THE IMPACT OF ARTIFICIAL INTELLIGENCE ON THE DEVELOPMENT OF PREDICTIVE COMPETENCE IN MODERN SPECIALISTS
The relevance of this study stems from the rapid development of artificial intelligence (AI), particularly large language models and generative technologies, which are profoundly transforming professional activity. These changes significantly influence the formation of predictive competence – a cr...
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Alfred Nobel University
2025-06-01
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| Series: | Alfred Nobel University Journal of Pedagogy and Psychology |
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| Online Access: | https://pedpsy.duan.edu.ua/images/PDF/2025/1/16.pdf |
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| author | Viacheslav Osadchyi Maksym Pavlenko Liliia Pavlenko Oleksii Sysoiev Vladyslav Kruglyk |
| author_facet | Viacheslav Osadchyi Maksym Pavlenko Liliia Pavlenko Oleksii Sysoiev Vladyslav Kruglyk |
| author_sort | Viacheslav Osadchyi |
| collection | DOAJ |
| description | The relevance of this study stems from the rapid development of artificial intelligence (AI), particularly
large language models and generative technologies, which are profoundly transforming professional
activity. These changes significantly influence the formation of predictive competence – a crucial human
capacity for reasoned forecasting and decision-making under uncertainty. Empirical data confirm the
high accuracy of AI-generated forecasts, sometimes surpassing that of humans, and indicate improved
professional productivity when AI is used effectively. At the same time, diverse adaptation patterns to
AI use necessitate a rethinking of the role of human judgement and raise concerns about technological
dependency, algorithmic bias, and unequal access to innovation. These challenges call for a reorientation of
educational approaches, placing emphasis on critical thinking and skills for effective human-AI interaction.
The purpose of the study is to conduct a comprehensive analysis and theoretical substantiation of
the impact of modern AI technologies – particularly large language models and generative AI – on the
development and transformation of professionals’ predictive competence.
Research objectives are as follows: to conceptualise predictive competence within the context
of digital transformation; to analyse structural shifts in its key components (cognitive, regulatory,
and communicative); to explore the mechanisms of AI’s influence on cognitive predicting processes; to
systematise potential advantages and risks associated with the integration of AI in professional contexts.
The study employs theoretical methods such as analysis, synthesis, and generalisation of findings
from interdisciplinary research, as well as conceptual and comparative analysis of human-AI interaction
models and the evolving essence of predictive competence.
AI demonstrably increases the efficiency of forecasting processes but simultaneously transforms their
nature – from autonomous human-generated predictions to the management of hybrid human-machine
systems. This shift requires professionals to acquire new skills, including critical evaluation and validation of
AI outputs, prompt engineering, and the integration of AI-generated insights into complex decision-making.
The most significant transformations influence the cognitive, regulatory, and communicative components of
predictive competence. The dual nature of AI’s impact is evident – offering enhanced analytical capabilities while posing risks of hallucinations, cognitive inertia, and increased digital inequality. Accordingly, the
professional role evolves from that of executor to analyst, moderator, and ethical regulator of forecasting
processes.
Conclusions. Artificial intelligence is irreversibly reshaping the landscape of professional activity, par-
ticularly in the domain of forecasting. Its influence on predictive competence is deep, multifaceted, and at
times contradictory. Maximising its benefits while mitigating associated risks requires a proactive, critical,
and adaptive attitude from professionals and educators alike. To this end, educational programmes should
be enriched with: practice-oriented integration of AI tools into professional curricula; targeted development
of skills for evaluating AI outputs; competence in prompt engineering for forecasting; the promotion of
metacognitive awareness. These measures will enable the preparation of specialists who do not merely un-
derstand AI but can employ it purposefully, critically, and responsibly to enhance their predictive capacities. |
| format | Article |
| id | doaj-art-b1ea8cdc14ae47a3b9c7ebef76ab577a |
| institution | DOAJ |
| issn | 3041-2196 3041-220X |
| language | deu |
| publishDate | 2025-06-01 |
| publisher | Alfred Nobel University |
| record_format | Article |
| series | Alfred Nobel University Journal of Pedagogy and Psychology |
| spelling | doaj-art-b1ea8cdc14ae47a3b9c7ebef76ab577a2025-08-20T03:13:42ZdeuAlfred Nobel UniversityAlfred Nobel University Journal of Pedagogy and Psychology3041-21963041-220X2025-06-0112916717810.32342/3041-2196-2025-1-29-15THE IMPACT OF ARTIFICIAL INTELLIGENCE ON THE DEVELOPMENT OF PREDICTIVE COMPETENCE IN MODERN SPECIALISTSViacheslav Osadchyi0Maksym Pavlenko1Liliia Pavlenko2Oleksii Sysoiev3Vladyslav Kruglyk4Borys Grinchenko Kyiv Metropolitan UniversityBerdyansk State Pedagogical UniversityBerdyansk State Pedagogical UniversityMazovian University in PłockBohdan Khmelnytsky Melitopol State Pedagogical UniversityThe relevance of this study stems from the rapid development of artificial intelligence (AI), particularly large language models and generative technologies, which are profoundly transforming professional activity. These changes significantly influence the formation of predictive competence – a crucial human capacity for reasoned forecasting and decision-making under uncertainty. Empirical data confirm the high accuracy of AI-generated forecasts, sometimes surpassing that of humans, and indicate improved professional productivity when AI is used effectively. At the same time, diverse adaptation patterns to AI use necessitate a rethinking of the role of human judgement and raise concerns about technological dependency, algorithmic bias, and unequal access to innovation. These challenges call for a reorientation of educational approaches, placing emphasis on critical thinking and skills for effective human-AI interaction. The purpose of the study is to conduct a comprehensive analysis and theoretical substantiation of the impact of modern AI technologies – particularly large language models and generative AI – on the development and transformation of professionals’ predictive competence. Research objectives are as follows: to conceptualise predictive competence within the context of digital transformation; to analyse structural shifts in its key components (cognitive, regulatory, and communicative); to explore the mechanisms of AI’s influence on cognitive predicting processes; to systematise potential advantages and risks associated with the integration of AI in professional contexts. The study employs theoretical methods such as analysis, synthesis, and generalisation of findings from interdisciplinary research, as well as conceptual and comparative analysis of human-AI interaction models and the evolving essence of predictive competence. AI demonstrably increases the efficiency of forecasting processes but simultaneously transforms their nature – from autonomous human-generated predictions to the management of hybrid human-machine systems. This shift requires professionals to acquire new skills, including critical evaluation and validation of AI outputs, prompt engineering, and the integration of AI-generated insights into complex decision-making. The most significant transformations influence the cognitive, regulatory, and communicative components of predictive competence. The dual nature of AI’s impact is evident – offering enhanced analytical capabilities while posing risks of hallucinations, cognitive inertia, and increased digital inequality. Accordingly, the professional role evolves from that of executor to analyst, moderator, and ethical regulator of forecasting processes. Conclusions. Artificial intelligence is irreversibly reshaping the landscape of professional activity, par- ticularly in the domain of forecasting. Its influence on predictive competence is deep, multifaceted, and at times contradictory. Maximising its benefits while mitigating associated risks requires a proactive, critical, and adaptive attitude from professionals and educators alike. To this end, educational programmes should be enriched with: practice-oriented integration of AI tools into professional curricula; targeted development of skills for evaluating AI outputs; competence in prompt engineering for forecasting; the promotion of metacognitive awareness. These measures will enable the preparation of specialists who do not merely un- derstand AI but can employ it purposefully, critically, and responsibly to enhance their predictive capacities.https://pedpsy.duan.edu.ua/images/PDF/2025/1/16.pdfpredictive competenceartificial intelligence (ai)large language models (llm)generative aiprofessional developmenthigher educationcognitive processeshuman-ai interaction / human- machine interactionskill transformationcritical thinking |
| spellingShingle | Viacheslav Osadchyi Maksym Pavlenko Liliia Pavlenko Oleksii Sysoiev Vladyslav Kruglyk THE IMPACT OF ARTIFICIAL INTELLIGENCE ON THE DEVELOPMENT OF PREDICTIVE COMPETENCE IN MODERN SPECIALISTS Alfred Nobel University Journal of Pedagogy and Psychology predictive competence artificial intelligence (ai) large language models (llm) generative ai professional development higher education cognitive processes human-ai interaction / human- machine interaction skill transformation critical thinking |
| title | THE IMPACT OF ARTIFICIAL INTELLIGENCE ON THE DEVELOPMENT OF PREDICTIVE COMPETENCE IN MODERN SPECIALISTS |
| title_full | THE IMPACT OF ARTIFICIAL INTELLIGENCE ON THE DEVELOPMENT OF PREDICTIVE COMPETENCE IN MODERN SPECIALISTS |
| title_fullStr | THE IMPACT OF ARTIFICIAL INTELLIGENCE ON THE DEVELOPMENT OF PREDICTIVE COMPETENCE IN MODERN SPECIALISTS |
| title_full_unstemmed | THE IMPACT OF ARTIFICIAL INTELLIGENCE ON THE DEVELOPMENT OF PREDICTIVE COMPETENCE IN MODERN SPECIALISTS |
| title_short | THE IMPACT OF ARTIFICIAL INTELLIGENCE ON THE DEVELOPMENT OF PREDICTIVE COMPETENCE IN MODERN SPECIALISTS |
| title_sort | impact of artificial intelligence on the development of predictive competence in modern specialists |
| topic | predictive competence artificial intelligence (ai) large language models (llm) generative ai professional development higher education cognitive processes human-ai interaction / human- machine interaction skill transformation critical thinking |
| url | https://pedpsy.duan.edu.ua/images/PDF/2025/1/16.pdf |
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