The industrialization of thinking

From the 17th to the mid-20th century, “computer” meant a person who performed mathematical calculations for various purposes. The initial applications were in natural sciences, predominantly astronomy and fluid mechanics; in the twentieth century, these computers were increasingly used for military purposes, nuclear research and then space travel.

It was only when freely programmable calculating machines were developed that the term “computer” transferred to these machines. From then on, the (electronic) computers very quickly took on the work of their human predecessors – leading to the disappearance of an entire profession.

Disruption: AI gobbles up administrative tasks
Today, computers are ever-present in the office environment and since their invention have gained massively in computing power. It is no longer possible to imagine processing data without them in any industry. Nevertheless, in the office, computers are generally seen as little more than tools or equipment – they have become quite complex, obviously, but the actual cognitive work is still carried out by humans. The burning question is whether anything will change in this respect in future – whether sophisticated cognitive tasks can also be handed over to computers. Currently available cognitive systems can, in particular, take on simple tasks that are otherwise unattractive for administrative staff.

This issue is characteristic of business segments in which disruption caused by new technologies is looming. Such revolutions typically begin at the unattractive end of the value chain. The disruptive process for “mental work” has already started: In the field of NLP (natural language processing) in particular, the systems and the possibilities for using them are evolving rapidly (see box).

Standard: machine – Special case: human
Industrialization means the standardization and automation of work processes. Standardization means that processes can always run exactly the same. Even in “mental work”, e.g. in banking and insurance or in administration, it has long been the case that processes are implemented consistently. The division of labor and specialization of departments for subprocesses, typical of industrialization, has also already penetrated most lines of work. And the tools – that is, the software used – are now also largely standardized.

Examples of iintelligent automation of office tasks
One of ti&m’s clients is reviewing customers and potential business partners as part of their own KYC process. Part of this review includes an Internet search. Previously, this search was carried out by employees, who put together a file on the individuals for the purpose of reaching a decision. Today, the file is compiled by an AI-based system – the administrators can thus concentrate entirely on evaluation and decision-making. For another client, ti&m is implementing a system that reads the scanned mail, interprets the data and initiates the relevant processes – which are then executed entirely automatically or by administrative staff.

However, the end-to-end automation that is part of industrialization is still in its infancy; many tasks in the finance industry remain supported by administrative staff, as in the past. That said, there is plenty of research being carried out in this field right now, and accordingly, new technologies are being developed: AI-supported systems are getting better and better at extracting data from documents, classifying it, and executing processes independently on the basis of said data. The projects mentioned in the box are just two examples of this. Other opportunities include the generation of sets of rules for invoicing services in health insurance, or learning rules for automated accounting.

New technologies will ensure that, alongside existing standardization, the automation of business processes will increasingly encompass more areas. As a result, more and more of the relevant “intellectual work” of the administrative staff will be transferred to machines, which are able to make decisions flexibly and execute processes and, at the same time, can deal with much greater complexity than would be possible for a human being.

This automation will mean that the range of tasks carried out by humans becomes ever smaller – and above all, increasingly sophisticated. Here we will see the same pattern as was the case with the industrialization of manufacturing: “actual” production will be fully automated, while special tasks, custom products and the engineering/ design of new products remain the domain of human employees.

“AI-supported systems are getting better and better at executing processes independently.”

New working models, new forms of collaboration, new leadership
The industrialization of intellectual work will bring about a change in work mode: The nature of collaborative working, the organization of businesses, the layout of offices depend heavily on how much “mental input” the work demands. People who carry out individual tasks in a process divided on the basis of Taylorism can very well be accommodated in large offices with one desk next to another. Command & control works well as a management principle here.

However, if the work is harder to plan, more creative, with frequent switching between conceptual (i.e. quiet) work and interaction with other team members, the requirements are completely different: There is far less need for individual desks and much greater need for flexibility for coming together, delineated spaces for uninterrupted communication – and more individual responsibility, delegation and trust in collaborative working and leadership.

The industrialization of thinking also has an impact on the “toolmaker” – i.e., on technology companies such as ti&m. Instead of fully programmed algorithms or parameterized sets of rules, there is a constant need for more systems that can respond to new situations in a flexible and self-learning way. Technology is evolving away from classical programming to data science, AI and similar innovative technologies.

As was the case with the industrialization of manufacturing, it is to be expected that the industrialization of thinking will result in less routine work for people to do, being replaced with more interesting work requiring better training and qualifications. So it is highly likely that in the future more professions will follow in the path of the computer and transfer over from man to machine.

ti&m special Future of Work
New value chains, digitalization and cultural change: numerous factors are fundamentally changing the way we work. Our new special explores what this profound transformation means for companies, management and employees. to download

From the 17th to the mid-20th century, “computer” meant a person who performed mathematical calculations for various purposes. The initial applications were in natural sciences, predominantly astronomy and fluid mechanics; in the twentieth century, these computers were increasingly used for military purposes, nuclear research and then space travel.

It was only when freely programmable calculating machines were developed that the term “computer” transferred to these machines. From then on, the (electronic) computers very quickly took on the work of their human predecessors – leading to the disappearance of an entire profession.

Disruption: AI gobbles up administrative tasks
Today, computers are ever-present in the office environment and since their invention have gained massively in computing power. It is no longer possible to imagine processing data without them in any industry. Nevertheless, in the office, computers are generally seen as little more than tools or equipment – they have become quite complex, obviously, but the actual cognitive work is still carried out by humans. The burning question is whether anything will change in this respect in future – whether sophisticated cognitive tasks can also be handed over to computers. Currently available cognitive systems can, in particular, take on simple tasks that are otherwise unattractive for administrative staff.

This issue is characteristic of business segments in which disruption caused by new technologies is looming. Such revolutions typically begin at the unattractive end of the value chain. The disruptive process for “mental work” has already started: In the field of NLP (natural language processing) in particular, the systems and the possibilities for using them are evolving rapidly (see box).

Standard: machine – Special case: human
Industrialization means the standardization and automation of work processes. Standardization means that processes can always run exactly the same. Even in “mental work”, e.g. in banking and insurance or in administration, it has long been the case that processes are implemented consistently. The division of labor and specialization of departments for subprocesses, typical of industrialization, has also already penetrated most lines of work. And the tools – that is, the software used – are now also largely standardized.

Examples of iintelligent automation of office tasks
One of ti&m’s clients is reviewing customers and potential business partners as part of their own KYC process. Part of this review includes an Internet search. Previously, this search was carried out by employees, who put together a file on the individuals for the purpose of reaching a decision. Today, the file is compiled by an AI-based system – the administrators can thus concentrate entirely on evaluation and decision-making. For another client, ti&m is implementing a system that reads the scanned mail, interprets the data and initiates the relevant processes – which are then executed entirely automatically or by administrative staff.

However, the end-to-end automation that is part of industrialization is still in its infancy; many tasks in the finance industry remain supported by administrative staff, as in the past. That said, there is plenty of research being carried out in this field right now, and accordingly, new technologies are being developed: AI-supported systems are getting better and better at extracting data from documents, classifying it, and executing processes independently on the basis of said data. The projects mentioned in the box are just two examples of this. Other opportunities include the generation of sets of rules for invoicing services in health insurance, or learning rules for automated accounting.

New technologies will ensure that, alongside existing standardization, the automation of business processes will increasingly encompass more areas. As a result, more and more of the relevant “intellectual work” of the administrative staff will be transferred to machines, which are able to make decisions flexibly and execute processes and, at the same time, can deal with much greater complexity than would be possible for a human being.

This automation will mean that the range of tasks carried out by humans becomes ever smaller – and above all, increasingly sophisticated. Here we will see the same pattern as was the case with the industrialization of manufacturing: “actual” production will be fully automated, while special tasks, custom products and the engineering/ design of new products remain the domain of human employees.

“AI-supported systems are getting better and better at executing processes independently.”

New working models, new forms of collaboration, new leadership
The industrialization of intellectual work will bring about a change in work mode: The nature of collaborative working, the organization of businesses, the layout of offices depend heavily on how much “mental input” the work demands. People who carry out individual tasks in a process divided on the basis of Taylorism can very well be accommodated in large offices with one desk next to another. Command & control works well as a management principle here.

However, if the work is harder to plan, more creative, with frequent switching between conceptual (i.e. quiet) work and interaction with other team members, the requirements are completely different: There is far less need for individual desks and much greater need for flexibility for coming together, delineated spaces for uninterrupted communication – and more individual responsibility, delegation and trust in collaborative working and leadership.

The industrialization of thinking also has an impact on the “toolmaker” – i.e., on technology companies such as ti&m. Instead of fully programmed algorithms or parameterized sets of rules, there is a constant need for more systems that can respond to new situations in a flexible and self-learning way. Technology is evolving away from classical programming to data science, AI and similar innovative technologies.

As was the case with the industrialization of manufacturing, it is to be expected that the industrialization of thinking will result in less routine work for people to do, being replaced with more interesting work requiring better training and qualifications. So it is highly likely that in the future more professions will follow in the path of the computer and transfer over from man to machine.

ti&m special Future of Work
New value chains, digitalization and cultural change: numerous factors are fundamentally changing the way we work. Our new special explores what this profound transformation means for companies, management and employees. to download

From the 17th to the mid-20th century, “computer” meant a person who performed mathematical calculations for various purposes. The initial applications were in natural sciences, predominantly astronomy and fluid mechanics; in the twentieth century, these computers were increasingly used for military purposes, nuclear research and then space travel.

It was only when freely programmable calculating machines were developed that the term “computer” transferred to these machines. From then on, the (electronic) computers very quickly took on the work of their human predecessors – leading to the disappearance of an entire profession.

Disruption: AI gobbles up administrative tasks
Today, computers are ever-present in the office environment and since their invention have gained massively in computing power. It is no longer possible to imagine processing data without them in any industry. Nevertheless, in the office, computers are generally seen as little more than tools or equipment – they have become quite complex, obviously, but the actual cognitive work is still carried out by humans. The burning question is whether anything will change in this respect in future – whether sophisticated cognitive tasks can also be handed over to computers. Currently available cognitive systems can, in particular, take on simple tasks that are otherwise unattractive for administrative staff.

This issue is characteristic of business segments in which disruption caused by new technologies is looming. Such revolutions typically begin at the unattractive end of the value chain. The disruptive process for “mental work” has already started: In the field of NLP (natural language processing) in particular, the systems and the possibilities for using them are evolving rapidly (see box).

Standard: machine – Special case: human
Industrialization means the standardization and automation of work processes. Standardization means that processes can always run exactly the same. Even in “mental work”, e.g. in banking and insurance or in administration, it has long been the case that processes are implemented consistently. The division of labor and specialization of departments for subprocesses, typical of industrialization, has also already penetrated most lines of work. And the tools – that is, the software used – are now also largely standardized.

Examples of iintelligent automation of office tasks
One of ti&m’s clients is reviewing customers and potential business partners as part of their own KYC process. Part of this review includes an Internet search. Previously, this search was carried out by employees, who put together a file on the individuals for the purpose of reaching a decision. Today, the file is compiled by an AI-based system – the administrators can thus concentrate entirely on evaluation and decision-making. For another client, ti&m is implementing a system that reads the scanned mail, interprets the data and initiates the relevant processes – which are then executed entirely automatically or by administrative staff.

However, the end-to-end automation that is part of industrialization is still in its infancy; many tasks in the finance industry remain supported by administrative staff, as in the past. That said, there is plenty of research being carried out in this field right now, and accordingly, new technologies are being developed: AI-supported systems are getting better and better at extracting data from documents, classifying it, and executing processes independently on the basis of said data. The projects mentioned in the box are just two examples of this. Other opportunities include the generation of sets of rules for invoicing services in health insurance, or learning rules for automated accounting.

New technologies will ensure that, alongside existing standardization, the automation of business processes will increasingly encompass more areas. As a result, more and more of the relevant “intellectual work” of the administrative staff will be transferred to machines, which are able to make decisions flexibly and execute processes and, at the same time, can deal with much greater complexity than would be possible for a human being.

This automation will mean that the range of tasks carried out by humans becomes ever smaller – and above all, increasingly sophisticated. Here we will see the same pattern as was the case with the industrialization of manufacturing: “actual” production will be fully automated, while special tasks, custom products and the engineering/ design of new products remain the domain of human employees.

“AI-supported systems are getting better and better at executing processes independently.”

New working models, new forms of collaboration, new leadership
The industrialization of intellectual work will bring about a change in work mode: The nature of collaborative working, the organization of businesses, the layout of offices depend heavily on how much “mental input” the work demands. People who carry out individual tasks in a process divided on the basis of Taylorism can very well be accommodated in large offices with one desk next to another. Command & control works well as a management principle here.

However, if the work is harder to plan, more creative, with frequent switching between conceptual (i.e. quiet) work and interaction with other team members, the requirements are completely different: There is far less need for individual desks and much greater need for flexibility for coming together, delineated spaces for uninterrupted communication – and more individual responsibility, delegation and trust in collaborative working and leadership.

The industrialization of thinking also has an impact on the “toolmaker” – i.e., on technology companies such as ti&m. Instead of fully programmed algorithms or parameterized sets of rules, there is a constant need for more systems that can respond to new situations in a flexible and self-learning way. Technology is evolving away from classical programming to data science, AI and similar innovative technologies.

As was the case with the industrialization of manufacturing, it is to be expected that the industrialization of thinking will result in less routine work for people to do, being replaced with more interesting work requiring better training and qualifications. So it is highly likely that in the future more professions will follow in the path of the computer and transfer over from man to machine.

ti&m special Future of Work
New value chains, digitalization and cultural change: numerous factors are fundamentally changing the way we work. Our new special explores what this profound transformation means for companies, management and employees. to download

From the 17th to the mid-20th century, “computer” meant a person who performed mathematical calculations for various purposes. The initial applications were in natural sciences, predominantly astronomy and fluid mechanics; in the twentieth century, these computers were increasingly used for military purposes, nuclear research and then space travel.

It was only when freely programmable calculating machines were developed that the term “computer” transferred to these machines. From then on, the (electronic) computers very quickly took on the work of their human predecessors – leading to the disappearance of an entire profession.

Disruption: AI gobbles up administrative tasks
Today, computers are ever-present in the office environment and since their invention have gained massively in computing power. It is no longer possible to imagine processing data without them in any industry. Nevertheless, in the office, computers are generally seen as little more than tools or equipment – they have become quite complex, obviously, but the actual cognitive work is still carried out by humans. The burning question is whether anything will change in this respect in future – whether sophisticated cognitive tasks can also be handed over to computers. Currently available cognitive systems can, in particular, take on simple tasks that are otherwise unattractive for administrative staff.

This issue is characteristic of business segments in which disruption caused by new technologies is looming. Such revolutions typically begin at the unattractive end of the value chain. The disruptive process for “mental work” has already started: In the field of NLP (natural language processing) in particular, the systems and the possibilities for using them are evolving rapidly (see box).

Standard: machine – Special case: human
Industrialization means the standardization and automation of work processes. Standardization means that processes can always run exactly the same. Even in “mental work”, e.g. in banking and insurance or in administration, it has long been the case that processes are implemented consistently. The division of labor and specialization of departments for subprocesses, typical of industrialization, has also already penetrated most lines of work. And the tools – that is, the software used – are now also largely standardized.

Examples of iintelligent automation of office tasks
One of ti&m’s clients is reviewing customers and potential business partners as part of their own KYC process. Part of this review includes an Internet search. Previously, this search was carried out by employees, who put together a file on the individuals for the purpose of reaching a decision. Today, the file is compiled by an AI-based system – the administrators can thus concentrate entirely on evaluation and decision-making. For another client, ti&m is implementing a system that reads the scanned mail, interprets the data and initiates the relevant processes – which are then executed entirely automatically or by administrative staff.

However, the end-to-end automation that is part of industrialization is still in its infancy; many tasks in the finance industry remain supported by administrative staff, as in the past. That said, there is plenty of research being carried out in this field right now, and accordingly, new technologies are being developed: AI-supported systems are getting better and better at extracting data from documents, classifying it, and executing processes independently on the basis of said data. The projects mentioned in the box are just two examples of this. Other opportunities include the generation of sets of rules for invoicing services in health insurance, or learning rules for automated accounting.

New technologies will ensure that, alongside existing standardization, the automation of business processes will increasingly encompass more areas. As a result, more and more of the relevant “intellectual work” of the administrative staff will be transferred to machines, which are able to make decisions flexibly and execute processes and, at the same time, can deal with much greater complexity than would be possible for a human being.

This automation will mean that the range of tasks carried out by humans becomes ever smaller – and above all, increasingly sophisticated. Here we will see the same pattern as was the case with the industrialization of manufacturing: “actual” production will be fully automated, while special tasks, custom products and the engineering/ design of new products remain the domain of human employees.

“AI-supported systems are getting better and better at executing processes independently.”

New working models, new forms of collaboration, new leadership
The industrialization of intellectual work will bring about a change in work mode: The nature of collaborative working, the organization of businesses, the layout of offices depend heavily on how much “mental input” the work demands. People who carry out individual tasks in a process divided on the basis of Taylorism can very well be accommodated in large offices with one desk next to another. Command & control works well as a management principle here.

However, if the work is harder to plan, more creative, with frequent switching between conceptual (i.e. quiet) work and interaction with other team members, the requirements are completely different: There is far less need for individual desks and much greater need for flexibility for coming together, delineated spaces for uninterrupted communication – and more individual responsibility, delegation and trust in collaborative working and leadership.

The industrialization of thinking also has an impact on the “toolmaker” – i.e., on technology companies such as ti&m. Instead of fully programmed algorithms or parameterized sets of rules, there is a constant need for more systems that can respond to new situations in a flexible and self-learning way. Technology is evolving away from classical programming to data science, AI and similar innovative technologies.

As was the case with the industrialization of manufacturing, it is to be expected that the industrialization of thinking will result in less routine work for people to do, being replaced with more interesting work requiring better training and qualifications. So it is highly likely that in the future more professions will follow in the path of the computer and transfer over from man to machine.

ti&m special Future of Work
New value chains, digitalization and cultural change: numerous factors are fundamentally changing the way we work. Our new special explores what this profound transformation means for companies, management and employees. to download

From the 17th to the mid-20th century, “computer” meant a person who performed mathematical calculations for various purposes. The initial applications were in natural sciences, predominantly astronomy and fluid mechanics; in the twentieth century, these computers were increasingly used for military purposes, nuclear research and then space travel.

It was only when freely programmable calculating machines were developed that the term “computer” transferred to these machines. From then on, the (electronic) computers very quickly took on the work of their human predecessors – leading to the disappearance of an entire profession.

Disruption: AI gobbles up administrative tasks
Today, computers are ever-present in the office environment and since their invention have gained massively in computing power. It is no longer possible to imagine processing data without them in any industry. Nevertheless, in the office, computers are generally seen as little more than tools or equipment – they have become quite complex, obviously, but the actual cognitive work is still carried out by humans. The burning question is whether anything will change in this respect in future – whether sophisticated cognitive tasks can also be handed over to computers. Currently available cognitive systems can, in particular, take on simple tasks that are otherwise unattractive for administrative staff.

This issue is characteristic of business segments in which disruption caused by new technologies is looming. Such revolutions typically begin at the unattractive end of the value chain. The disruptive process for “mental work” has already started: In the field of NLP (natural language processing) in particular, the systems and the possibilities for using them are evolving rapidly (see box).

Standard: machine – Special case: human
Industrialization means the standardization and automation of work processes. Standardization means that processes can always run exactly the same. Even in “mental work”, e.g. in banking and insurance or in administration, it has long been the case that processes are implemented consistently. The division of labor and specialization of departments for subprocesses, typical of industrialization, has also already penetrated most lines of work. And the tools – that is, the software used – are now also largely standardized.

Examples of iintelligent automation of office tasks
One of ti&m’s clients is reviewing customers and potential business partners as part of their own KYC process. Part of this review includes an Internet search. Previously, this search was carried out by employees, who put together a file on the individuals for the purpose of reaching a decision. Today, the file is compiled by an AI-based system – the administrators can thus concentrate entirely on evaluation and decision-making. For another client, ti&m is implementing a system that reads the scanned mail, interprets the data and initiates the relevant processes – which are then executed entirely automatically or by administrative staff.

However, the end-to-end automation that is part of industrialization is still in its infancy; many tasks in the finance industry remain supported by administrative staff, as in the past. That said, there is plenty of research being carried out in this field right now, and accordingly, new technologies are being developed: AI-supported systems are getting better and better at extracting data from documents, classifying it, and executing processes independently on the basis of said data. The projects mentioned in the box are just two examples of this. Other opportunities include the generation of sets of rules for invoicing services in health insurance, or learning rules for automated accounting.

New technologies will ensure that, alongside existing standardization, the automation of business processes will increasingly encompass more areas. As a result, more and more of the relevant “intellectual work” of the administrative staff will be transferred to machines, which are able to make decisions flexibly and execute processes and, at the same time, can deal with much greater complexity than would be possible for a human being.

This automation will mean that the range of tasks carried out by humans becomes ever smaller – and above all, increasingly sophisticated. Here we will see the same pattern as was the case with the industrialization of manufacturing: “actual” production will be fully automated, while special tasks, custom products and the engineering/ design of new products remain the domain of human employees.

“AI-supported systems are getting better and better at executing processes independently.”

New working models, new forms of collaboration, new leadership
The industrialization of intellectual work will bring about a change in work mode: The nature of collaborative working, the organization of businesses, the layout of offices depend heavily on how much “mental input” the work demands. People who carry out individual tasks in a process divided on the basis of Taylorism can very well be accommodated in large offices with one desk next to another. Command & control works well as a management principle here.

However, if the work is harder to plan, more creative, with frequent switching between conceptual (i.e. quiet) work and interaction with other team members, the requirements are completely different: There is far less need for individual desks and much greater need for flexibility for coming together, delineated spaces for uninterrupted communication – and more individual responsibility, delegation and trust in collaborative working and leadership.

The industrialization of thinking also has an impact on the “toolmaker” – i.e., on technology companies such as ti&m. Instead of fully programmed algorithms or parameterized sets of rules, there is a constant need for more systems that can respond to new situations in a flexible and self-learning way. Technology is evolving away from classical programming to data science, AI and similar innovative technologies.

As was the case with the industrialization of manufacturing, it is to be expected that the industrialization of thinking will result in less routine work for people to do, being replaced with more interesting work requiring better training and qualifications. So it is highly likely that in the future more professions will follow in the path of the computer and transfer over from man to machine.

ti&m special Future of Work
New value chains, digitalization and cultural change: numerous factors are fundamentally changing the way we work. Our new special explores what this profound transformation means for companies, management and employees. to download

From the 17th to the mid-20th century, “computer” meant a person who performed mathematical calculations for various purposes. The initial applications were in natural sciences, predominantly astronomy and fluid mechanics; in the twentieth century, these computers were increasingly used for military purposes, nuclear research and then space travel.

It was only when freely programmable calculating machines were developed that the term “computer” transferred to these machines. From then on, the (electronic) computers very quickly took on the work of their human predecessors – leading to the disappearance of an entire profession.

Disruption: AI gobbles up administrative tasks
Today, computers are ever-present in the office environment and since their invention have gained massively in computing power. It is no longer possible to imagine processing data without them in any industry. Nevertheless, in the office, computers are generally seen as little more than tools or equipment – they have become quite complex, obviously, but the actual cognitive work is still carried out by humans. The burning question is whether anything will change in this respect in future – whether sophisticated cognitive tasks can also be handed over to computers. Currently available cognitive systems can, in particular, take on simple tasks that are otherwise unattractive for administrative staff.

This issue is characteristic of business segments in which disruption caused by new technologies is looming. Such revolutions typically begin at the unattractive end of the value chain. The disruptive process for “mental work” has already started: In the field of NLP (natural language processing) in particular, the systems and the possibilities for using them are evolving rapidly (see box).

Standard: machine – Special case: human
Industrialization means the standardization and automation of work processes. Standardization means that processes can always run exactly the same. Even in “mental work”, e.g. in banking and insurance or in administration, it has long been the case that processes are implemented consistently. The division of labor and specialization of departments for subprocesses, typical of industrialization, has also already penetrated most lines of work. And the tools – that is, the software used – are now also largely standardized.

Examples of iintelligent automation of office tasks
One of ti&m’s clients is reviewing customers and potential business partners as part of their own KYC process. Part of this review includes an Internet search. Previously, this search was carried out by employees, who put together a file on the individuals for the purpose of reaching a decision. Today, the file is compiled by an AI-based system – the administrators can thus concentrate entirely on evaluation and decision-making. For another client, ti&m is implementing a system that reads the scanned mail, interprets the data and initiates the relevant processes – which are then executed entirely automatically or by administrative staff.

However, the end-to-end automation that is part of industrialization is still in its infancy; many tasks in the finance industry remain supported by administrative staff, as in the past. That said, there is plenty of research being carried out in this field right now, and accordingly, new technologies are being developed: AI-supported systems are getting better and better at extracting data from documents, classifying it, and executing processes independently on the basis of said data. The projects mentioned in the box are just two examples of this. Other opportunities include the generation of sets of rules for invoicing services in health insurance, or learning rules for automated accounting.

New technologies will ensure that, alongside existing standardization, the automation of business processes will increasingly encompass more areas. As a result, more and more of the relevant “intellectual work” of the administrative staff will be transferred to machines, which are able to make decisions flexibly and execute processes and, at the same time, can deal with much greater complexity than would be possible for a human being.

This automation will mean that the range of tasks carried out by humans becomes ever smaller – and above all, increasingly sophisticated. Here we will see the same pattern as was the case with the industrialization of manufacturing: “actual” production will be fully automated, while special tasks, custom products and the engineering/ design of new products remain the domain of human employees.

“AI-supported systems are getting better and better at executing processes independently.”

New working models, new forms of collaboration, new leadership
The industrialization of intellectual work will bring about a change in work mode: The nature of collaborative working, the organization of businesses, the layout of offices depend heavily on how much “mental input” the work demands. People who carry out individual tasks in a process divided on the basis of Taylorism can very well be accommodated in large offices with one desk next to another. Command & control works well as a management principle here.

However, if the work is harder to plan, more creative, with frequent switching between conceptual (i.e. quiet) work and interaction with other team members, the requirements are completely different: There is far less need for individual desks and much greater need for flexibility for coming together, delineated spaces for uninterrupted communication – and more individual responsibility, delegation and trust in collaborative working and leadership.

The industrialization of thinking also has an impact on the “toolmaker” – i.e., on technology companies such as ti&m. Instead of fully programmed algorithms or parameterized sets of rules, there is a constant need for more systems that can respond to new situations in a flexible and self-learning way. Technology is evolving away from classical programming to data science, AI and similar innovative technologies.

As was the case with the industrialization of manufacturing, it is to be expected that the industrialization of thinking will result in less routine work for people to do, being replaced with more interesting work requiring better training and qualifications. So it is highly likely that in the future more professions will follow in the path of the computer and transfer over from man to machine.

ti&m special Future of Work
New value chains, digitalization and cultural change: numerous factors are fundamentally changing the way we work. Our new special explores what this profound transformation means for companies, management and employees. to download