the various systems connected to it. ... Costello's first major discovery was that ServiceNow shipped the same credential to every third-party service that authenticated to the Virtual Agent application programming interface (API). It was a simple, obvious string — "servicenowexternalagent" — and it allowed him to connect to ServiceNow as legitimate third-party chat apps do. To do anything of significance with the Virtual Agent, though, he had to impersonate a specific user. Costello's second discovery, then, was quite convenient. He found that as far as ServiceNow was concerned, all a user needed to prove their identity was their email address — no password, let alone multifactor authentication (MFA), was required. ... An attacker could use this information to create tickets and manage workflows, but the stakes are now higher, because ServiceNow decided to upgrade its virtual agent: it can now also engage the platform's shiny new "Now Assist" agentic AI technology. ... "It's not just a compromise of the platform and what's in the platform — there may be data from other systems being put onto that platform," he notes, adding, "If you're any reasonably-sized organization, you are absolutely going to have ServiceNow hooked up to all kinds of other systems. So with this exploit, you can also then ... pivot around to Salesforce, or jump to Microsoft, or wherever."

Cybercrime Inc.: When hackers are better organized than IT

Cybercrime has transformed from isolated incidents into an organized industry. The large groups operate according to the same principles as international corporations. They have departments, processes, management levels, and KPIs. They develop software, maintain customer databases, and evaluate their success rates. ... Cybercrime now functions like a service chain. Anyone planning an attack today can purchase all the necessary components — from initial access credentials to leak management. Access brokers sell access to corporate networks. Botnet operators provide computing power for attacks. Developers deliver turnkey exploits tailored to known vulnerabilities. Communication specialists handle contact with the victims. ... What makes cybercrime so dangerous today is not just the technology itself, but the efficiency of its use. Attackers are flexible, networked, and eager to experiment. They test, discard, and improve — in cycles that are almost unimaginable in a corporate setting. Recruitment is handled like in startups. Job offers for developers, social engineers, or language specialists circulate in darknet forums. There are performance bonuses, training, and career paths. The work methods are agile, communication is decentralized, and financial motivation is clearly defined. ... Given this development, absolute security is unattainable. The crucial factor is the ability to quickly regain operational capability after an attack. Cyber resilience describes this competence — not only to survive crises but also to learn from them.