AI Technology Trends Radar

your strategic guide to the evolving AI landscape

Artificial Intelligence (AI) is driving transformative innovation, leading industries to redefine the levels of efficiency previously impossible to achieve. Rapid advancements in the field are enabling precise navigation of complex real-world challenges and intuitive ways of customer interactions. As AI research and applications expand, they unlock vast business opportunities, making AI a key catalyst for future growth.

AI Technology Trends Radar - An Interactive View

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Explore and collaborate with our AI Tech Trends Radar! This interactive visualization showcases 31 AI Technology Trends.
Click on any trend to discover:
• Adoption phase
• Market potential
• Horizon classification
• Relationships with other trends

For example, selecting Generative AI reveals it belongs to Horizon 1 , is in the Improving adoption phase, and has Very high market potential. It also connects with 10 other trends, aiding its adoption.

Promising AI Technology Trends

Agentic AI

Agnetic AI

Agentic AI effectively retrieves and coordinates information from various sources, where expertise is spatially and temporally distributed. This significantly boosts overall system performance, making it a crucial R&D area in modern AI.

Zero Trust

AI enhances zero trust by continuously monitoring, analyzing behavior, detecting anomalies, and automating responses to potential security threats.

Explainable AI

Explainable AI enables auditing and testing of AI systems by explaining their decision-making processes, which helps identify and correct errors and biases. This enhances transparency and interpretability of AI while fostering trust and confidence.

GraphRAG

GraphRAG delivers hierarchical summaries by identifying interconnected nodes, offering insights into themes and topics without predefined questions. It serves as an invaluable asset for data-driven enterprises, automating the generation of knowledge graphs.

Computer Vision

Computer Vision enables machines to interpret and understand visual information from the world. Recent algorithm advancements are redefining image processing, offering enhanced accuracy, adaptability, and scalability.

Edge AI

Edge AI processes data locally at the network edge, reducing latency and bandwidth usage while enhancing real-time decision-making. It improves security by minimizing data transfer to centralized servers and integrates multiple AI models on the scale.

Self-Adaptive Hyper Personalization

Self-Adaptive Hyper-Personalization

The technology uses real-time data to learn about user behaviours and trends that businesses can use to refine strategies, optimize offerings, and innovate. Proactively addressing user preferences and pain points can help reduce customer churn.

Self-Adaptive Security

Due to APTs and zero-day malware attacks, self-adaptive security is in high demand. However, integration with existing IT infrastructure is crucial as it enhances threat detection, incident response, and access controls.

Leaders Speak

LTIMindtree is building an enterprise-grade data and digital foundation, which has proved essential for embedding automation and AI in the client's platform solutions. This helps the clients get better internal and external stakeholder experiences and insights from their business processes while minimizing risk and optimizing costs.

Krishnan Iyer

Chief Growth Officer, LTIMindtree

AI is not merely automating existing processes; it is also fostering intuitive ways of product interactions with the development of agentic systems that learn from their environment and make decisions with minimal human intervention.

Indranil Mitra

Vice President, LTIMindtree Research

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