Abstract:This study addresses the limitations of traditional Customer Relationship Management (CRM) systems by analyzing the adoption and impact of Artificial Intelligence (AI) integration (AI-Powered CRM). Informed by the Technology…
logy Acceptance Model (TAM) for employee perception and the Resource-Based View (RBV) for strategic capability, the primary objective is to evaluate how AI-driven automation enhances customer service processes and, subsequently, impacts marketing efficiency. The research employs an exploratory qualitative case study design, utilizing in-depth interviews, document analysis, and system observation on a single organization to gather rich, contextual data. The results demonstrate that AI integration significantly accelerated service, with chatbots handling 65–70% of routine queries and drastically reducing response times. Operationally, these improvements fostered high employee acceptance (TAM). Strategically, the AI-Powered CRM generated refined predictive analytics, resulting in a 12–18% improvement in campaign conversion rates and efficient resource allocation, confirming that AI creates a valuable and difficult-to-imitate strategic capability (RBV). The study concludes that AI-Powered CRM is a critical enabler for both operational efficiency and long-term strategic competitiveness in digital markets.
Abstract:In an uncertain economic climate, a large global retailer used AI-powered spend intelligence to move $220 million from indirect operational costs toward high-impact R&D. In a difficult recession, this decisive step boosted…
ed revenue by 11%, demonstrating the transformative impact of effective capital management. This achievement contrasts with "spend blindness," where industry studies show most financial leaders struggle to link expenditure patterns to strategic growth outcomes and resort to reactive cost-cutting. This study addresses this crucial gap. A thorough mixed-methods approach including a global survey of 400 CFOs, longitudinal case studies of ten multinational organizations, and advanced predictive modeling substantiated a new paradigm. Research shows that companies that understand AI-driven spend orchestration develop 7.3% faster than competitors. This premium comes from a 37% improvement in the Growth Efficiency Ratio (GER), a critical statistic for translating savings into innovation, and 5.8 times more strategic investment opportunities than standard financial approaches allow. The Spend Intelligence Quotient (SIQ), a groundbreaking statistic that assesses financial agility through integrated spend monitoring, predictive analytics, and rapid capital reallocation, is key to this advantage. This paper introduces the empirically based Spend Orchestration Framework and the requirements for the 2025 AI Finance Stack to obtain SIQ >80, the empirically proven threshold for sustainable competitive advantage. The message is clear: finance chiefs must go beyond oversight. Today's CFO may use predictive contracting and algorithmic governance to turn spend data into strategic leverage, ensure resilience, and capture disproportionate value in.
Abstract:The increased integration of operational technology (OT), Internet of Things (IoT), and business IT systems has allowed sophisticated attackers to circumvent isolated security features and launch cross-platform assaults.…
Current fragmented techniques, with discrete detectors monitoring Modbus, Kubernetes, MQTT, or other domain-specific protocols, cannot handle cross-system risks. These methodologies overlook 68% of multi-vector marketing that uses both physical and digital channels. This study introduces a transfer learning architecture to integrate detection capabilities by correlating threats across protocols, devices, and settings. The architecture generates a unified feature space that extracts behavioral semantics from industrial control system logs, cloud telemetry, network traffic, and device-level signals to produce protocol-agnostic threat representations. Adversarial domain adaptation and semantic graph embeddings enable cross-domain knowledge transfer with minimum retraining. Security teams may now discover kill chains like infected cloud containers preceding illegal PLC command execution every 23 minutes. Validated against real-world attack datasets from water treatment facilities (OT) and cloud infrastructure (IT), the system achieved 93.4% cross-platform attack recall, a 41.3 percentage point improvement over prior methodologies. It reduced OT data labeling by 89% and false positives by 93.5%. This paradigm shift transforms threat correlation from a reactive, domain-specific process to adaptive intelligence, boosting resilience for critical infrastructure, industrial ecosystems, and smart environments facing cyber-physical hazards. The framework's practical validation in energy, industry, and vital infrastructure shows its importance in protecting an increasingly linked world.
Abstract:This study investigates the influence of artificial intelligence (AI) integration on strategic financial management in large corporations. Focusing on a sample of 20 Fortune 500 companies from diverse industries, the research…
earch employs a quantitative, descriptive-analytical approach utilizing secondary data from financial reports and AI system logs. The findings reveal that AI adoption significantly enhances forecasting accuracy, risk identification, and operational efficiency, while also enabling financial managers to redirect resources toward creative and strategic initiatives. However, the study also identifies challenges related to data quality, ethical considerations, and skill gaps in AI utilization. The results highlight the importance of a balanced approach that combines AI-driven insights with managerial intuition to maximize value creation in the digital age.
Abstract:The era of artificial intelligence (AI) has brought significant changes in Strategic Human Resource Management (SHRM). This study aims to explore organizational adaptation strategies in facing the integration of AI in SHRM…
RM after 2024. Using the Scoping Review method, this study identifies key trends, challenges, and best strategies in implementing AI in HR management. The review results show that AI improves efficiency in recruitment, performance evaluation, and employee skills development, but also presents ethical challenges such as algorithmic bias and personal data protection. In addition, companies that are successful in adopting AI implement reskilling and upskilling strategies to ensure workforce readiness. This study provides insights for academics and practitioners in developing HR policies that balance technological efficiency and a human value-based approach.
Abstract:Artificial intelligence is likely to have a significant impact on marketing strategies and customer behaviors in the years ahead. Research in this field has grown considerably, demonstrating AI's ability to simulate human…
n behavior and perform tasks intelligently. With growing interest among marketing researchers and practitioners, this research aims to provide an overview of the evolution of both marketing and AI research fields. This paper explores the emerging role of artificial intelligence in personalized engagement marketing, which focuses on creating, communicating, and delivering customized offerings to customers. Utilizing the Systematic Literature Review technique, we examined over 300 academic articles to uncover prevalent themes and gain a deeper understanding of current AI utilization in marketing. We then propose a plan for future research that examines potential changes in marketing strategies and customer behaviors while emphasizing critical policy considerations related to privacy, bias, and ethics. The implications for marketing managers are discussed along with predictions about how AI will impact branding and customer management practices going forward. Our research highlighted several benefits of integrating AI into marketing such as improved customer interactions, increased revenue, reduced expenses, and enhanced overall efficiency. However, this research also pointed out areas requiring further investigation including challenges posed by AI integration like shortage of skilled personnel and data privacy concerns.
Abstract:Artificial Intelligence has become a transformative technology in the field of financial technology, leveraging advanced algorithms and machine learning to identify risks and make informed decisions. However, its widespread…
ead adoption presents new challenges related to ethical use, data privacy, security concerns, potential bias, and discrimination. This study aims to explore the benefits of AI-based risk management in Fintech while highlighting associated challenges and providing recommendations. This research utilises the systematic review methodology to analyse existing literature and identify important patterns, gaps, and areas for further investigation. The study utilised data gathered from the Scopus database to obtain credible scholarly materials. Research data was collected from a variety of countries including the United States, China, European nations, and other Asian countries in order to develop a comprehensive understanding of AI-based risk management on a global scale. The findings highlight the crucial role of ethical considerations in implementing AI-based risk management systems to ensure fairness, transparency, and accountability. Moreover, the fintech industry needs to establish strong data protection measures and address issues related to bias and discrimination in order to instil trust and uphold public confidence in AI-based risk management. Future research should emphasise assessing the effectiveness of different algorithms and approaches while also examining potential regulatory frameworks and legal implications associated with AI-based risk management strategies.
Abstract:Perkembangan pesat teknologi Artificial Intelligence (AI) telah mengubah lanskap pendidikan tinggi secara signifikan, terutama dengan hadirnya tutor virtual berbasis AI yang mampu memberikan umpan balik cepat, tepat, dan…
personal. Analisis Real merupakan salah satu mata kuliah yang paling menantang dalam program pendidikan matematika karena sifat abstraknya sering menyebabkan rendahnya self-efficacy mahasiswa. Penelitian ini bertujuan menganalisis pengaruh pemanfaatan AI sebagai tutor virtual terhadap self-efficacy mahasiswa Pendidikan Matematika Universitas Asahan yang menempuh mata kuliah Analisis Real. Penelitian menggunakan pendekatan kuantitatif dengan desain quasi-experimental one-group pretest-posttest, melibatkan 15 mahasiswa yang dipilih melalui purposive sampling. Instrumen angket self-efficacy dikembangkan berdasarkan tiga dimensi Bandura (magnitude, strength, generality), divalidasi melalui expert judgment dengan Cronbach’s Alpha sebesar 0,84. Hasil analisis deskriptif menunjukkan peningkatan rata-rata skor self-efficacy dari 65,67 (pre-test, kategori sedang) menjadi 79,93 (post-test, kategori tinggi), dengan peningkatan sebesar 21,7%. Uji Wilcoxon Signed-Rank Test menghasilkan nilai Z = −3,408 dengan p-value = 0,001 (p < 0,05), yang mengkonfirmasi terdapat perbedaan signifikan self-efficacy mahasiswa sebelum dan sesudah intervensi enam minggu menggunakan AI tutor virtual.
The rapid development of Artificial Intelligence (AI) technology has significantly transformed higher education, particularly through AI-based virtual tutors capable of providing fast, precise, and personalized feedback. Real Analysis, one of the most challenging mathematics education courses, frequently causes low self-efficacy among students due to its abstract nature and demands for formal proof-writing. This study examines the effect of utilizing AI as a virtual tutor on self-efficacy of mathematics education students at Universitas Asahan. A quantitative quasi-experimental one-group pretest-posttest design was employed with 15 students selected via purposive sampling. The self-efficacy questionnaire was based on Bandura’s three dimensions: magnitude, strength, and generality, validated by expert judgment with Cronbach’s Alpha coefficient of 0.84. Descriptive analysis results showed an increase in mean self-efficacy scores from 65.67 (pre-test, moderate category) to 79.93 (post-test, high category), representing a 21.7% improvement. The Wilcoxon Signed-Rank Test yielded Z = −3.408 with p-value = 0.001 (p < 0.05), confirming a significant difference in student self-efficacy before and after the six-week AI virtual tutor intervention.
Abstract:Kegiatan pengabdian kepada masyarakat ini bertujuan untuk meningkatkan pemahaman dan keterampilan mahasiswa dalam memanfaatkan Artificial Intelligence (AI) pada penulisan karya ilmiah berbasis Al-Qur’an secara efektif dan…
dan etis. Metode yang digunakan adalah pendekatan Service Learning yang mengintegrasikan pembelajaran konseptual dengan praktik langsung, melibatkan 30 mahasiswa sebagai peserta. Pelaksanaan kegiatan dilakukan melalui beberapa tahapan, yaitu penyampaian materi, diskusi dan tanya jawab, praktik penulisan, serta refleksi dan evaluasi. Hasil kegiatan menunjukkan bahwa peserta mengalami peningkatan pemahaman terhadap konsep AI dan penerapannya dalam penulisan ilmiah, yang ditunjukkan melalui keterlibatan aktif selama proses pembelajaran serta kemampuan menghasilkan karya ilmiah secara sistematis. Selain itu, peserta juga menunjukkan peningkatan kemampuan berpikir kritis dalam menyikapi penggunaan AI, khususnya terkait aspek etika dan validitas informasi. Meskipun demikian, masih terdapat variasi kemampuan peserta dalam menyusun karya ilmiah serta potensi ketergantungan terhadap teknologi. Oleh karena itu, diperlukan pendampingan lanjutan dan penguatan literasi akademik serta etika penggunaan AI agar hasil pembelajaran lebih optimal dan berkelanjutan.
Abstract:(Abstrak) Perkembangan teknologi kecerdasan buatan (Artificial Intelligence/AI) membuka peluang yang signifikan bagi guru dalam meningkatkan kualitas perencanaan dan pelaksanaan pembelajaran. Namun, pemanfaatan teknologi…
gi pembelajaran berbasis AI di SMP lingkup Kabupaten Kolaka Timur belum sepenuhnya optimal, khususnya dalam perancangan kegiatan pembelajaran dan penyusunan Rencana Pelaksanaan Pembelajaran (RPP). Kegiatan Pengabdian kepada Masyarakat (PKM) ini bertujuan untuk memperkuat kapasitas profesional guru melalui pelatihan pemanfaatan aplikasi pembelajaran berbasis AI, seperti Canva, Word AI, dan ChatGPT, guna mendukung perencanaan pembelajaran yang efektif dan inovatif.
Pelaksanaan kegiatan dilakukan melalui tahapan penyusunan materi pelatihan, kegiatan tatap muka, demonstrasi, praktik langsung terbimbing, latihan mandiri, serta pendampingan intensif. Peserta kegiatan terdiri atas guru dan kepala sekolah, dengan fasilitator utama dosen dari Fakultas Keguruan dan Ilmu Pendidikan Universitas Lakidende.
Hasil kegiatan menunjukkan adanya peningkatan pemahaman guru terhadap konsep teknologi pembelajaran digital serta kemampuan dalam merancang perangkat pembelajaran berbasis AI, meliputi media presentasi, lembar kerja digital, dan RPP berbantuan AI. Guru menunjukkan tingkat partisipasi dan antusiasme yang tinggi serta mampu menghasilkan rancangan pembelajaran yang lebih kreatif, efektif, dan relevan dengan karakteristik mata pelajaran. Secara keseluruhan, kegiatan PKM ini memberikan kontribusi positif terhadap peningkatan kompetensi pedagogik dan profesional guru dalam pemanfaatan teknologi AI secara berkelanjutan, sekaligus menjadi upaya strategis dalam mendukung transformasi digital sekolah dan peningkatan kualitas pembelajaran.