Artificial Intelligence in Modern Computing: A Comprehensive Review of Applications, Challenges, and Future Trends

Abstract

Artificial intelligence (AI) has evolved from a novelty to a necessity in today’s world. By consolidating the existing secondary quantitative indicators and analyzing the cross-cutting data, this study investigated the current state of AI, its possibilities, and problems. Differing from the conventional review, the paper utilized the latest practices, possibilities, investments, infrastructure, and regulations about AI as the arguments and extracted the comparative data from them. In particular, the article analyzed the Stanford AI Index 2026, International Energy Agency’s report ‘Energy and AI’, NIST AI Risk Management Framework, EU Artificial Intelligence Act, UNESCO guidelines, and many studies related to AI in healthcare, cybersecurity, and computing. The descriptive statistics of the studies demonstrate that 88% of the organizations have adopted AI in 2025, and 70% of them have utilized generative AI technologies in at least one area of their operations, implying that the difference between the lines is 18%. Meanwhile, the utilization of AI agents is still below 10%, which reflects the difference of 78% between AI agents and overall AI applications. Moreover, the performance of models on SWE-bench Verified increased from 60% to almost 100% per annum, and the electric power consumption of data centers is forecasted to increase from 415 TWh in 2024 to 945 TWh in 2030, which is 127.7% higher and constitutes 14.7% average annual growth. The domain scoring analysis also identified cybersecurity, finance, healthcare, and industrial systems as the highest AI impact areas needing governance attention. Based on the findings, the paper proposed a five-lever Modern Computing AI Integration Framework, covering data, infrastructure, models, applications, and governance. Ultimately, the study concluded that the most pressing question in modern computer science was not whether to embrace artificial intelligence, but whether its rise and accompanying expansion and investment would serve the needs of reliability, safety, and energy, security, and human-centered governance, and whether it would overcome these challenges.