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AI has penetrated the core of production, and the development direction from the user end is already very clear. Intelligent agents will fully permeate the industry. In the long run, intelligent agents will evolve into a complex system similar to an "AI operating system." Users only need to issue tasks, and the system can automatically decompose the task and coordinate multiple intelligent agents to complete it together. It is evident that the technical foundation is climbing, and the application layer's explosion is inevitable. The next few years will be the golden period for Agentic AI to take root.

WE CAN SEE

We can see

·Agentic AI greatly reduces the barriers to building applications, making everyone a builder;

·Ontology becomes a map for AI to understand companies, combined with agent orchestration and decision-making processes;

·GUI Agents in human-machine collaboration and digital automation will redefine the future traffic entry points;

·AIGC penetrates most intelligent scenarios, and AI capabilities require public infrastructure products to support them, and connect with the cloud-based AI-driven digital world to generate synergistic effects......

01

The industry penetration of Agentic AI is astonishing

In 2026, new generation intelligent agent technologies represented by OpenClaw, Agentic AI, Harness Agent, and Palantir are sweeping through the underlying logic of technological research and development at an unprecedented speed, profoundly influencing the path choices for enterprise digitalization. If years ago it was a "battle of thousands of models," then the main battlefield in 2026 has fully shifted: AI is moving from the "passive response" of large models to the key transition of "active decision-making and execution" by intelligent agents. Means:The transformation of technological research and enterprise digitalization driven by the new generation of intelligent agent technology is here.

OpenClaw's value lies not only in technological breakthroughs but also in revealing the core bottleneck for the large-scale deployment of AI agents. OpenClaw uses more than 30 times the tokens per task compared to traditional Q&A, forming a stable "utility-like" revenue model. Harness Engineering (Control Engineering). Like putting a reins on a wild horse, it builds a control system including the runtime environment, constraints, and feedback loops, ensuring AI's power is released along the right track. The rise of Harness Engineering marks a new stage in AI engineering, evolving from "prompt engineering" and "context engineering" to "control engineering."

In the field of enterprise-level intelligent agent platforms, Palantir represents a different technical path. Palantir Foundry platform seamlessly connects heterogeneous data sources such as databases, APIs, and IoT sensors through its unique three-layer architecture (data integration layer, ontology layer, and application layer), while maintaining complete data lineage tracking.

The industry penetration speed of Agentic AI is also astonishing. Agents have upgraded from "auxiliary coding tools" to "digital colleagues" capable of participating in requirements analysis, solution design, code modification, testing, and even the entire R&D process. Traditional "large R&D organizations" are being replaced by "small teams + AI agents." According to Gartner, this model is expected to become mainstream by 2030.

In the future, the underlying driving force of the "super organization" form will shift from human-to-human division of labor and collaboration to human-and-intelligent-agent hybrid teams. For enterprises, the greatest value of self-evolving intelligent agents lies in their role as the core logic of digital construction, upgrading from "introducing a tool to improve efficiency" to "building an intelligent system that continuously evolves with business to reshape productivity."

For enterprise digitalization, these new technologies carry profound strategic significance. Intelligent agents will drive the comprehensive reconstruction of internet infrastructure. Browsers, search engines, and account systems all need to transform into "service agents." Companies that successfully embrace Agentic AI will have the opportunity to establish irreplaceable competitive barriers in this paradigm shift from "tools" to "digital agents."

02

General intelligence will become the most basic public infrastructure service for future society

In 2026, AGI reached a historical turning point. Looking back at the standard event of the Transformer paper in 2017, the fierce competition and development of large models allowed society to use AGI as social production materials for the first time, enabling large-scale, low-cost, real-time access across various industries. This truly made large models the most important public infrastructure service. This verifies that after the early accumulation of any technological change, the hallmark is when it becomes a social basic public service, and its value is fully revealed.

At the beginning of the year, Token Economics showed us that this general intelligence can be measured by the unit cost of tokens and the output of intelligence. This means that tokens can be measured like electricity consumption or water usage. As a result, at the GDC conference held by NVIDIA in 2026, Huang Renxun first said, "Our future goal is to become a Token Factory, we are just producing tokens." This positions computing power and basic intelligence as the most standardized public services provided to the industry. It is evident that the consensus among giants has shifted from pure technological arms race to the large-scale supply of underlying computing power. This equals establishing a "cost per kilowatt-hour" benchmark for AI services, making abstract capabilities quantifiable and tradable.

Sam Altman also proposed that OpenAI is also a Token company, so tokens have become a universal measurement standard, representing society's ability to call upon intelligence. Due to the establishment of Token Economics, the industry widely uses general intelligence as a social infrastructure.

With this comes the second phase of AGI development, massive intelligent applications. At the beginning of the year, the lobster, various agents were constantly being launched, and the era of true intelligent agent explosion has arrived. Perhaps we will face dozens of thousands of intelligent agents. How to choose? How to determine which agent is more suitable? How to entrust an important task to an agent that doesn't make mistakes? This may be the core issue that needs to be resolved during the intelligent agent development phase.

Future, all internet services will be agentized, thus giving birth to massive innovation. AI is moving from dialogue to completing complex tasks. In the context of intelligent agents, there will be very complex collaboration, and intelligent agents will need to be able to call each other. During this process, it will further evolve into an AIOS, an AI operating system, which may require 5 to 10 or even more intelligent agents to work together to complete. Therefore, it is not a simple choice, not choosing A or B in a marketplace, but trusting an operating system to break down complex tasks and match them with the most suitable agent. This is the super application of intelligent agents (Personal Assistant), personal assistant, allowing ordinary users to choose and trust various intelligent agent services that suit them. This means that AI has officially crossed from a "chat tool" to a "productivity tool," and the focus of future competition will shift from the capability of a single agent to ecosystem-level system collaboration.

The evolution of the intelligent interface into AIOS requires complex collaboration between intelligent agents. These intelligent interactions show us that agents have evolved from the simple matching stage, where we find the right agent through one entrance, to throwing tasks to agents and completing complex agent operations. An AI operating system can automatically decompose and match tasks to the appropriate intelligent agents, indicating that the interaction mode has changed from "people seeking services" to "things seeking services," and the system will take over the complex scheduling work.

03

Prospect: The Impact of New Technologies on Tech Companies

Future Digital Processes

For enterprises implementing digital transformation, 2026 is not only a window of opportunity to introduce agents but also a strategic node to restructure core business processes and systematically convert enterprise knowledge into sustainable evolutionary intelligent assets. Enterprises that first build a "self-evolutionary closed loop" will have the opportunity to establish an irreplaceable competitive barrier in this industry transformation driven by intelligent agents.

Future Self-Evolution

"Self-evolution" will be a leap in the overall intelligent capabilities of the organization, defining a comprehensive transformation across three dimensions: self-evolution of intelligent agents, individual self-evolution, and organizational self-evolution. Unlike the static nature of traditional agents that are "fixed once delivered," self-evolving intelligent agents are designed as dynamic systems that can "validate, close the loop, and evolve infinitely," pushing industrial software from "one-time delivery of finished products" to "living organisms that grow continuously with the enterprise's business."

Future Enterprise Operations

For enterprise operations, optimal algorithm = optimal decision + direct embodiment of highest efficiency. The profound significance of this framework lies in upgrading enterprise operations from "optimizing item by item with people involved" to "defining goals with people and intelligent agents continuously autonomously optimizing." It frees R&D personnel from complex algorithm tuning, allowing them to focus on creative tasks and strategic planning.

Future AI Infrastructure

The essence of enterprise AI infrastructure is no longer expanding computing power scale but systematically reconfiguring enterprise knowledge and intelligence. The construction of enterprise AI infrastructure and intelligent agent technology ecosystems is undergoing a profound paradigm shift, moving from "data-driven" to "knowledge-driven," and from "model-first" to "ontology-first." In this shift, Ontology is gradually moving from academic conceptual research into the core of the industry, becoming the cornerstone supporting the construction of enterprise-level AI infrastructure and intelligent agent technology ecosystems.

Future First-Mover Advantage: Ontology-Driven, Knowledge-Driven, and Agent-Driven

Ontology provides the "semantic geometry" from data to intelligence, enabling AI to truly become the native labor force that understands, remembers, and drives enterprise evolution. In this transformation, enterprises that first complete the infrastructure leap from "data infrastructure" to "ontology-driven, knowledge-driven, agent-driven" will gain a decisive first-mover advantage in the tide of the intelligent economy.

Future R&D Business Value Metrics

Any technological construction detached from business value orientation will fall into the trap of "AI for AI's sake". R&D companies should adhere to the complete process of "goal definition - ontology modeling - agent development - execution loop - value measurement," ensuring that each construction phase can be mapped to quantifiable business value metrics, avoiding meaningless arms races in models and computing power. Starting from the "business value loop," reverse-engineer technology selection and architectural design. Under limited resources, actively integrating into the industry open-source ecosystem and participating in industry ontology standardization will be effective paths to reduce AI infrastructure construction costs and shorten the construction cycle.

Future Cost Management Logic and Governance Paradigm

The new generation of intelligent agent technologies brings not only a surge in efficiency but also a completely new set of cost management logic and governance paradigms. Cost investment has evolved from "hardware procurement" into a full lifecycle systematic project. From model calls to system integration, from continuous maintenance to risk assessment, every link requires strict calculation and control. Governance has upgraded from "security compliance" to a core capability determining whether intelligent agents can truly create value.

For R&D companies, establishing a scientific cost evaluation system and a sound governance framework will allow them to truly move steadily and far in the industrial transformation driven by intelligent agents. In today's rapid development of intelligent agent technology, the answer no longer depends on whether one has the ability to ride "a fiercer horse," but rather on whether one can design the most stable reins for it.

Tenth 2026 CSDI Summit, Shenzhen October 16-18

Explore the Agentic AI Digital Agent World Together

At the time of the Agentic AI era, for tech companies' operations, large model capabilities should focus on creative tasks, strategic planning, and business integration. The technical paradigm of software development and big data technology is moving towards model-driven autonomy. A large number of intelligent software development tools and frameworks have emerged. Data has become the core of intelligent software development. The AI industry has shifted from "model capability-driven" to "computing power organization and efficiency-driven," with a lot of data and massive intelligent scenarios playing a key role in the sustainable development of AI. The demand for intelligent computing resources and the training and deployment of complex models require developers to apply high-performance hardware (such as GPUs, TPUs, etc.) and distributed computing technologies (such as cloud computing, cluster computing, databases, etc.). These technologies are still topics of research and exploration for IT organizations.

To this end, the tenth edition of the 2026 CSDI China Software Development Intelligent Innovation Technology Summit will be held in Shenzhen from October 16 to 18, bringing together more than 100 top innovators from home and abroad to meet the definite long-term trend of "data intelligence integration and decision intelligence," promoting AI toward self-evolution and embracing the frontiers of Agentic AI application exploration practices.

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The Tenth 2026 CSDI is about to open, inviting IT heroes from all walks of life, to lead the way.

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Substantial professional expertise, forward-thinking thinking, and excellent practice provide the industry with a great perspective and outstanding ideas. Upholding the concept of technology for good, we promote the exchange and dissemination of the IT industry. We hope to find like-minded individuals who pursue excellence and talent, and guests with rich experience in the forefront of AI, to join us and work together to explore the future of the knowledge revolution!

Highlights