← Trend Radar·AI/ML·Agentic AI
AI/ML↑ Fastest growing · top 10%

Agentic AI

AI systems that plan, use tools, and execute multi-step tasks autonomously — moving from chatbots to digital workers that act in the world.

Innovators
Early Adopters
Early Majority
▲ Late Majority
Saturation
Papers Analyzed
25,656
research papers
Signal Clusters
11
research threads
Primary Driver
Tech
strongest force
Paper Coverage
2023–2026
publication years
Intelligence Brief

This research helps businesses build smarter AI that reasons like humans, making them better at understanding complex data and collaborating for improved decision making.

Late Majority

This is becoming standard practice. Most relevant organizations have adopted or are planning to. Innovation focus shifts to cost reduction and integration.

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Research Signals · 11 clusters detected

Late Majority● TechTracked since Mar 2026·3,552 papers·+22.2% MoM
S01

Agent Memory Architectures

? What if our digital assistants could truly learn from every past interaction, remembering what we like and dislike so deeply they anticipate our needs before we even articulate them, fundamentally changing how we shop, work, and live

This research cluster, "Agent Memory Architectures," explores how artificial intelligence agents can develop and utilize memory to learn from past experiences and adapt their behavior over time. The sheer volume of 3552 papers published between 2023 and 2026 indicates a rapidly maturing field, moving beyond early exploration into widespread adoption, with over 77% of its projected potential already reached. This innovation is crucial for unlocking more sophisticated AI capabilities, enabling agents to perform complex, multi-step tasks with a sustained understanding of context, thereby solving the limitation of stateless AI.

Adoption Curve

Unreliable projection · missed held-back months by 88%
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Deep Analysis

Within the next year, expect to see more sophisticated customer service bots and personal assistants that can recall specific details from previous interactions, leading to more personalized and efficient user experiences. Over the next 2-3 years, as the field reaches its peak activity, AI agents will become integral to complex workflows in fields like software development and scientific research, with initial adoption by tech-forward companies and research institutions. The primary remaining barrier will be ensuring these agents' memories are reliable, secure, and ethically managed, preventing unintended consequences from past learning.

PEST Implications

Political

Governments might need new regulations for AI agents that remember and learn from past interactions, impacting how they are deployed in public services.

Economic

Businesses can develop more sophisticated and personalized customer service bots that recall previous conversations, leading to improved customer loyalty and sales.

Social

The ability of AI agents to learn and adapt could change how people interact with technology, potentially leading to more natural and helpful digital assistants in daily life.

Tech

This research pushes the boundaries of artificial intelligence, enabling the creation of smarter, more adaptable digital tools that can perform complex tasks with greater autonomy.

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Late Majority● TechTracked since Apr 2026·1,205 papers·+20.8% MoM
S02

Agent Memory Retrieval

? What if every customer interaction, every past decision, and every piece of feedback your company has ever received could be instantly recalled and synthesized by an AI to personalize every future engagement and predict what your customers will want next

The research trend of Agent Memory Retrieval is rapidly maturing, addressing the critical need for AI agents to remember and learn from past interactions. With over 1200 papers published between 2023 and 2026, this field is moving beyond basic storage to develop sophisticated systems that allow AI to maintain context, personalize responses, and improve performance over time, much like human memory. This capability is essential for AI to evolve from simple tools into truly intelligent, long-term partners.

Adoption Curve

Unreliable projection · missed held-back months by 47%
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Deep Analysis

The adoption of Agent Memory Retrieval is already in its late majority phase, with peak research activity anticipated in approximately three years. In the short term, expect more personalized digital assistants and customer service agents. Within two to three years, as research activity peaks, AI agents will become more adept at complex, long-horizon tasks across industries like software engineering, scientific discovery, and advanced recommendation systems, overcoming current barriers of context bloat and inconsistent recall.

PEST Implications

Political

Governments may need to consider new regulations for AI agents that store and access personal information, impacting data privacy laws.

Economic

Businesses can develop more personalized customer experiences and efficient internal operations by using AI agents that remember past interactions.

Social

The ability of AI to recall and learn from past events could lead to more helpful and consistent digital assistants in our daily lives.

Tech

This research enables AI agents to learn and adapt over time, making them more capable of complex tasks and independent decision-making.

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Late Majority● TechSettledTracked since Mar 2026·1,226 papers·-2.7% MoM
S03

Software Engineering Agents

? What if your company's entire software development team could be replaced by a handful of AI "agents" that write, test, and fix code faster and cheaper than any human team ever could

Software engineering agents, powered by advanced AI, are becoming active contributors to code development, moving beyond simple assistance to autonomously writing, testing, and even fixing code. The sheer volume of 1226 research papers published between 2023 and 2026 demonstrates significant momentum, indicating a shift towards solving complex software development challenges and unlocking new levels of productivity. These agents are transforming how software is built by automating intricate coding tasks, improving efficiency, and accelerating innovation.

Adoption Curve

Unreliable projection · missed held-back months by 37%
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Deep Analysis

Within the next year, expect these agents to become more integrated into existing development tools, with early adopters in large tech companies focusing on automating repetitive coding tasks and bug fixes. Over the next 2-3 years, as peak activity approaches, these agents will tackle more complex features and entire project modules, with industries like gaming and financial services leading adoption due to their high demand for rapid development and complex codebases. The primary remaining barriers include ensuring the security and reliability of agent generated code and overcoming the challenge of agents understanding nuanced architectural designs.

PEST Implications

Political

Governments may need to consider new regulations regarding the ethical use and accountability of AI in software development.

Economic

Businesses can expect increased efficiency and reduced costs as AI agents automate parts of the software creation process.

Social

The way people work in tech will change, potentially requiring new skills and shifting job roles as AI becomes a collaborator.

Tech

Companies can build more sophisticated software faster, leading to quicker innovation and new digital products and services.

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Late Majority● TechTracked since Mar 2026·1,220 papers·+2.1% MoM
S04

Agent Security Vulnerabilities

? What if the AI assistants you rely on to manage your business could be secretly instructed to steal your confidential data or sabotage your operations without you ever knowing

This research explores how AI agents can be tricked or attacked, potentially leading to data leaks or system failures, which is crucial for protecting business operations and sensitive information.

Adoption Curve

Floor, not a measurement · monthly rate still rising — no ceiling estimable, so this is a lower bound
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PEST Implications

Political

Governments may need to develop new regulations to ensure the safe and ethical use of AI agents, protecting citizens from potential misuse.

Economic

Businesses that rely on AI agents could face significant financial losses if these systems are compromised, impacting customer trust and operational continuity.

Social

The public's confidence in AI technologies could erode if security vulnerabilities lead to data breaches or harmful actions by intelligent agents.

Tech

Developers and companies must invest heavily in advanced security measures to prevent malicious actors from exploiting weaknesses in AI agent systems.

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Late Majority● TechTracked since Apr 2026·2,696 papers·+13.0% MoM
S05

Agentic Learning Paradigms

? What if your employees could learn new skills and solve complex problems instantly, just by asking the right questions and letting intelligent assistants handle the heavy lifting?

This research helps AI agents learn and improve faster by teaching them to think ahead and use tools effectively, leading to smarter and more capable AI for business.

Adoption Curve

Floor, not a measurement · monthly rate flat, no peak yet — no ceiling estimable, so this is a lower bound
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PEST Implications

Political

Governments may need new rules to manage AI agents that can learn and adapt independently, impacting how decisions are made and accountability is assigned.

Economic

Businesses can automate complex tasks and create new services by using AI agents that learn from experience, potentially boosting efficiency and creating new markets.

Social

The way people interact with technology could change dramatically as AI agents become more capable of understanding and responding to human needs and goals.

Tech

This research is accelerating the development of smarter AI systems that can solve problems and perform tasks with less direct human guidance, opening up new possibilities for innovation.

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Late Majority● TechTracked since Apr 2026·2,110 papers·+12.3% MoM
S06

Agentic Tool Benchmarks

? What if your company's most complex workflows could be reliably managed by AI agents, freeing up your human workforce for more creative and strategic endeavors

This research helps businesses measure how well AI agents can perform complex real-world tasks, ensuring they are reliable and effective tools.

Adoption Curve

Floor, not a measurement · monthly rate flat, no peak yet — no ceiling estimable, so this is a lower bound
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PEST Implications

Political

Governments may need new rules to ensure AI agents using tools are safe and fair for citizens.

Economic

Businesses can create more efficient and automated customer service or internal operations by using AI that can interact with software.

Social

People might interact with AI assistants that can perform complex tasks, like booking travel or managing finances, more seamlessly in their daily lives.

Tech

This research is rapidly advancing how AI can understand and operate digital tools, leading to smarter and more capable AI systems in the near future.

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Late Majority● TechSettledTracked since Mar 2026·3,092 papers·-1.4% MoM
S07

Agent System Design

? What if your company's entire operations could run themselves, making decisions faster and better than any human team, freeing everyone for more creative and strategic work?

Agent systems use smart AI to automate complex tasks, improving efficiency and decision making in industries like manufacturing and finance.

Adoption Curve

Floor, not a measurement · monthly rate flat, no peak yet — no ceiling estimable, so this is a lower bound
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PEST Implications

Political

Governments may need to develop new regulations to address the ethical and legal responsibilities of autonomous AI agents operating in society.

Economic

Businesses can leverage these intelligent agents to automate complex tasks, potentially leading to significant cost savings and new service offerings.

Social

The development of these agents could transform how people interact with technology and each other, impacting everything from education to entertainment.

Tech

This research is accelerating the creation of smarter, more adaptable AI systems that can work together to solve problems in novel ways.

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Early Adopters● TechTracked since Mar 2026·1,860 papers·+23.8% MoM
S08

Distributed Agent Control

? What if you could have an entire fleet of autonomous delivery drones or warehouse robots seamlessly coordinating their every move, even in unpredictable environments, to get goods to customers faster and cheaper than ever before

This research helps coordinate many independent robots or systems to work together efficiently, even with communication delays or uncertainty, for tasks like delivery or exploration.

Adoption Curve

Floor, not a measurement · monthly rate flat, no peak yet — no ceiling estimable, so this is a lower bound
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PEST Implications

Political

Governments might use these advanced systems to coordinate emergency response teams more effectively across different jurisdictions during natural disasters.

Economic

Businesses can improve efficiency and cut costs by using these systems to manage fleets of delivery vehicles or automated factory robots.

Social

Communities could benefit from smarter traffic management systems that reduce congestion and travel times for everyone.

Tech

This research is paving the way for more sophisticated AI that can manage complex tasks with many independent but coordinated parts, like autonomous drone swarms or smart grids.

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Early Majority● TechTracked since Mar 2026·2,464 papers·+18.1% MoM
S09

Social Intelligence Agents

? What if the AI assistants we rely on daily develop their own social dynamics, potentially influencing our decisions or even forming alliances among themselves in ways we can't predict or control

This research explores how AI agents interact socially, helping businesses understand and build more effective, engaging, and trustworthy AI systems for customers and employees.

Adoption Curve

Floor, not a measurement · monthly rate flat, no peak yet — no ceiling estimable, so this is a lower bound
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PEST Implications

Political

Governments may need to develop new regulations to govern the interactions and responsibilities of increasingly sophisticated AI agents in public life.

Economic

Businesses can leverage AI agents to automate complex negotiations and analyze market dynamics, potentially leading to more efficient transactions and new revenue streams.

Social

The rise of AI agents capable of understanding human intentions could transform how we interact with technology, affecting everything from customer service to personal assistance.

Tech

This research is pushing the boundaries of AI, enabling agents to communicate secretly, manage financial risks, and even exhibit human-like social reasoning.

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Late Majority● TechTracked since Apr 2026·4,586 papers·-27.9% MoM
S10

Agentic Reasoning Systems

? What if your company's AI could not only understand complex customer needs but also proactively suggest innovative solutions and negotiate deals like a seasoned salesperson, transforming every interaction into a revenue opportunity?

This research helps businesses build smarter AI that reasons like humans, making them better at understanding complex data and collaborating for improved decision making.

Adoption Curve

Moderate confidence · within 17% on held-back months
Peak ~2.3yrNow100%50%0%Adoption-2yrToday+2yr+4yrModel fit 100%InnovatorsEarlyEarlyLateSaturation
Late Majority: This is becoming standard practice
75.2% of projected market reached
Peak expected in ~2.3 years

The field is maturing and becoming standard practice. Research focus is shifting from invention to optimisation and deployment at scale.

Hover the chart to explore adoption over time

Phase Position

RISINGDOMINANTEMERGINGMATUREAdoption →Velocity →0%100%75%v18
Late Majority· widely adopted, slowing down
75.2% adoption · velocity 18th percentile

PEST Implications

Political

Governments may need new regulations to manage how these intelligent agents interact and make decisions in public systems.

Economic

Businesses can automate complex tasks, leading to increased efficiency and potentially new service offerings that were previously impossible.

Social

These agents could change how we work, learn, and even receive healthcare by providing personalized assistance and analysis.

Tech

The development of these agentic reasoning systems represents a significant leap forward in artificial intelligence, enabling machines to solve problems more independently.

Deeper Signals

Maturity, From the Writing Itself

Reads as Early Adopters based on how these papers are written, not the Late Majority stage the paper-volume model above shows. The language frequently uses terms like "propose," "explore," "towards," and "framework," indicating a focus on developing and testing new approaches rather than widespread production deployment.

Early Majority● TechTracked since Mar 2026·1,645 papers·+45.7% MoM
S11

Multi-Agent Reinforcement Learning

? What if your entire supply chain could spontaneously reconfigure itself to avoid disruptions, learning and adapting in real-time like a single, intelligent organism?

This research helps businesses coordinate multiple autonomous systems, like robots or vehicles, to work together effectively and achieve complex goals.

Adoption Curve

Validated projection · within 8% on held-back months
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PEST Implications

Political

Governments may face new challenges in regulating autonomous systems that operate collaboratively, impacting national security and international relations.

Economic

Businesses can expect to see new efficiencies and cost savings as AI agents learn to optimize complex operations in areas like supply chains and energy grids.

Social

The public might experience more responsive and intelligent automated services, from smarter traffic management to personalized digital assistants.

Tech

This research is rapidly advancing the ability of multiple AI systems to work together intelligently, creating more sophisticated and capable automated solutions.

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Research Momentum

+99% year-over-year(2025 → 2026, sample papers)
20232605202475112025149782026149780Papers

Based on representative paper sample per cluster · not a complete count

Stage Breakdown

Share of papers per adoption stage, weighted by cluster size.

Early Adopters7%
Early Majority16%
Late Majority77%

Research insights powered by Google Gemini

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