From practical noise from artificial intelligence to practical application: Why should institutions think about the suitability

We fully enter the era of independent transformation, Artificial intelligence agents It transforms how companies work and create value. But with hundreds of sellers demanding that they provide “artificial intelligence agents”, how can we penetrate the noise and understand what these systems can really accomplish, and most importantly, how should we use it?

The answer is more complicated than creating a list of tasks that can automatically and test whether the artificial intelligence agent can achieve these tasks against the standards. The plane can move faster than the car, but it is the wrong option for a trip to the grocery store.

Why should we not try to replace our work with artificial intelligence agents

Each institution creates a certain amount of value for its customers, partners and employees.

This amount is a small part of the total capacitable value of the value (i.e. the total amount of value that the institution can make by its customers, partners and employees).

If each employee leaves the working day with a long list of tasks for the next day and another list of tasks to completely re-coordinate them-elements that create value if it is possible to give priority-there is an imbalance in value, time and effort, and leave the value on the table.

The easiest place to start with Artificial intelligence agents The work that is already taking place and the value that is created. This makes initial mental mathematics easy, as you can set the existing value and analyze opportunities to create the same value faster or more reliable.

There is nothing wrong with this exercise as a stage in the transformation process, but where most institutions and artificial intelligence initiatives fail in Just look How artificial intelligence can apply to the value that is already created. This narrows their focus and investments in the narrow intertwined fragment in the Finn scheme below, leaving the majority of the value that is cursed on the table.

Humans and machines, by their nature, have different strengths and weaknesses. The institutions that re -invent work with their partners in the field of business, technology and partners in the industry will outperform those who focus only on one set of value and monitor greater degrees of automation without increasing the total value of the value.

Understanding the capabilities of the artificial intelligence agent through the Spar framework

To help explain how Artificial intelligence agents workWe have created what we call the Spar framework: meaning, planning, behavior and thinking. This framework reflects how humans achieve our goals and provide a natural way to understand how artificial intelligence agents work.

SensorJust as we use our senses to collect information around the world around us, artificial intelligence agents collect signals from their environment. They follow the operators, collect relevant information and monitor their operating context.

planning: Once the agent collects signals around his environment, he does not only jump into implementation. Like people who think about their options before acting, artificial intelligence agents are developed to address the information available in the context of their goals and rules to make enlightened decisions about achieving their goals.

representationThe ability to take concrete measures that distinguish artificial intelligence factors from simple analytical systems. They can coordinate multiple tools and systems to carry out tasks, monitor their actions in actual time, and make adjustments to stay in the path.

ThinkingPerhaps the most developed ability is learning from experience. Advanced artificial intelligence can evaluate their performance, analyze results and improve their methods based on better – create a continuous improvement course.

What makes artificial intelligence agents strong is how these four capabilities work together in an integrated cycle, creating a system that can follow complex goals with increased development.

This exploratory ability can contradict the current processes that have already been improved several times through digital transformation. It may result in a small -term reinvention, but exploring new ways to create value and making new markets that can lead to significant growth.

5 steps to build an artificial intelligence agent strategy

Most technicians, consultants and business leaders follow a traditional approach when introducing artificial intelligence (87 % failure): 87 %):

1. Create a list of problems;

or

1. Check your data;
2. Choose a set of possible use cases;
3. Analysis of use cases for return on investment (ROI), feasibility, cost, schedule;
4. Choose a sub -set of cases of use and investment in implementation.

This approach may seem defense because it is understood that it is best practices, but the data shows that it does not work. It’s time for a new approach.

1. Plan the total capable value that your organization can provide to your customers and partners, given your basic competencies and the organizational and geopolitical conditions of the market.
2. Evaluate the current value of your organization’s creation.
3. Choose the five best valuable opportunities and manufacture your institution to create a new value.
4. Analysis of the return on investment, feasibility, cost and the timetable for an engineer, AI’s agent solution (Repeat the two steps 3 and 4 as necessary).
5. Choose a sub -set of value and investment in implementation.

Create a new value with artificial intelligence

The journey to the era of independent transformation (with more independent systems that create value continuously) is not an enemy – it is strategic progress, as it builds organizational ability in addition to technological progress. By determining the value at the beginning and the growing aspirations systematically, you will put your organization to flourish in the era of artificial intelligence agents.

Permanent Brian is the author of the book ” Independent transformation: creating a more human future in the era of artificial intelligence

Pascal Burnett, author of the book ” Functional artificial intelligence: Hosage of artificial intelligence agents to re -invent works, work and life

Evergreen and Bornet teach a new online cycle on artificial intelligence agents with Cassie Kozyrkov: Artificial intelligence of the Undersecretary of the leaders