The Balanced Scorecard (BSC) is a strategic management framework introduced by Kaplan and Norton in 1992 to address the limitations of traditional performance measurement systems. It integrates financial and non-financial performance measures across four perspectives—financial, customer, internal processes, and learning and growth. Over three decades, the BSC has evolved into a comprehensive strategic tool adopted across industries and sectors worldwide. While its adaptability and integrative approach are strengths, criticisms include challenges in implementation, assumed cause–effect relationships, and relevance in decentralized organizations. Future research should investigate cultural adaptation; the incorporation of environmental, social, and governance metrics; and advancements driven by artificial intelligence to maintain ongoing relevance.

This review paper examines how Generative AI (GAI) and Large Language Models (LLMs) can transform smart cities in the Industry 5.0 era. Through selected case studies and portions of the literature, we analyze these technologies’ impact on industrial processes and urban management. The paper targets GAI as an enabler for industrial optimization and predictive maintenance, underlining how domain experts can work with LLMs to improve municipal services and citizen communication, while addressing the practical and ethical challenges in deploying these technologies. We also highlight promising trends, as reflected in real-world case studies ranging from factories to city-wide test-beds and identify pitfalls to avoid. Widespread adoption of GAI still faces challenges that include infrastructure and lack of specialized knowledge as a limitation of proper implementation. While LLMs enable new services for citizens in smart cities, they also expose certain privacy issues, which we aim to investigate in this study. Finally, as a way forward, the paper suggests future research directions covering new ethical AI frameworks and long-term studies on societal impacts. Our paper is a starting point for industrial pioneers and urban developers to navigate the complexity of GAI and LLM integration, balancing the demands of technological innovation on one hand and ethical responsibility on the other.

This entry examines the impact of Enterprise Resource Planning (ERP) systems on business efficiency and productivity. We will delve into how ERP streamlines workflows, improves data accessibility, and ultimately enhances a company's overall operational effectiveness. By understanding these aspects, businesses can gain valuable insights into the potential of ERP to transform their operations and achieve a competitive edge.

Today, Artificial Intelligence (AI) is revolutionizing the industry, helping doctors and healthcare providers deliver better, faster, and more personalized care. This is what we call “smart healthcare”. A review published in MDPI discusses artificial intelligence applications in smart healthcare. Traditionally, healthcare has focused on doctors and specialists. But smart healthcare flips that model by putting the patient at the center. Thanks to AI, smart healthcare uses technology to enhance the entire experience, making it more personalized, accurate, and efficient. AI analyzes vast amounts of health data, helping doctors make faster decisions, from diagnosing diseases to creating tailored treatment plans. AI is transforming healthcare in major ways. It helps with disease prediction and prevention by using patient data to predict and prevent outbreaks and health issues like cancer and COVID-19. Diagnostic imaging benefits from AI, as it analyzes X-rays, CT scans, and MRIs to spot abnormalities that might be missed by the human eye, speeding up diagnoses. AI also helps create personalized treatment plans, especially in cancer care, by tailoring treatment to your unique genetic and health data. Virtual health assistants powered by AI track symptoms, provide health advice, and help manage chronic conditions—all from your phone. Remote patient monitoring through wearables alerts doctors to any health issues in real-time, ensuring quicker care. AI also speeds up drug discovery by predicting the effectiveness of drugs and bringing life-saving medications to market faster. In the operating room, AI-assisted robotic surgery enhances precision and reduces recovery times. NLP for EHRs (Electronic Health Records) helps doctors quickly extract critical information from patient records, improving decision-making. On the mental health front, AI supports behavioral health by detecting issues early through data analysis from wearables and social media, allowing patients to get the help they need faster. AI also assists with clinical trial matching, connecting patients to the right studies and making research more efficient. These AI applications are transforming healthcare, making it smarter, faster, and more personalized than ever before. But there are challenges! Data integration is difficult due to incompatible systems, and managing massive amounts of data requires tools like Hadoop. Real-time decision-making is slowed by cloud delays, which makes edge computing a better solution. AI’s lack of transparency raises trust issues, while security risks threaten patient privacy. Bias, ethical concerns, and EHR integration need to be addressed, and scaling AI for large systems remains tricky. In rural areas, weak internet connectivity limits AI’s potential, requiring offline models. Overcoming these challenges will unlock AI’s full potential in healthcare. AI is the future of healthcare, but addressing these challenges is key to unlocking faster diagnoses, better treatments, and smarter care. 

This Chinese AI startup, DeepSeek, is flipping the script on global tech—and it's coming for OpenAI's crown. What is DeepSeek?DeepSeek is a free AI chatbot that's going head-to-head with OpenAI's ChatGPT. It can answer questions, write essays, and even code. Basically, your new AI best friend. But here's the wild part: while OpenAI's GPT-4 cost over $100 million to develop, DeepSeek's latest model, DeepSeek-R1, was trained for just $6 million! How'd they pull it off?DeepSeek managed to bypass U.S. chip export restrictions by using Nvidia's A100 chips and other cheaper alternatives. The result? A high-performance AI that's also more affordable to run. Who's behind it?DeepSeek was founded in December 2023 by Liang Wenfeng, an entrepreneur with a background in both computer science and finance. He previously ran a hedge fund, High-Flyer, which uses AI for quantitative trading. App store dominationDeepSeek launched in the U.S. and immediately became the TOP 1 free app on the Apple App Store! But it wasn't all smooth sailing—they faced massive cyberattacks and had to limit registrations. Still, their growth is off the charts. Why DeepSeek is making waves?DeepSeek is proving that you don’t need a massive budget or cutting-edge hardware to create groundbreaking AI. This has shaken up the industry. Nvidia's stock dropped, losing billions in market value, as investors begin to question whether expensive chips are really necessary for AI. Controversies & ScrutinyDeepSeek is facing global backlash. Australia has banned the app from government devices over security concerns, while Italy blocked it over data privacy issues. Since DeepSeek stores data on servers in China, there are fears about surveillance and data misuse. ConclusionDeepSeek's rapid rise marks a significant moment in the global AI race. With its low-cost, high-performance AI, the company is challenging U.S. giants like Nvidia and OpenAI. As China pushes for self-reliance, DeepSeek could be the start of a new era in the global AI landscape.