What is Artificial Intelligence (AI)?

Artificial Intelligence is not new, but it has been getting new attention since end of 2022 with the introduction of ChatGPT. Read here what you need to know about AI.

AI at a glance

AI at a glance

Artificial Intelligence - Basic knowledge, application areas and trends

Artificial Intelligence - Basic knowledge, application areas and trends

Is this the final breakthrough for Artificial Intelligence?

With the AI-based chatbot ChatGPT from the Californian start-up OpenAI, the topic of AI has received a lot of attention since the end of 2022.

With ChatGPT - it seems - the topic of AI has become suitable for the masses. Users simply call up the provider's site, enter their question, and receive an answer within seconds.

This development is attracting the attention of the tech giants:

  • Microsoft has been cooperating with OpenAI since 2019 and has already integrated ChatGPT into its own search engine.
  • Apple restricts the use of the tool for its own employees and is working on its own solution.
  • And Google is holding its own with its own chatbot Bard, which was launched in March 2023.

But AI is not just for end users. Currently, numerous useful AI functions are already making their way into companies - including ERP systems such as SAP S/4HANA.

Experts agree that companies can tap into enormous potential with the help of AI.

  • Many errors can be identified before they occur.
  • Companies can optimize customer relationships, logistics chains and flows of goods.
  • In addition, complete processes can soon be automated.

But what exactly is behind the term Artificial Intelligence? How long have AI applications been available and why are they becoming increasingly popular? What can AI already do today and where are the limits?

What do terms like "machine learning" and "deep learning" mean? How will Artificial Intelligence change companies and society in the future? And how does SAP deal with artificial intelligence?

On this page you will find answers to these and many other questions about AI.

Artificial Intelligence: Definition

Artificial Intelligence: Definition

Artificial Intelligence (AI) is a discipline of computer science. In Germany, the synonym Artificial Intelligence (AI) is also used.

AI deals with methods that enable machines (computers) to solve tasks in the same way as a human would do with his intelligence.

AI therefore encompasses not only aspects of information technology, but also psychology, neuroscience, linguistics, communication sciences, mathematics, and philosophy.

Computer science is thus more of a means to an end. It brings the various disciplines together and enables implementation.

In order for AI to be able to solve tasks independently, it must be trained. To do this, experts use special algorithms and provide the AI with training data. Through constant training, the AI continues to improve - until it can solve the set tasks itself.

There are basically two or three types of Artificial Intelligence:

1. Autonomous and automatic completion of tasks (weak AI)

The most widely used AI today is a "Weak AI", a weak Artificial Intelligence.

Solutions such as intelligent software assistants, Internet search engines, self-driving cars or voice recognition systems already work with AI and are increasingly finding their way into our everyday lives.

Although corresponding systems have already achieved enormous performance, they are called weak AI in technical jargon.

The reason for this is that weak AI solutions operate at a relatively superficial intelligence level and do not develop a deep understanding of problem solving.

2. Imitation of human thinking and behavior (strong AI)

Strong AI (also called "Strong AI") aims to match or exceed human intellectual capabilities.

Systems with strong AI can recognize patterns and learn. Most importantly, they can apply the knowledge they acquire to many new tasks not covered by existing algorithms.

Strong AI acts actively and flexibly and on par with humans. However, systems with strong AI do not currently exist.

3. Artificial Superintelligence

Systems with "artificial superintelligence" theoretically have a consciousness and human characteristics such as emotions.

To date, it has not yet been possible to develop such a superintelligence. In research circles, there is controversial discussion about whether the development of such an AI is even feasible.

Difference between Artificial Intelligence, Machine Learning and Deep Learning

Difference between Artificial Intelligence, Machine Learning and Deep Learning

Artificial Intelligence, Machine Learning and Deep Learning are different.

  • Artificial Intelligence (or Artificial Intelligence) is an umbrella term that encompasses technologies and methods that enable machines to mimic human thinking.
  • Machine Learning is a subfield of AI that stands for the ability of machines to continuously improve themselves with the help of pattern recognition and training data.
  • Deep learning, in turn, is a subfield of machine learning. Here, the machines train themselves with the help of multilayer neural networks and can solve highly complex tasks.

Let's take a closer look at the approaches below to further highlight the differences.

Machine Learning

Machine Learning

Machine learning describes mathematical methods that enable a machine to independently generate knowledge from empirical values.

Or to put it more simply: Machine Learning lets computers do useful things without first programming them to do so. Only the algorithm is programmed.

From a technical point of view, machine learning uses algorithms (calculation rules) that can independently recognize regularities and patterns in data. To do this, they must first be provided with extensive data and trained.

In the development phase, a programmer ensures that the machine learning model is continuously adapted and optimized.

In this way, the algorithm becomes "smarter" from data set to data set through pattern recognition until it can finally perform its task independently with new and unknown data.

The main goals of machine learning are,

  • to recognize correlations,
  • to link data intelligently,
  • to draw conclusions and
  • make precise predictions.

In the business environment, machine learning applications have the potential to relieve employees of tedious, unproductive tasks. This frees up resources for new areas and makes work more efficient and economical.

For example, learning software can independently scan paper documents, recognize the text, initiate further steps and organize archiving.

A more complex scenario in which machine learning is already being used today is predictive maintenance. The algorithms used are able to detect possible damage to technical equipment and error patterns at an early stage in order to request maintenance if necessary.

Voice recognition on cell phones, spam filters in e-mail inboxes, and even facial recognition in photo management are all controlled in significant parts by machine learning algorithms.

Often, we humans are already in contact with machine learning today without even knowing it. This is the case, for example, when we are shown personalized advertising.

Deep Learning

Deep Learning

Deep Learning is a subfield of Machine Learning. It is a special method that uses so-called "deep" artificial neural networks (Deep Neural Networks or DNN) and huge amounts of data to learn particularly efficiently.

The method is based on learning processes in the human brain. Based on the information available, corresponding systems can repeatedly link what has been learned with new content and thus continuously learn new things.

At a certain point, the machine is then able to provide forecasts, make independent decisions and question them. If the result of the decision is not satisfactory, it is adjusted in a new attempt.

Humans do not normally intervene in this learning process. This is also the essential difference to Machine Learning.

Deep Learning is particularly suitable for scenarios in which large amounts of data are to be examined for models and patterns. Examples of applications here are also speech, object or face recognition.

In speech recognition, for example, Deep Learning makes it possible to independently expand the vocabulary of systems with new words and word variants. Other areas of application include autonomous vehicles or robots, AI in computer games, or a prediction of customer behavior as part of CRM solutions.

What is ChatGPT?

What is ChatGPT?

ChatGPT is a chatbot from OpenAI, a US-based company involved in AI development and research.

Through ChatGPT's interface, users can enter their questions and receive answers generated by the chatbot. The possible uses are many:

  • from the creation of a wide variety of texts
  • to checking spelling,
  • from the rephrasing of given texts to the listing of questions
  • to listing questions on a specific topic.

OpenAI's language model has been and is being trained with real texts (based on texts up to the year 2021) and is constantly improving. However, the answers are not always error-free, as many examples have already shown.

Development and use of Artificial Intelligence

Development and use of Artificial Intelligence

Since its emergence, Artificial Intelligence has made enormous leaps in development. This is especially true for the recent past. In the management of corporations, AI is currently a topic of the future, in which the potential is seen to fundamentally change companies and society.

Through the use of AI, opportunities arise to optimize one's own business and even to reorganize entire industries. But how did Artificial Intelligence come about and what forms have corresponding systems actually reached to date?

History: The beginning of Artificial Intelligence

History: The beginning of Artificial Intelligence

The origins of Artificial Intelligence date back to the 1950s. As early as that decade, the term was used at a science conference in the United States. Scientist Marvin Minsky is considered one of the founding fathers of AI.

In 1966, Minsky defined AI thus: "Artificial Intelligence is the science of making machines do things that would require intelligence if done by men." Loosely translated, this means artificial intelligence is when machines do things that require human intelligence to do.

Also, an early milestone in AI was the Turing Test. Developed in the 1950s by British mathematician Alan Turing, it was designed to allow a human to communicate synchronously with other humans and a machine via chat software.

In the 1960s, the so-called "General Problem Solver" was presented. This was an AI system that could solve simple problems. In the same decade, the ELIZA software caused a sensation. At the time, the chat system made it possible to simulate therapy conversations.

In 1996, a computer beat the then reigning world chess champion Garri Kasparov. In the following decades, the capabilities of Artificial Intelligence improved continuously. This was largely due to steadily improving memory capabilities and computing power.

In 2011, IBM's Watson software was introduced. It was able to win the quiz show Jeopardy against human opponents. AlphaGo is another AI program that achieved the feat, previously considered nearly impossible, of beating the world's best professional Go player in 2016.

Today's use of Artificial Intelligence

Today's use of Artificial Intelligence

Artificial intelligence is now present in both our personal and professional lives. A classic example is speech recognition, which has gained notoriety through applications such as the voice assistants Siri (from Apple) and Alexa (from Amazon). In addition, work is being done on translation systems that translate conversations live into another language.

In addition, for some years now we have encountered so-called chatbots, which are used by companies to increase the efficiency of customer communication.

This is software that can conduct a dialog with users through extensive databases, linguistic knowledge and a full-text search engine. In English-speaking countries, chatbots already act as contact persons for medical questions.

Another important area of application for Artificial Intelligence is predictive analytics. Here, algorithms create predictions for the future development of customer relationships, results and business processes on the basis of historical data from a wide range of sources. The financial sector uses corresponding applications in claims management and for fraud detection.

Predictive analytics can also be used to optimize the planning of marketing campaigns. For example, algorithms can predict which customer will buy a particular product, at what time, and where.

AI applications are also used in service management. Here, for example, Artificial Intelligence takes over the categorization of incidents and the management of support dialogs. In addition, support staff can be assisted in analyzing and solving problems, provided a suitable knowledge database is available

In IT security, AI has also led to significant improvements. Here, AI-based solutions now make it possible to identify attack patterns and prioritize security incidents. Security systems are continuously evolving with machine learning methods by collecting, analyzing and classifying threat data.

What does Artificial Intelligence mean for SAP?

What does Artificial Intelligence mean for SAP?

SAP's current direction suggests: The Walldorf-based company wants to position itself as a software provider that makes intelligent companies possible with its products.

AI - in addition to the focus on cloud ERP systems - is a central element for SAP on this path.

With Artificial Intelligence, SAP aims to automate all business processes and improve the user experience, among other things - for all end-to-end processes from Lead-to-Cash to Design-to-Operate to Recruit-to-Retire.

Since 2023, SAP has been stepping up its efforts to integrate as many AI solutions as possible into the entire portfolio and thus make them usable. SAP has introduced the generic term SAP Business AI for this purpose.

Currently (as of May 2023), SAP offers over 130 AI application scenarios that are already integrated into SAP software. According to SAP, these solutions are already being used by around 23,000 customers.

In the future, the company will also focus on Generative AI. This form of AI stands for systems that can be used to generate something new based on data (for example, texts, images or videos).

One of the long-term goals is, among other things, an ERP solution that can be operated primarily by means of speech recognition.

For this purpose, the integrated assistant called "CoPilot" was already introduced a few years ago. It enables users to interact with the system by voice (or keyboard and chat function) and, for example, to search for information.

In purchasing and sourcing, for example, voice-based elements are intended to speed up and simplify purchase requisitions. Sales staff, on the other hand, will be able to convert offers into orders via voice command.

Another vision is an intelligent assistant that is able, for example, to understand the agenda of meetings and automatically provide the appropriate key figures. The corresponding software should learn from the user's habits and adapt intelligently on this basis.

Another important area of application for artificial intelligence in the SAP environment will be the automation of processes. This will result in enormous savings for companies.

Artificial Intelligence

Are you already using AI for automation in SAP? Find out how you can take your accounting to a new level with the help of our partner Nooxit.

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Current AI solutions from SAP.

Current AI solutions from SAP.

SAP already has a large number of AI and machine learning applications in its portfolio - and for almost every business area and core business process. Artificial Intelligence and Machine Learning are already integrated in the SAP product SAP S/4HANA.

For example, these include:

Lead-to-Cash Process

  • SAP Emarsys Customer Engagement: predicting customer purchase intent with AI lead scoring and increasing online sales with personalized product recommendations
  • SAP Sales Cloud: improve forecast accuracy with automated pipeline health assessments
  • SAP CPQ: improve close probability with discount recommendations

Design-to-operate process

  • SAP Integrated Business Planning: predict demand with intelligent demand assessment and automatically classify and categorize quotes with intelligent segmentation
  • SAP Predictive Asset Insights: Efficiently complete maintenance tasks with object part and damage code suggestions

Source-to-pay process

  • SAP Fieldglass Solutions: Finding external employees with intelligent resume screening
  • SAP Ariba solutions: Correctly classify invoices with automated data enrichment services

Recruit-to-Retire Process

  • SAP Fieldglass Solutions: Find the best candidates with intelligent resume screenin
  • SAP SuccessFactors solutions: Tailored training recommendations to improve training and talent development

Finance

  • SAP Cash Application: Automation of receivables reconciliation
  • Intercompany matching and reconciliation (ICMA): Simplify the financial close process by identifying and resolving discrepancies between intercompany transactions

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SAP Cloud ALM is a cloud-based offering from SAP that enables companies to implement and manage cloud solutions. Find out what it's all about here.

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What is SAP Datasphere?

Get a handle on your business-relevant data with SAP Datasphere. The SAP solution provides a central environment for the provision and analysis of data from SAP and non-SAP systems.

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Central Finance, Simple Finance or S/4HANA Finance?

SAP Central Finance, SAP Simple Finance or SAP S/4HANA Finance - the variety of terms can be confusing. We will shed light on this and tell you how the solutions diffe

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SAP Business One

SAP Business One is an ERP system for SMEs. It covers all important areas of a company and offers interesting additional functions. Learn more about the software on this page!

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SAP C4C (SAP Hybris Cloud for customer)

With the SAP C4C solution, companies are moving their CRM to the cloud. You can read in this article how the system presents itself in detail and which advantages it offers. Find out more now

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SAP Cloud Security: How secure is the SAP Cloud?

The security of data in the cloud is a topic that many companies view critically. Yet the standards for SAP cloud security are extremely high.

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SAP CRM

SAP CRM is a solution for the customer relationship management of companies. In our article we explain the functions for customer relationship management in detail.

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SAP Data Hub

With SAP Data Hub, companies bring together data from different sources and formats to extract valuable knowledge. On this page, we explain in detail what is behind the platform.

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SAP Data Services

SAP Data Services is the tool of the hour for the analysis, integration, transformation and quality management of data. Find out what it is all about and how it is used in practice.

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SAP ERP

On this page you can read which ERP systems are offered by SAP and for which core processes and company size they are suitable. You will also receive information about the deployment models.

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SAP EWM

Smooth processes in logistics are of great importance. Process optimization in the warehouse and in the supply chain is therefore on the agenda of numerous executives. SAP EWM can help.

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Highlights of SAP S/4HANA Public Cloud 2408 Release

SAP has published Release 2408 for SAP S/4HANA Cloud, Public Edition. Here you will find information on the most important new features.

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SAP S/4HANA Migration Cockpit

The SAP S/4HANA Migration Cockpit is a tool developed by SAP and successor to LSMW for data migration to SAP S/4HANA. It is currently the only tool for migration to the cloud.

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SAP S/4HANA Cloud 2208 Release Highlights

SAP has released 2208 for the SAP S/4HANA Cloud. This article provides an overview of some of the most important innovations.

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SAP S/4HANA 2020 Release

SAP has published the latest release for the on-premise version of SAP S/4HANA: the SAP S/4HANA 2020 Release. This release provides companies with new functions and innovations in all areas.

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What is SAP RE-FX?

Managing large stocks of real estate is complex. With RE-FX, SAP provides a solution for companies to simplify real estate management significantly.

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SAP S/4HANA Cloud, Public Edition

This SAP cloud solution is always equipped with the latest technologies and is ready for use very quickly.

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SAP Ariba - Solutions for Purchasing and Procurement

Digitize purchasing and procurement processes, from supplier selection to contract - with SAP Ariba. We provide an overview of the features, functions and benefits of the cloud-based B2B marketplace.

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SAP ABAP

ABAP is a proprietary programming language that was developed for programming applications in the SAP context. It is basically similar to the COBOL programming language

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The 6 biggest risks of an SAP transformation

Changing SAP systems involves many dangers and stumbling blocks. We've dealt with the six biggest threats. From carve-out to merge - the malice of your transformation scenario

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Reorganization of SAP Merchandise Group

Historically, product group structures have mostly grown strongly and urgently need to be optimized. What stumbling blocks are to be expected on the way to a successful reorganization of product groups?

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New SAP S/4HANA Cloud update cycle

SAP provides regular upgrades and updates for cloud customers. The delivery cycle has changed at the beginning of 2022.

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Machine Learning

Machine Learning is a technology from the field of artificial intelligence. Find out what is behind Machine Learning and how it is used in companies.

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Liquidity planning

Companies need reliable liquidity planning. In this way they avoid liquidity bottlenecks and insolvency. SAP Central Finance supports planning with real-time financial data.

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Liquidity ratios

Liquidity ratios are an indicator of whether a company can meet its payment obligations. Liquidity ratios 1-3 are used to measure short-term liquidity positions.

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Cost plan conversion in SAP

There are many reasons for a chart of accounts conversion. However, the conversion itself involves a number of dangers that need to be avoided. In the following article, we will show you how to do this.

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Joint Venture

A joint venture is when different companies cooperate as partners. In several cases it can be advantageous for companies to cooperate with other companies.

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IT architecture models

How can an IT architecture be rebuilt? What role do IT architecture models play? And which current trends are currently changing the view of IT architecture? You can find the answers here.

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Industry 4.0

Industry 4.0 refers to the digitalization of industrial production. On this page we deal comprehensively with the background. In addition, we explain what is changing for companies in detail.

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What is IFRS 15?

Since 2018, companies have to apply the international accounting standard IFRS 15. On this page you can find out everything about the background, content, effects and implementation.

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What is SAP Build?

Developing without code knowledge? SAP Build makes it possible. The solution can be used to build apps, automate processes and create corporate websites. Get to know SAP Build here.

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Digital Twin – Twin with added value

In the Digital Twin, the analogue and digital worlds merge. The virtual image of a real product collects data, enables simulations or allows improvements to be tested - without much effort.

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SAP Business Technology Platform

What is the SAP Business Technology Platform? Learn more about the solution here and find out what possibilities and advantages SAP BTP offers.

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Data Warehouse

A data warehouse enables companies to combine and analyze a wide variety of data. You will find everything worth knowing about data warehousing and corresponding systems on this page!

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SAP Basis - operation, structure and definition

SAP Basis is the foundation of every SAP system. On this page you can find out what is behind the term and what SAP Basis is responsible for in detail.

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SAP Authorization System under SAP S/4HANA

The introduction or conversion to SAP S/4HANA can be an opportunity to optimize your own SAP authorization system.

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SAP Best Practices: Definition, Meaning and Use

Those who use SAP Best Practices benefit several times over. The standards simplify and accelerate business processes and make companies more flexible. They also help with the changeover to SAP S/4HANA

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SAP BO explained in detail and understandably

SAP BO is a collection of products from numerous individual solutions, with which companies realize analysis and visualization of business management data. But what does this mean in concrete terms

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SAP BRF+ - Implement business rules easily in ABAP

With the SAP Business Rule Framework plus (SAP BRF+), complex business rules can be accommodated in SAP - and without specific IT know-how. Learn more about this approach here.

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SAP C/4HANA and CX - for sales, service, marketing

With SAP C/4HANA or SAP CX, companies manage their customer experience with the latest generation of tools. Find out here how this SAP product family is made up and what it does.

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SAP S/4HANA Cloud, Private Edition

The individual cloud solution for maximum data control

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What is LeanIX?

SAP LeanIX is a solution for the management of Enterprise Architecture (EA), the IT enterprise architecture. Find out here what you need to know about the functions, benefits and areas of application of LeanIX.

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What is the accounting SAP CO-PA?

Accounting-based SAP CO-PA is on the advance and is regarded as SAP's strategic solution. But is it really the market segment calculation of the future?

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What is a Buy Side Due Diligence?

If the buyer commissions the due diligence examination, this is referred to as a "buy-side due diligence".

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Corporate Finance

Corporate finance is embedded in every corporate strategy. Every activity must be financed, capital must be used optimally, the value of the company must be increased and risks must be averted.

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SAP Demo System: Experience S/4HANA live immediately

With the help of live demo systems, companies can experience SAP S/4HANA immediately - and thus, among other things, test and evaluate whether the SAP best practice standard is sufficient for their processes.

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What is Artificial Intelligence (AI)?

Artificial Intelligence is not new, but it has been getting new attention since end of 2022 with the introduction of ChatGPT. Read here what you need to know about AI.

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Adobe Forms for SAP

Adobe Forms for SAP lets you develop forms - a technology that surpasses its two predecessors, SAPscript and SmartForms.

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Asset Deal

Companies that buy companies have several options. One variant: the asset deal. What does the term mean? What are the advantages of this procedure? What are the practical implications?

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GROW with SAP

GROW with SAP is SAP's new offering for new customers and midsize companies to get started quickly and easily with SAP S/4HANA.

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Greenfield vs. Brownfield: the right strategy

There are different ways to SAP S/4HANA: Greenfield, Brownfield or even a selective migration. To find out where the differences lie and the advantages and disadvantages of the respective strategies, read here.

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12 questions about SAP S/4HANA Cloud

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M&A deals: opportunities and risks

New highs in M&A deals are being recorded, and the value of deals worldwide has also risen significantly recently. But why is that and what are M&A deals anyway?

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What is SAP SuccessFactors?

SAP SuccessFactors is an HR cloud solution. It supports companies in controlling and transforming their HR management processes. In this article, we provide an overview of the solution.

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ECC conversion by 2033: SAP Cloud Transition Option

New offering for SAP customers: In Q2 2025, SAP will introduce a "transition option" to support the move from SAP ECC to SAP Cloud by 2033 (instead of 2030).

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What is the SAP Business Data Cloud?

The SAP Business Data Cloud (BDC) is a fully managed SaaS solution for standardizing and managing SAP data. Read here what you need to know about BDC.

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What is SAP Business Suite in the cloud?

SAP has relaunched the name Business Suite - for all of the Group's cloud applications. Read here what you need to know about the new Business Suite.

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What is an e-invoice?

E-invoicing between domestic companies has been mandatory since January 1, 2025. Here you will find answers to the most important questions about electronic invoicing.

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What is SAP Document and Reporting Compliance?

SAP Document and Reporting Compliance (SAP DRC) is the SAP solution. Companies can use it to meet compliance requirements. Read here what you need to know about SAP DRC.

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ETL Process

The ETL process is one of the fundamental concepts in computer science. It enables the transformation of data from various sources into valuable knowledge. On this page, you will learn more about the details!

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19 questions about SAP S/4HANA

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What is SAP Credit Management?

SAP Credit Management is a software solution that helps companies to manage credit risk when dealing with customers. Get to know the solution here.

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What is SAP Cash Management?

SAP Cash Management helps companies to manage cash flows, liquidity planning and cash flow monitoring. Find out here what you need to know about this product.

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What is SAP Collections and Dispute Management?

Efficient receivables management and rapid dispute resolution: SAP Collections and Dispute Management automates processes, improves liquidity and strengthens customer relationships - integrated in SAP S/4HANA.

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What is SAP SCM?

SAP SCM is an independent product with various functions for supply chain management under SAP ECC. Read here what you need to know about SAP SCM.

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What is WalkMe?

With the help of the Digital Adoption Platform, users can get to know and use software more easily and companies can optimize applications. WalkMe has been part of SAP since 2024. Get to know the solution here.

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11 questions about SAP Central Finance

SAP Central Finance is an SAP platform for finance and controlling, reporting and consolidation. Read the answers to 11 key questions about Central Finance here.

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Central processes in SAP Central Finance

With SAP Central Finance, processes in Finance can be centralized. Find out here what these processes are and what advantages they have in detail.

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10 questions about RISE with SAP

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SAP and Brexit: What you need to consider now

Since January 1, 2021, the negotiated partnership agreement between the EU and the United Kingdom has provisionally applied. Many companies still have to make necessary adjustments now.

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Ethical principles already defined.

Ethical principles already defined.

Artificial Intelligence is accompanied by enormous societal changes and privacy challenges. SAP has already addressed these "downsides" of AI in depth as well.

For example, the software group has developed guidelines to guide the introduction and development of AI components. The overarching goal here is to "improve the operations of the global economy and the lives of people."

The principles include the following aspects:

  • Value-driven (respect for human rights and UN Guiding Principles).
  • Focus on people and user experience
  • Businesses acting without prejudice
  • Transparency and integrity
  • Quality and security
  • Data protection and privacy

In addition, SAP aims to address the societal challenges posed by AI. Aspects such as economic redistribution, economic development, social security and normative issues play a role here.

Ethical and moral issues in the field of artificial intelligence.

Ethical and moral issues in the field of artificial intelligence.

Several ethical dilemmas arise in the context of artificial intelligence.

  • For example, there is a critical need to question whether decisions made by autonomous machines may pose a threat to free will and the assumption of responsibility.
  • In addition, developers may imbue AI software with tendencies that lead, for example, to the exclusion of individuals or to discrimination. This circumstance is particularly problematic if these tendencies arise unintentionally in the context of machine learning.
  • Further, there is a risk that people can be identified, categorized, and evaluated through profiling algorithms based on their activities, preferences, opinions, or other information they share or generate online. This could put cultural and political pluralism at risk.
  • In addition, AI systems need vast amounts of data to meaningfully undergo learning processes. This includes personal data. Current data protection laws are in considerable conflict with this.
  • However, the large amount of information poses further challenges. For example, it is sometimes difficult to filter out correct and error-free information. If the database is not of undoubtedly high quality, software results and decisions cannot be trusted to a high degree.

AI & Accounting

Reduce accounting costs by up to 90 percent? Find out now about the offers from our partner Nooxit.

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Outlook: Where is the trend for Artificial Intelligence heading?

Outlook: Where is the trend for Artificial Intelligence heading?

Artificial Intelligence is undoubtedly a highly emotional topic. Extreme positions often dominate the discussion.

One camp sees AI as a threat to all of humanity, while the other often sees the technology as a panacea for all of our problems.

No one can yet judge whether one of these scenarios will come to pass. The fact is, however, that AI will become significantly more important in the coming years and decades. Experts agree that Artificial Intelligence is a key technology of the digital revolution.

For companies that want to make progress in terms of digitization, there is therefore hardly any way around using the possibilities of Artificial Intelligence for themselves and driving forward automation via AI. SAP already offers a wealth of opportunities for this.

  • It is very likely that employees will be relieved of routine activities by AI in the future. In particular, standard processes that are repeated with high frequency are the potential area of application.
  • However, machines will not only automate processes in the coming years. There is also enormous potential in the analysis of big data. In contrast to classic approaches, which are based purely on the evaluation of past values, AI enables a look into the future.
  • On this basis, precise decisions can be made and new business models and smart services (such as predictive maintenance of machines) can be realized.
  • The optimization of goods flows and logistics chains is another area of application in which AI is likely to become established.

And where does that leave humans? Will they soon be completely replaced in the working world by robots with Artificial Intelligence? Certain job profiles could indeed disappear as a result of AI, but at the same time new jobs will be created.

Human skills such as creativity and empathy could once again come to the fore. There will be freedom to concentrate on one's own strengths again and to develop innovations. This also has a positive effect on employee satisfaction.

The intuition factor will also continue to be in demand. Decisions will be based much more on data from intelligent analyses. However, if the decision-making scope is high, the human being will still have the last word for the time being.

Conclusion: Opportunity and risk at the same time

Conclusion: Opportunity and risk at the same time

There is an opportunity for AI to evolve positively and empower people to better solve the problems of modern society and achieve more.

There is a risk in allowing AI to act beyond the limits of meaningful control. For companies, such an approach would be unacceptable, and not just in terms of reputation and ethics.

Management would potentially delay or even stop innovation entirely if it failed. The degree of security and control in the use of Artificial Intelligence could therefore determine whether intelligent machines become a curse or a blessing for us.

Are you interested in our AI solutions for SAP? Then feel free to drop me a message!

Shape your future with us

Meinolf Schäfer

Senior Director Sales & Marketing

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