Goldman Sachs Cio: Prepare the EI local residents to form the future of the work

Agentic AI refers to artificial intelligence systems that can perform tasks on behalf of people and can make independent decisions without direct control. These systems can prepare a detailed plan based on context, memory and existing information, and can perform the steps you need to complete a task. Their opportunities to grow are a turn of passive means of active employees.

The agent will produce a very small level roles of AI and the reality is more nuanced in reality. Instead of reducing the importance of early career workers, this sliding is more critical than ever since a simple reason. “Grew up” with generation generation AI, which is already included in the workforce. PACE is more comfortable and equipped to form the future. They are “AI Local”.

At the same time, someone said: “There is no compression algorithm for experience, and the best of practice and voice, the best is 4 years old and still fast. Will it provide experienced control of the question of the question?

It is important to understand how the AI has raised the generation of local residents by the necessary skills and means to be a leader and to determine the future of the work and determine the future of the case. We will determine how we combine our instincts, creativity and adaptation, not a means of aI, but as partners as a means. The upcoming problem is not technological; This is cultural, education and different person.

New EU Paradigm

Here’s the first thing we need to come to terms: This is a new game with new athletes more likely than previous players.

Think of this way: If you don’t want to learn the piano later, you can be enthusiastic and dedicated, but the probability of being a produce is thin. Similarly, think of someone who learns to use a computer better on a computer. Even decades later, their writing, mouse use or navigation of user interfaces often shows late beginnings.

The same dynamic is now opened with AI tools. A generation emerges a division AI for non-local people, adapting to the AI-first or AI-Hybrid workforce can be more difficult than we expect. However, this is the place where the majority of institutional knowledge and experience is located.

Several technological turns have created vacuums of similar knowledge: the application of computers, internet, mobile, cloud technology and others. In any case, the main student for certain roles in the fluency took ten years or more before the deficit. Those who do not require these skills or can not pass the workforce completely out of the entirety roles. What is different now is the speed. The AI shift takes place for decades. In the ability to use AI tools, employees who are incompetent will remain behind and learn to use it to improve their work.

As every major technological turn, a new generation leaders emerge, especially with the AI, reloads the landscape. Consider the cheeses of companies like Devin, Windsurf and scale AI-all AI locals. Can one of them be the next law doors or Michael Dell? Possible. Therefore, as a society, those who assess our responsibility and leaders, this new generation should maximize the potential of this new generation and pay attention to the “great” to our small athletes.

Investing in the AI residents

We need to invest in the young talent that redefines the industry we work. It is difficult to understand the scale, if we accept that the exact contours of this transition is difficult to predict the AI. In a world in which the technology is developed in Sonic, we need to ensure that the pace of managing man’s adaptation. Simply put the best of our best athletes for this new arena, we need to equip this change with the necessary skills to manage and manage.

The ability to demand AI coworkers with the arrival of the agent AI will soon be an initial opportunity. It will require even the smallest employees and personal contributions to master the three basic management skills in the turn, even the smallest staff and individual contributions: explain clearly by explaining a case clearly and control the results. Control, agent technology is still important in a world where it is mature. The failure mode here is not technological and organizational. To point out to an agent without control capability, we are a recipe for disaster, so we need to instill a new quality control and agency feelings in our people.

As an example, today AI systems are highly sensitive to how the questions are broken. The use or “context” is processed by AI’s focus layers, which determines the relative importance of each word or the sign. A slightly incorrect error can be strengthened, the output can be distorted. In the case of autonomous agents, hallucinations are not only cause bad answers, they can trigger mistakes or even dangerous movements. As far as we are confident, these tools will not act irrational, we must keep people in the loop. So it is important to re-thinking the concept of agency.

Agency, in this broader sense, the AI agent, how these tasks are fulfilled and the agent, including people, information sources and other agents. MCP and new communication protocols such as A2A It arises to standardize interactions. However, the human role remains the center.

As young workers receive the responsibilities of “managers”, the traditional borders between work and engineering are solved. As product managers and engineers converted, today’s specialists must be fluent in both domains. Now it means to be an excellent product manager to be a great engineer: understand the client, identify risks and biases and design a compensation control design. This is the mindset that we should cultivate in our AI-native workforce. They are expected to manage their AI agents, not only by giving commands, but to understand their capabilities and restrictions and waiting for the risks. Control, requires an experience and requires experience, this tempo is a difficult commodity.

Cultivated transformation

The rise of artificial intelligence is not just a technological evolution – a cultural change that changes most of these organizations. His effect reaches aside gaining productivity, it complicates how structural teams are built, identifying roles and manage the performance of human and AI agents in Hybrid Workforce.

We enter a circuit that developers do not just write the code, and knowledge workers can summarize complex documents per second. But these are surface level changes. At a deeper level, we must reconstruct the basic elements of our enterprises: how we cooperate, how we lead and how we grow. This transformation is not only technical; It is also mainly psychological and management. When AI agents include daily workflows, human staff will experience a change in identity, agency and expectations. Leaders should therefore re-think of management science. We must prepare new models for both not only for people, but also for people, but also, training and career development.

As people, AI agents will require “career paths” and management frameworks and will be able to play the role, and where they can be used in the best way and place the management process. We must develop our teams together with more efficient, expanding virtual colleagues, and we can work 24 hours a week in 7 days. If we do not turn off them, they will never go out or retire.

We need to equip the employees with their skills to control this turn. This includes the ability to communicate, entrust and control. In a world where everyone can twist a number of virtual colleagues, the basic restriction, the concept of individual contribution changes to the player-coach.

Control is the key to this evolution. We must ensure that the representatives have the ability to inspect the quality of the work created by the EU. Imagine an airway due to the application of autopilot with automatic land and automatic flight features, autopil flight features, some flights only decide to fill with small pilots. Will we feel the same feeling of security and quality? If we feel properly equipped to control the small pilots.

As a result, the cultural transformation is more than accepting new tools during such sharp technological development. A new generation is to accelerate ways to form and practice, equip them from start-up management skills and use innate dating and skills with this new technology.

Today, the change of technology is ahead of human change. To break old habits and build new skills, the program and aIB again reset the human brain, easier to change. Non-AI locals – most of all we have are the most difficult task: to exercise a new generation in Baton and equip the skills needed to manage something that does not fully understand the current generation. All this without luxury of time.

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