Summarizing AI

This video has been created using generative AI.

Artificial Intelligence (AI)

is a technology that equips machines with human-like capabilities such as problem-solving, visual perception, speech recognition, decision-making, and language translation, seen in everyday applications like AI assistants and facial recognition software.

Machine Learning (ML)

is a subset of AI that focuses on enabling computer systems to learn and improve from experience or data, incorporating elements from fields like computer science, statistics, and psychology.

Deep Learning

is a branch of Machine Learning that uses multi-layered neural networks to analyze complex data patterns, and it may employ different learning methods like supervised, unsupervised, and reinforcement learning depending upon the task and available data.

Generative AI (Gen AI)

is a form of deep learning which utilizes foundation models, like large language models, to create new content, including text, images, sound, and videos, based on the data they were trained on.

Foundation models

are AI systems that use self-supervised learning on vast data to perform a variety of tasks, such as writing documents or creating images. Their versatility and adaptability make them a significant advancement in AI, lowering the barriers to adoption.

Large language models (LLMs)

are a subcategory of foundation models that are used for text and computer code.

Generative AI technology has seen rapid adoption. This adoption is driven by the fact that generative AI only requires natural language skills, has become widely available, and is easy for everyone to use.

SAP's customers are also adopting AI, including generative AI solutions in their business at a rapid rate. According to McKinsey:

• 33% of organizations are using generative AI regularly in at least one business function.

• 40% of organizations will increase investment in AI because of generative AI.

• 60% of organizations employing AI are already using generative AI.

According to Morgan Stanley, generative AI is expected to add up to $4.1 trillion of economic impact to the global economy in the next three years - this almost equals the gross domestic product of the German economy.

Assuming software vendors and tech companies take 20% of the value created in the form of revenue, this economic impact results in an addressable market of $820 billion for global software in the next 3 years.

However, we know enterprise customers take time to adopt new technology.​ Morgan Stanley assumes that around 20% of the addressable market will adopt and realize value in the next ​3 years.​ This is $150 billion in additional generative AI software spend globally, which is on top of traditional enterprise software.​

With these capabilities and market potential, AI provides a huge opportunity for companies and society. However, the technology also comes with risks that need to be mitigated to achieve relevant, reliable, and responsible outcomes. Therefore, what does that mean for SAP and our customers?

This video has been created using generative AI.