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What does Artificial Intelligence and Machine Learning mean for SAP BI?

22 Oct 2020

Artificial intelligence (AI) is now everywhere, according to an IDC report, the spending on AI systems will reach $97.9 billion in 2023, more than two and a half times the $37.5 billion that was spent in 2019. Gartner have also released findings, which suggest the use of AI and machine learning (ML) will transform analytics and business intelligence (BI) platforms in 2020[i]. AI has exploded on to the market, software and application vendors such SAP will need to adapt or be left behind.

What is AI and ML?

Throughout my career AI has always fascinated me, in recent years the technology has become more prominent, both in work and at home. This has encouraged me to develop my understanding of the field and the impact it is having on BI. Almost everyone will have some kind of interaction with a form of AI on a daily basis. Some common examples of this include:

  • Siri
  • Google Maps
  • Netflix
  • Social media (Facebook/Snapchat)

AI and ML are popularly used buzzwords right now, often used interchangeably. Yet, they are not quite the same thing. A simple way to put it is as follows:

Artificial Intelligence is an application in which a machine can perform human-like tasks.

Machine Learning is a system that has the ability to automatically learn and improve from experience, without being directly programmed. ML is one of the many concepts that is used to achieve AI.

What does AI/ML mean for Business Intelligence?

BI is the process of using software to transform raw data into actionable information to support an organisation’s decision-making process. How this has been achieved has developed over time, as seen in the visual below. We are approaching a new generation for analytics, and this breakthrough in BI will bring about the era of ‘Augmented Intelligence’. A report from the mention the name of the report Capgemini Research Institute found that organisations implementing AI are much more likely to achieve benefits that meet or exceed their expectations, specifically with regards to increasing revenue, optimising costs and reducing risk.

Evolution of Business Intelligence
Evolution of Business Intelligence
Source: Capgemini 

Impact of AI-Enabled Business Intelligence:

  1. Automation of tasks – AI can handle routine tasks freeing up analysts and consultants to be more productive with their time.
  2. Data Quality – reduction in the number of human errors with automated quality control. AI systems can operate with limited to no human intervention and thus can make decisions to auto correct mistakes and deal with issues.
  3. Self Service – business intelligence tool sets will reach new levels of self service, reducing the need for technical knowledge and offering simpler ways of interacting with data. Systems will be able to learn based on a user’s preferences and previous activities, offering a tailored service for each user. For example, when interacting with Siri, a user is able to use natural language to produce a query, making it easy to extract the information required.

AI technologies will make it more efficient to derive insights and make better decisions by improving the whole analytical process. Tools will suggest new ways of combing data which will uncover previously hidden insights. These emerging capabilities will make BI and data-driven decision-making more accessible than ever before. Natural language interfaces will make it simple for business users to gain insights at all levels of an organisation, regardless of their technical understanding.

How has SAP reacted to the evolution of AI-Enabled BI?

SAP have many product offerings which incorporate different AI concepts. One stands out to me as their answer to AI-Enabled BI, this tool is SAP Analytics Cloud (SAC). SAC has been designed to provide an all in one approach to analytics, incorporating functionality for all types of users in one product. By having both data preparation and analytics functions available in one product, users are able to work more efficiently, switching freely between data management and the creation of visualisations.

SAC AI Capabilities

SAC has many AI concepts incorporated into the tool, and people often get confused as SAP do not directly call these concepts ML or AI. Instead they have their own specific terms for different AI functionality which incorporates concepts such as ML and natural language processing. These are listed below along with the capabilities they each provide:


  • Automatic data cleansing.
  • Highlight potential errors.
  • Automatic classification of data.
  • Enhance data to gain deeper insights.

Smart Transformations

  • Automatically suggests smart transformations for data.
  • Provides recommendations for data preparation.
  • Foundation for enhanced visualisations.

Predictive Forecasting

  • Simple one click forecasting of future performance.
  • Automatic detection of risks and potential future trends

Augmented Analytics

  • Q&A data using natural language, generates best fit visualisation based on question asked.
  • As easy to use as a search engine.
  • Identifies key influencers and relationships in the data.
  • Uncover how business factors influence performance.

The short clip below discusses some of these key features and provides a quick glance at what SAC can offer:Please allow statistical cookies to see this Youtube embed

I believe implementing AI-enabled business intelligence will add significant strategic value to an organisation. It provides a vital competitive edge which will support business development and provide fast actionable insights. BI fuels business growth and leads to better informed decision making. SAP have developed SAC to take full advantage of AI, ensuring they keep pace with the new era of augmented Intelligence.

At Capgemini we recognise the growing demand for AI infused solutions, because of this Capgemini have created the AI Academy, a learning platform to ensure our consultants are equiped with the latest skills and capabilities to deliver cutting edge AI solutions. A big talking point in AI is ethics, creating a robust and trust worthy solution, for more information and some further reading I’d recommend the following blog AI and the Ethical Conundrum. To find out more about SAP BI and how it could benefit your organisation, please get it touch.

[i] Gartner state that “Data and analytics leaders should plan to adopt augmented analytics as platform capabilities mature.”