The Age of Intelligent Agents: Reshaping Productivity and Redefining Human Value

In the new paradigm driven by intelligent agents, productivity is no longer a simple linear sum of human effort or the output of individual agents. Instead, it should be seen as a combination of “system-level effectiveness” and “human–AI collaborative output.” The core idea is that productivity should measure how well the overall system—designed and supervised by humans and operating in collaboration with intelligent agents—achieves its broader goals. We infer that this includes the agent collective’s task completion rate, resource utilization efficiency, and ability to solve complex problems. Metrics should include the system’s (humans and agents) “goal attainment rate”—its success in completing complex projects or achieving business growth targets within a defined timeframe—and its “end-to-end efficiency” in optimizing workflow cycle time, costs, and resource consumption, rather than focusing on any single stage.

In addition, the “quality and speed of decision-making” demonstrated by intelligent agent systems will become a key dimension for measuring productivity, evaluating the accuracy and timeliness of agent-assisted or autonomous decisions, as well as their positive impact on final outcomes. Meanwhile, the “innovation output rate” measures the quantity and quality of the system’s breakthrough contributions to the creation of products, services, processes, or knowledge. We expect these metrics to enable organizations to assess more comprehensively the deep transformative benefits of agent technology, moving fundamentally beyond traditional measures based on the number of tasks completed by individuals and capturing the new meaning of productivity in the age of collaborative intelligence.

As intelligent agent systems become increasingly autonomous, human productivity is no longer measured by the volume of repetitive work performed. Instead, it centers on the ability to guide, optimize, correct, and empower these systems. “Agent orchestration and management effectiveness” measures how efficiently and effectively people design, deploy, and monitor groups of agents—for example, how well tasks are assigned and how promptly issues are resolved. “The quality of strategy and goal setting” assesses how clear and forward-looking the goals and strategies people establish for agent systems are, and how effectively they drive business growth. This reflects the distinctive value humans bring as architects of intelligent systems.

We infer that performance in “risk identification and ethical governance” will also become an important dimension for measuring human productivity, ensuring that AI agent behavior complies with ethical standards and laws and regulations while effectively mitigating potential risks. Finally, “human–AI collaboration efficiency and satisfaction” will assess how smoothly and efficiently people and AI agents work together, as well as how satisfied people are with the assistance they receive. These higher-order contributions highlight the irreplaceable role of humans in managing complex systems, strategic planning, and value-driven decision-making, ensuring that the development and application of AI agent technologies always serve human well-being.

As AI agents take on more and more execution-focused tasks, human value is shifting away from physical labor and repetitive intellectual work toward areas that agents struggle to replicate or that require distinctly human qualities. We believe humans will become “guardians of ethics and values,” providing AI systems with their ultimate moral compass. Agents excel at execution and optimization, but lack the broader vision to transcend current data and rules. Humans will therefore focus on shaping strategy and vision, identifying new growth opportunities and opening up uncharted territory. This shift in core value suggests that humans will move from being executors to serving as guides at a higher level.

For undefined problems that are highly ambiguous, lack historical data, and require knowledge to be integrated across disciplines, human intuition, inductive reasoning, and divergent thinking remain essential, making people the explorers of complex problems and unknown territory. Although AI agents can generate new content, truly disruptive ideas, artistic expression, and scientific breakthroughs often arise from human inspiration, emotion, and deep insight, making people the source of innovation and creativity. Together, these areas form an entirely new domain of irreplaceable human value in the age of automation.

In fields such as customer service, team management, public relations, education, and healthcare, human empathy, emotional intelligence, and the ability to build trusting relationships are core strengths that intelligent agents cannot replace, making people the “center of empathy and interpersonal interaction.” As intelligent agent technology evolves rapidly, people will need to keep learning new skills, adapt to new paradigms, and lead the design and improvement of how intelligent agents learn. They will therefore play the role of “leaders in learning and adaptation.” Together, these abilities form the soft skills and leadership that will make people indispensable in the future.

We believe that as intelligent agents become more efficient at carrying out tasks, human value will lie in the “advancement of wisdom”—a shift from “executors” to “intelligence architects” who focus on building, optimizing, and overseeing agent ecosystems. “Deepening connections” will also become a core human contribution: serving as a bridge between technology and society, between different agent systems, and between people through deeper emotional bonds. We hope this transformation will give people more time and energy to pursue personal growth, contribute to society, and find spiritual fulfillment—redefining the meaning of work and the purpose of life, and enabling a higher form of human flourishing.