Generative AI-Centric Technologies: Get Gartner® Report

February 13, 2025
By Aaron Linskens

3 minute read time

Artificial intelligence (AI) continues to revolutionize how businesses operate, with generative AI (GenAI) technologies taking center stage as critical enablers for innovation.

Over the coming years, advancements in domain-specific and multimodal large language models (LLMs) and agentic AI will push the boundaries of automation, decision-making, and human-AI collaboration.

Organizations that invest in these transformative GenAI-centric technologies can achieve greater adaptability, operational efficiency, and industry-specific problem-solving capabilities.

The Technologies Driving the Next Wave of GenAI Innovation

Adopting generative AI-centric technologies will enable businesses to develop tailored solutions, streamline complex workflows, and unlock unprecedented opportunities across industries.

Domain-Specific Large Language Models: Industry-Tailored AI

Domain-specific LLMs address the unique challenges and requirements of specific industries, from healthcare and finance to manufacturing and retail.

• Why it matters: General-purpose models often lack the precision needed for specialized tasks. Domain-specific LLMs close this gap, delivering more accurate and relevant solutions.

• Business impact: This enhances automation, improves efficiency in decision-making, and empowers businesses to solve industry-specific problems.

• Next steps: Collaborate with AI providers to develop or deploy domain-specific models tailored to your organization's needs.

Multimodal GenAI: Enhanced Intelligence Through Diverse Data

Multimodal GenAI processes and integrates multiple types of data, such as text, images, and video, to create richer and more accurate insights.

• Why it matters: Businesses operate in complex environments with diverse data. Multimodal GenAI enables better understanding and predictions across contexts.

• Business impact: This supports advancements in areas such as computer vision, natural language processing (NLP), and predictive analytics.

• Next steps: Leverage multimodal models to analyze diverse data types and enhance cross-functional AI applications.

Agentic AI: Autonomous and Intelligent Systems

Agentic AI represents the next frontier of generative AI, characterized by its ability to learn autonomously, act independently, and make decisions in complex environments.

• Why it matters: Agentic AI can provide the agility and autonomy required to respond to emerging challenges and opportunities.

• Business impact: This empowers industries with autonomous systems for logistics, customer service, and decision-making.

• Next steps: Invest in agentic AI technologies to automate routine tasks and enable scalable, self-sufficient systems.

High-Quality Data: The Foundation for GenAI Success

Generative AI systems need high-quality data for reliable, unbiased results. Advances in synthetic data and simulation are transforming AI training, reducing reliance on real data, improving privacy and reducing bias.

• Why it matters: Poor data quality can harm GenAI efforts, causing inefficiencies, inaccuracies, and ethical risks. Synthetic data offers scalability while ensuring security and integrity.

• Business impact: This enhances model accuracy, reduces training costs, and ensures data privacy compliance.

• Next steps: Prioritize investments in synthetic data generation and intelligent simulation tools to improve the reliability and robustness of AI models.

Lead the Next AI revolution With Smarter Investments

To stay competitive, organizations must harness the power of GenAI-centric technologies to solve industry-specific challenges, improve decision-making, and drive operational efficiency.

By focusing on domain-specific LLMs, multimodal AI, agentic AI, and high-quality data, businesses can unlock the full potential of generative AI while ensuring scalability, security, and ethical responsibility.

Explore how these technologies can transform your business. Download the full Emerging Tech Impact Radar: Artificial Intelligence research report from Gartner to learn more.

Gartner, Emerging Tech Impact Radar: Artificial Intelligence, Annette Zimmermann, Danielle Casey, et al, 5 December 2024

Written by Aaron Linskens

Aaron is a technical writer at Sonatype. He works at a crossroads of technical writing, developer advocacy, and information design. He aims to get developers and non-technical collaborators to work better together in solving problems and building software.