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Secure SSDLC in the age of generative AI

Sat, 26 Sep 2026 12:01:21 +0200

Why traditional SSDLC is vulnerable to GenAI

In 2026, we are witnessing a transition from experimental use of large language models to their full integration into enterprise environments. Traditional software development life cycle (SSDLC) processes, which relied on static analyzers and manual reviews, are struggling to keep pace with the speed at which AI generates code. According to Gartner, by 2028, over 50% of enterprises will utilize specialized AI security platforms, highlighting the critical need for transforming development processes.

Managed autonomy: architectural control of AI agents in BPM processes

Fri, 25 Sep 2026 12:01:20 +0200

Why excessive agency is a critical risk for corporate AI

Integrating generative AI into business processes opens new opportunities but creates significant vulnerabilities. The OWASP 'Top 10 Risk & Mitigations for LLMs and Gen AI Apps 2025' report identifies 'Excessive Agency' as a distinct risk class. This occurs when an AI model is granted the ability to perform actions beyond its intended business scope. Typical examples include an agent attempting to approve a financial transaction exceeding a user's authorization limit or accessing sensitive customer data unnecessary for the specific task.

Data sovereignty and LLM in enterprise: hybrid cloud strategies

Thu, 24 Sep 2026 12:01:05 +0200

Infrastructure readiness: why 13% of companies outperform the market

According to the Cisco AI Readiness Index 2025, only 13% of organizations worldwide are classified as "Pacesetters." These leaders outperform competitors through infrastructure readiness rather than just model adoption. The primary challenge for CTOs today is not AI capabilities, but ensuring data sovereignty when integrating LLMs into hybrid cloud environments. When data is transmitted to third-party AI providers without proper control, critical security and compliance risks emerge.

Integrating satellite broadband into enterprise BSS/OSS infrastructure

Wed, 23 Sep 2026 12:01:18 +0200

Challenges of satellite network integration

According to the Ericsson Mobility Report 2025, the number of satellite broadband subscriptions is projected to grow from 9 million at the end of 2025 to 30 million by 2031. For large enterprises, this forecasted growth presents a new challenge: existing telecom infrastructure, designed for stable terrestrial channels, becomes a bottleneck when integrating LEO/MEO segments.

Traditional monolithic BSS/OSS systems are not adapted to the dynamic parameters of satellite networks, where latency and jitter metrics fluctuate constantly due to orbital dynamics and weather conditions. Furthermore, the lack of API standardization among various satellite providers complicates billing and quality of service monitoring.

Validating algorithmic solutions in OT: controlling AI-driven loops per IEC 62443

Tue, 22 Sep 2026 12:01:11 +0200

NIST SP 800-82 updates and critical infrastructure security guidelines require industrial enterprises to clearly validate algorithmic solutions. In an OT environment, where system availability is a priority, AI implementation must not disrupt the deterministic logic of ICS/SCADA operations.

Why OT determinism rejects AI "black boxes"

Industrial systems require predictability, whereas AI is probabilistic by nature. According to ISA/IEC 62443, which covers over 20 industries, every automation component must be validated for security compliance. An algorithmic error in a control loop can threaten the integrity and availability of critical infrastructure.

AI quality control in corporate document management

Mon, 21 Sep 2026 12:01:06 +0200

Businesses are massively transitioning from pilot AI experiments to implementing Intelligent Document Processing (IDP). However, in practice, leaders face a critical gap: AI models are probabilistic by nature, while corporate systems and legally significant processes are deterministic. When an algorithm acts as a "black box," the cost of error (e.g., incorrect data classification) outweighs the benefits of automation.

From pilots to industrial IDP: why AI requires architectural oversight

According to the AIIM methodology, mature IDP systems are impossible without high-quality data and clear fallback rules. The problem arises when businesses attempt to delegate decision-making to AI without control mechanisms. It is important to remember that, according to Ukrainian Law No. 851-15, the legal force of an electronic document cannot be denied solely due to its electronic form—this obliges companies to ensure process integrity at every stage.

Infrastructure readiness for AI agents: why domain data models are critical

Sun, 20 Sep 2026 12:01:05 +0200

In 2025, the focus of artificial intelligence implementation in the enterprise environment shifted from LLM experimentation to building robust infrastructure foundations. According to the Cisco AI Readiness Index 2025, based on a global study of over 8,000 leaders across 30 countries and 26 industries, data readiness is a key barrier to deriving business value from AI. Many enterprises face risks because they perceive AI agents as a "black box," overlooking the importance of a contextual data map.

Managing telecom infrastructure vulnerabilities with SBOM

Sat, 19 Sep 2026 12:01:28 +0200

Why code visibility has become the new security perimeter in telecom

According to the ENISA Threat Landscape 2025 report, digital infrastructure and services accounted for approximately 27.7% of data breaches between July 2024 and June 2025. For telecom operators, this indicates a critical supply chain vulnerability. While the network perimeter is typically protected, the internal architecture of BSS/OSS systems often remains a "blind spot" due to a mix of legacy code and modern cloud components, complicating timely vulnerability detection.

Procurement automation for critical infrastructure: from IIoT telemetry to ERP integration

Thu, 17 Sep 2026 12:02:50 +0200

Why calendar-based maintenance creates hidden risks

Traditional maintenance schedules based solely on time intervals are a source of inefficiency for critical infrastructure enterprises. This approach leads to premature replacement of functional parts or, conversely, missing critical wear, which triggers emergency shutdowns. As emphasized in NIST SP 800-82, in operational technology (OT) environments, system availability often takes precedence over confidentiality, making failure due to unpredictable wear unacceptable.

Architectural bridge between OT and ERP

The key challenge of automation is the gap between the OT circuit (PLC, sensors) and the ERP system where financial decisions are made. Reliable operation requires an architectural bridge that ensures data collection via IIoT. Using the OPC UA standard allows for the normalization of heterogeneous equipment data, ensuring platform-independent interoperability. This is the foundation upon which predictive analysis is built.

On-premises AI agent integration: ensuring NIS2 compliance

Tue, 08 Sep 2026 11:11:19 +0200

The ENISA Threat Landscape 2025 report notes an alarming trend: organizations subject to the NIS2 directive were targeted in 53.7% of all recorded incidents. Approximately 27.7% of data breaches occur in the digital infrastructure and services sector. For critical infrastructure enterprises and their digital partners, integrating artificial intelligence into the corporate landscape requires a radical rethinking of architectural approaches. Using external cloud APIs for autonomous AI agents creates uncontrollable supply chain security risks. A reliable scenario for sectors with high requirements is transitioning to on-premises integration, where data processing is controlled within the enterprise's secure perimeter.

Managing AI agent risks in enterprise business processes

Tue, 08 Sep 2026 11:05:55 +0200

Moving from generative AI experiments to deploying autonomous AI agents (agentic workflows) creates a critical challenge: how to grant an agent autonomy without the risk of unauthorized system actions. Businesses want to delegate routine operations to AI but face the dilemma of losing control over confidential data and the risk of the agent exceeding the authority of the employee it replaces.

AI agent security in corporate processes is achieved not by trying to make a Large Language Model (LLM) perfectly reliable, but by strictly limiting its actions within BPMN/DMN models and role-based access (RBAC/RLS) at the base platform level.

Software supply chain security: architectural isolation for NIS2 compliance

Mon, 07 Sep 2026 11:17:42 +0200

The modern cyber threat landscape is forcing critical infrastructure enterprises to rethink their approach to third-party software integration. According to the ENISA Threat Landscape 2025 report, based on an analysis of 4,875 incidents between July 1, 2024, and June 30, 2025, organizations classified as essential entities under the NIS2 directive accounted for 53.7% of all victims. Furthermore, the digital infrastructure and services sector accounted for approximately 27.7% of recorded data breaches. These figures clearly indicate that the software supply chain has become a critical attack vector.

AI document automation: audit architecture and compliance

Mon, 07 Sep 2026 11:10:20 +0200

As organizations shift from traditional enterprise content management (ECM) systems to intelligent information management in 2026, the ability to audit AI-driven document processing is no longer optional. Today, it is a fundamental regulatory requirement. CIOs and compliance officers face the critical risk of a "black box" in automation: when AI algorithms classify documents and extract data without a transparent audit trail, verifying data integrity during regulatory inspections becomes impossible.

The "black box" trap: why probabilistic AI requires control

Traditional electronic document management systems operate on deterministic rules, where every user action is strictly recorded. In contrast, intelligent document processing (IDP) systems use probabilistic machine learning models. They independently make decisions regarding document types and the fields that need to be extracted.

Autonomous AI agent orchestration in telecom networks

Sun, 06 Sep 2026 11:08:20 +0200

Over 90 service providers worldwide have already launched or are preparing for the commercial rollout of 5G Standalone (SA) networks, according to the Ericsson Mobility Report (November 2025). This technological transition has drastically increased the complexity of infrastructure management. The telecommunications industry must move beyond simple text-based AI chatbots toward autonomous AI agents. However, autonomous networks cannot function solely on AI without human oversight—they require deep integration into the IT landscape to perform routine operations.

Auditing IIoT control actions: building accountability architecture

Sun, 06 Sep 2026 11:02:49 +0200

The Industrial Internet of Things (IIoT) has definitively crossed the line between passive observation and active control. Previously, edge devices and sensors primarily collected telemetry, but today they are directly integrated into automated control loops. Edge AI algorithms independently make decisions about changing technological modes, and operators remotely send commands via communication networks.

This technological shift creates new challenges for operational security. The updated NIST SP 800-82 standard establishes a critical requirement: as systems transition to active control, every automated and manual signal must have a complete and immutable audit trail. Without a dedicated Control Audit Layer, enterprises lose the ability to distinguish between human actions, algorithm errors, and unauthorized interference.

Software supply chain security under NIS2: from verification to isolation

Sat, 05 Sep 2026 11:08:58 +0200

The modern cyber threat landscape has finally dispelled any illusions IT architects may have held regarding the security of third-party code. According to the ENISA Threat Landscape 2025 report, software supply chain attacks have become one of the most critical vectors for compromising corporate systems. Data from the European regulator, which analyzed 4,875 incidents between July 1, 2024, and June 30, 2025, indicates that essential entities under NIS2 accounted for 53.7% of all affected organizations. Furthermore, digital infrastructure and services were the source of approximately 27.7% of confidential data breaches.

Modernizing legacy ECM systems without big migrations

Sat, 05 Sep 2026 11:02:57 +0200

In the corporate IT solutions segment, approaches to infrastructure updates are shifting. The era of high-risk "big bang" migrations is giving way to an orchestration-first strategy. This allows for modernizing legacy ECM systems without interrupting operations by separating the interface layer from physical data storage.

The legacy ECM trap: why "big bang" migration threatens business

Large enterprises are often held hostage by monolithic legacy systems. Maintaining them is a financial burden, and their closed architecture hinders the adoption of modern tools. At the same time, replacing the system entirely through massive data transfers carries critical risks. Attempting to move millions of documents and their relationships in one go threatens metadata integrity and can lead to business process downtime.

Trust architecture in automated processes: Digital Provenance as a NIS2 requirement

Fri, 04 Sep 2026 11:16:31 +0200

The concept of business process automation has long evolved under the banner of execution speed and operational cost reduction. However, modern risk management realities, particularly the implementation of strict European NIS2 directive requirements, are shifting the focus. Today, operational speed alone is insufficient; evidentiary integrity, or Digital Provenance (the digital origin of data and decisions), is becoming critical. The lack of mechanisms that allow auditors to indisputably prove how, by whom, and based on what logic a decision was made or data was changed in the system, is turning into critical technical debt.

Integrating corporate VoIP cores with private 5G networks

Fri, 04 Sep 2026 11:10:51 +0200

With the growth of private 5G Standalone (SA) deployments, enterprise communication architects face the challenge of merging new mobile infrastructure with existing VoIP networks. According to the Ericsson Mobility Report 2025, over 90 operators have launched or are in the soft-launch phase of 5G Standalone. The goal of enterprise-level integration is not just to provide physical connectivity between domains, but to create a unified Least Cost Routing (LCR) contour and unified billing.

Data-centric architecture for AI agents: avoiding infrastructure bloat

Thu, 03 Sep 2026 11:13:22 +0200

Euphoria around generative AI in the enterprise sector is giving way to rigorous engineering pragmatism. Businesses have realized that the effectiveness of AI agents is determined not so much by the power of large language models (LLMs) as by infrastructure maturity and corporate data quality. According to the Cisco AI Readiness Index 2025, only 13% of organizations are classified as "Pacesetters"—leaders that consistently derive real value from AI implementation. Their main differentiator is a systematic focus on data readiness. Most companies, after initial pilots, encounter "AI bloat"—chaotic infrastructure expansion where uncontrolled model requests cause unpredictable spikes in cloud bills.