In the article, the author conducts a retrospective analysis of the main trends in the development of artificial intelligence and other related technologies of the Fourth Industrial revolutions for the period from 2013 to 2026, the interim results of the global introduction of artificial intelligence in the economic, social and individual psychological context are summed up. Further, based on qualitative analysis, expert assessments and a risk-based approach, an author's classification of threats and risks of accelerated implementation is presented artificial intelligence technologies for business and humans.

Despite the growing popularity of generative artificial intelligence, statistics show low levels of successful implementations in company processes. At the same time, there is a gap in systematic studies of the causes of such failures.
The purpose of the work is to analyze the practices of using generative artificial intelligence as a tool for automating processes (both successful and failed), as well as to identify typical risks and their causes. The study was carried out on the basis of statistical data, scientific papers and information about projects from open sources. Based on the collected risk data in each subject area, common application risks were identified and a matrix of causes, sources and consequences of each of the risks for the company was compiled. In addition, the gradual degradation of artificial intelligence tools was considered to compile a complete picture of the situation on the generative neural network market.
Based on the study, it was concluded that a complete uncontrolled model of process automation by generative artificial intelligence is impossible due to its instability in the long term. The proposed risk register serves as the basis for developing a more rational and cautious approach to the introduction of generative artificial intelligence, shifting the focus from total automation to a controlled hybrid model.

The article is devoted to the identification and assessment of cyber risks as threats to digital control systems at a gas transportation enterprise. A qualitative assessment of 12 identified risks was carried out, including the construction of «probability/consequence» and «significance/ controllability» matrices, as a result of which six risks were classified as material and six as immaterial. For each risk, risk management measures were developed; for material risks, internal control procedures were developed; and for all 12 risks, key risk indicators (KRIs) with threshold values were developed.

The article examines methods for assessing cyber risks from the perspective of their application in insurance. The main groups of cyber risk assessment methods are systematized, and a methodological approach to selecting and combining these methods for insurance purposes is proposed, based on the principle of «methods from tasks». Within this approach, a system of criteria for the suitability of methods for insurance companies is developed, including requirements for data, scalability, and sensitivity to preventive information security measures, interpretability for underwriters and actuaries, as well as the ability to account for aggregate and systemic cyber risk at the portfolio level. The areas of application for various cyber risk assessment methods are demonstrated in the tasks of underwriting, rate-setting, limit selection, deductible configuration et al.

The article addresses the problem of assessing risks to the economic security of an organization in the context of digital transformation. It is shown that traditional qualitative and quantitative risk assessment methods have limited applicability under conditions of high uncertainty inherent in digital transformation processes. In this regard, a result-oriented approach is proposed, based on the analysis of the dynamics of key performance indicators of the organization.
A dynamic model of economic security is developed, in which the state of the organization is described by a system of normalized indicators considered as functions of time. An integral indicator of the level of economic security is introduced, interpreted as a functional of the set of indicators, and its probabilistic interpretation is proposed as the probability of the system remaining within an admissible state.
It is shown that the implementation of digital technologies affects the dynamics of economic indicators through a controlled digital transformation factor, which necessitates the analysis of the economic security level as a stochastic process. A risk criterion is proposed in the form of the probability of reaching a critical level of economic security, allowing the consideration of extreme adverse scenarios.
An integral approach to assessing economic security is developed, taking into account the dynamics of indicators over a given time interval. In addition, a classification of risk zones is proposed, enabling the practical application of modeling results in managerial decision-making. The obtained results can be used in the development of decision-support methods under digital transformation conditions.

Development and testing of a modified methodology for assessing the economic efficiency of geological and technical measures in the oil and gas industry, taking into account risks affecting the financial result of activities.
The paper uses discounted cash flow methods, variance analysis based on the weighted moving average and moving variance, the real options method based on the PERT distribution, as well as the expected cash value method (EMV analysis). The calculations were based on data from the Srednebotuobinskoye oil and gas condensate field for a portfolio of 31 geological and technical measures planned for the period 2026-2029.
A modified NPV formula differentiating risk adjustment factors for positive and negative cash flows is proposed. The developed classification of risks of geological and technical measures was taken into account in the context of cause classes with calculated correction factors. Based on PERT modeling of stochastic deviations in oil and gas condensate production, probabilistic outcome scenarios were generated; a portfolio of activities is ranked through EMV analysis. It was shown that excluding risks, the total net present value of the portfolio is overestimated by 1,018 million rubles. (39%), and 11 out of 31 measures that looked effective in the standard DCF assessment, with comprehensive risk accounting, demonstrate a negative value of the expected cash value.
This determines the purpose of this study - to develop and test a modified methodology for investment assessment of geological and technical measures that correctly reflects risks. The proposed methodology makes it possible to eliminate the systematic overestimation of efficiency estimates characteristic of traditional DCF models, as well as reduce the risks of making incorrect management decisions and incurring waste costs. As a result, the financial result is maximized in conditions of limited resources. The methodology is universal and applicable to any oil and gas company that uses key investment performance indicators to make strategic decisions.

The proposed study is a continuation of the scientific work «Methodological Aspects of Legal Risk Monitoring and Assessment for an Energy Company», published in the journal «Issues of Risk Analysis» in december 2025. This article discusses the problem of adapting the Consolidated Legal Risk Index (CLRI) methodology for use in construction project management. Proposed are: a classification of selected indicators by legal risk groups, a formal mechanism for selecting relevant partial indices and indicators by project phase using an activity function and a twolevel proportional weight renormalization procedure, a phase-based CLRI as a resultant measure, formal procedure for calculating the cascading legal risk index.