Skip to main content
Enterprise AI Analysis: Generative artificial intelligence for sustainable development: predictive trend analysis in key sectors using natural language processing

Enterprise AI Analysis

Generative artificial intelligence for sustainable development: predictive trend analysis in key sectors using natural language processing

Generative Artificial Intelligence (GenAI) has revolutionized multiple industries by improving efficiency and promoting innovation in fields such as business, education, healthcare, and cybersecurity. This study evaluates the transformative impact of GenAI on advancing the United Nations' Sustainable Development Goals (SDGs) by analyzing research trends and applications. In this research, authors utilized Latent Dirichlet Allocation (LDA), a Natural Language Processing (NLP) technique. The work delineates emergent themes and sector-specific progressions in GenAI research. The dataset consists of 2162 research articles published from 2020 to 2025, obtained from the Scopus database. The abstracts of these publications provide the foundation for analysis, facilitating a thorough examination of literature. The authors provided 10 topics, which are recent trends that future researchers can explore. The results indicate GenAI's capability in processing automation, creative enhancement, and innovation promotion while addressing ethical concerns such as prejudice, privacy, and social effects. The study indicates potential directions for ethical technology adoption by analyzing trends in GenAI applications. This work highlights the essential requirement for interdisciplinary methods and ethical frameworks to optimize GenAI's contributions to innovation while assuring alignment with sustainable and equitable development goals.

Executive Impact & Key Metrics

Our analysis reveals critical shifts and opportunities in GenAI development and adoption.

0 Economic Growth Potential (by 2030)
0 Marketing Automation by 2025
0 Research Articles Analyzed (2020-2025)
0 Peak Research Growth in 2024
0 LDA Model Coherence Score

Deep Analysis & Enterprise Applications

Select a topic to dive deeper, then explore the specific findings from the research, rebuilt as interactive, enterprise-focused modules.

Image Augmentation
Social Media & Ethics
Art & Content Gen
GenAI in Healthcare
Education Ethics
Teaching & Learning
Business Innovation
LLM Apps (R&D)
SW Dev
Cybersecurity

Deep Learning for Image Augmentation

This area enhances medical imaging for better diagnostics, contributing to SDG 3 (Good Health and Well-Being). It also supports environmental monitoring through satellite imagery, aligning with SDG 15 (Life on Land).

Impact of Gen AI in Social Media Content Creation and Ethical Considerations

GenAI in social media promotes transparency and combats misinformation, supporting SDG 16 (Peace, Justice, and Strong Institutions). It democratizes content creation for marginalized communities, addressing SDG 10 (Reduced Inequalities).

Innovative Methods in Art and Content Generation

This topic enhances educational content, aligning with SDG 4 (Quality Education), and fosters economic growth in creative industries, contributing to SDG 8 (Decent Work and Economic Growth).

GenAI in Healthcare

GenAI supports personalized medicine and resource optimization, directly impacting SDG 3 (Good Health and Well-Being). It also advances medical innovations, aligning with SDG 9 (Industry, Innovation, and Infrastructure).

Ethical Integration of Content Development in Educational Landscape

Ensuring access to ethical and personalized educational tools aligns with SDG 4 (Quality Education). This is achieved through stakeholder collaborations, supporting SDG 17 (Partnerships for the Goals).

Impact of Gen AI on Teaching and Learning Practices

GenAI provides adaptive learning tools, contributing to SDG 4 (Quality Education). It also helps reduce educational disparities in underserved communities, addressing SDG 10 (Reduced Inequalities).

Impact of Gen AI on Business Innovation

GenAI boosts entrepreneurship and operational efficiency, supporting SDG 8 (Decent Work and Economic Growth). It fosters sustainable industrial innovation, aligning with SDG 9 (Industry, Innovation, and Infrastructure).

Future of LLM Applications in Research and Engineering

LLMs accelerate innovation in engineering, contributing to SDG 9 (Industry, Innovation, and Infrastructure). They also promote collaborative research globally, supporting SDG 17 (Partnerships for the Goals).

Gen AI in Programming and Software Development

GenAI improves productivity in software development, aligning with SDG 8 (Decent Work and Economic Growth). It optimizes resource usage for sustainable outcomes, supporting SDG 12 (Responsible Consumption and Production).

Cybersecurity Threat Detection Using Gen AI

GenAI strengthens digital security and protects critical infrastructure, contributing to SDG 16 (Peace, Justice, and Strong Institutions) and SDG 9 (Industry, Innovation, and Infrastructure).

Enterprise Process Flow: Research Methodology

Scopus Database
String Formulation
Corpus Collection
Preprocessing
LDA Model Implementation
0 Total Articles Published in 2024

LDA vs. Other Topic Models

Feature Benefits
LDA (Latent Dirichlet Allocation)
  • Superior interpretability
  • Scalability and computational efficiency
  • Captures semantic relationships
  • Probabilistic approach
NMF/Deep Learning Models
  • Higher accuracy (sometimes)
  • Less interpretable
  • Requires substantial compute resources
  • Difficulty capturing semantic details naturally

GenAI's Impact on Healthcare Diagnostics

Generative AI significantly enhances diagnostic precision and personalized treatment in healthcare. By analyzing vast medical datasets, LLMs help automate routine tasks like medical documentation and generate tailored treatment plans based on patient histories and genomic information, leading to better patient outcomes and innovation in preventive care.

Calculate Your Potential ROI with GenAI

Estimate the efficiency gains and cost savings GenAI can bring to your operations.

Estimated Annual Savings $0
Annual Hours Reclaimed 0

GenAI Implementation Roadmap

A structured approach to integrating Generative AI into your enterprise.

Phase 1: Assessment & Strategy

Identify key business areas, data readiness, and define specific GenAI goals aligned with your strategic objectives.

Phase 2: Pilot & Proof of Concept

Develop and test initial GenAI solutions in a controlled environment to validate effectiveness and gather early feedback.

Phase 3: Integration & Scaling

Integrate validated GenAI solutions into existing workflows and expand their application across relevant departments and processes.

Phase 4: Monitoring & Optimization

Continuously monitor GenAI performance, refine models, and adapt to new data and evolving business needs for sustained impact.

Ready to Transform Your Enterprise with GenAI?

Book a personalized consultation to explore how Generative AI can drive innovation and efficiency in your organization.

Ready to Get Started?

Book Your Free Consultation.

Let's Discuss Your AI Strategy!

Lets Discuss Your Needs


AI Consultation Booking