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Artificial Intelligence

Competitive, customer-focused and agile with AI in data management

Excellent data management combined with artificial intelligence is an unbeatable team. AI helps to process and analyze large amounts of data. To be able to decide where the biggest potentials for promising artificial intelligence applications are in a value chain, you need to understand and evaluate them.

Find out how here, when and why data analytics should be upgraded with artificial intelligence.

To use data better and more intensively and to introduce data-driven decision-making processes is a goal of many companies. With the help of AI applications, new products and services as well as data-based business models are already emerging today.

Experts from McKinsey forecast that the EU could increase its economic output by 19 percentage points by 2030 through a consistent focus on artificial intelligence – without any negative impact on the job market.

Intelligent systems support more efficient production processes, reduce energy consumption in systems, predict malfunctions or arrange day-to-day business in a more resource-efficient way. In the Digitalization Index for SMEs 2020/21, 31 percent of the companies surveyed said they expected disruptive changes (triggered by AI) in their industry. 77 percent would like to improve their service and product quality with the use of corresponding algorithms and thus strengthen their competitiveness.

What is Artificial Intelligence?

Artificial intelligence (AI for short) is a key technology and crucial for the success of companies – regardless of the industry. Human learning and thinking is adapted to mimic these skills and behaviors in an efficient and scalable way.

For example, insights can be quickly derived from data that is no longer comprehensible to a human due to its complexity or quantity. Decisions that were previously made on the basis of "gut instinct" under time pressure can be supported with data and facts or even made completely autonomously in this way.

Good to know: By 2025, the German government expects more than one-third of a company's value creation to be done by algorithms based on artificial intelligence.

Artificial intelligence is basically divided into two levels

Weak artificial intelligence

Weak artificial intelligence refers to systems that have developed extraordinary capabilities in a limited area, but are unable to evolve beyond that (e.g., Digital Assistants, Automated Data Analysis for Process Optimization, Alexa and Siri, etc.).

Strong artificial intelligence

Strong artificial intelligence refers to systems that have human characteristics in many aspects. In terms of independently recognizing problems, learning new skills or transferring what has already been learned to new circumstances.

While weak artificial intelligence has made major progress in recent years (complex issues such as customer traffic in stores can be accurately predicted by Google), strong artificial intelligence is still a long way off. Although there is agreement among most experts that strong AI is possible, it is more likely to be realized in the next few decades than in the next few years.

Why Is Artificial Intelligence Needed?

Artificial intelligence and machine learning are playing an increasingly important role in companies. There are many possible ways in which they can be used. They offer increased productivity and efficiency as well as new business values. The best-known example are chatbots in customer service, which act as virtual employees and enable 24/7 processing of customer inquiries.

In companies today, artificial intelligence is primarily used when repetitive tasks (i.e., recurring, rule-based activities) need to be automated. Accelerating data analyses with complex decision-making processes is also part of this.

AI can support companies in a wide range of strategic objectives and contribute significantly to the achievement of these goals:

  • Increasing revenue and business growth
  • Increasing cost efficiency
  • Improving market positioning
  • Developing and implementing innovative business models
  • Improving decision-making (in terms of quality, efficiency and innovation)
  • Increasing customer satisfaction
  • Improving working conditions and work performance
  • Increasing the productivity of employees
  • Reducing empty times, rejects and downtimes

According to IDC, 94 percent of the surveyed companies are convinced that artificial intelligence offers a significant competitive advantage. The decisive factor here is deriving the right use cases.

Before you introduce AI, you first need to be clear about the specific business case you want to use it for and what you hope to gain from it. First, identify a central area that artificial intelligence can sustainably optimize and thus contribute to the company's success.

The use of AI solutions lends itself to all areas such as marketing, sales, logistics, customer service, etc. Learn more about the possible uses of AI – with exciting application examples, we show you what artificial intelligence can already do in everyday business.

How Artificial Intelligence Is Changing the World of Work

The widespread use of artificial intelligence in companies has now established itself as a global trend. On the one hand, companies are constantly exposed to high cost and competitive pressure. On the other hand, the processing power of computers is faster than ever before and vast amounts of data are now available.

Once the prerequisites for artificial intelligence have been created in the company, significant potentials arise for the implementation of strategic goals:

Fact-based decisions

Intelligent analyses of large amounts of data enable the generation of accurate forecasts and the derivation of valuable decisions

  • Quality, efficiency and innovative power of decisions increase
Efficient end-to-end processes

Intelligent analytics improve resource utilization and asset effectiveness and make useful predictions about maintenance requirements

  • Cost efficiency increases
  • Blank times, rejects and downtimes decrease
Excellent Customer Experience

Intelligent analytics enable a comprehensive 360-degree customer view, outstanding 24/7 interaction and hyper-personalization

  • Customer satisfaction and sales increase, company growth benefits
Profitable business ideas

Intelligent analyses quickly and efficiently uncover market gaps and identify outstanding services or products

  • Development and implementation of innovative business models are accelerated, positioning in new markets is advanced
Productive working

Intelligent analyses and smart process automation take over routine, recurring work activities.

  • Working conditions and work performance of employees are improved; employee productivity increases

If companies actively deal with the use of artificial intelligence, it quickly becomes clear how complex the influencing factors can be and how significantly different business processes are affected across departments.

It is important to first identify and prioritize the overarching business goals in order to achieve the maximum benefit from the use of artificial intelligence in the company. Only then measures can be derived in a target-oriented manner and the use of AI can be driven forward with suitable tools, optimized processes and expert advice.

How Is Artificial Intelligence Being Used?

AI applications can do much more than efficiently evaluate large amounts of data. Artificial Intelligence offers companies the opportunity to automate processes and thus save costs and work more efficiently.

Application Areas of Artificial Intelligence
Fields of application of artificial intelligence (Source: Arthur D. Little, eco e. V.)

There is (to say the least) still potential for catching up and improving in terms of the design and implementation of AI scenarios in companies. This field has changed a lot in recent years and has developed rapidly.

Artificial intelligence has the potential to fundamentally change our working world. These three fields of application have already found extensive use:

Digital language and text processing (Natural Language Processing)

Natural Language Processing is used to automatically understand the content and context of texts and speech or to generate them

e.g. chatbots, text processing, text mining and voice assistants

Robotics and autonomous systems

Artificial Intelligence provides the key technology to enable autonomous machines to act on their own, solve complex tasks, and respond to unpredictable events

e.g. vehicles, machines, devices or software systems

Pattern recognition in large data sets

AI analyses are used to identify patterns in events that occur significantly often or rarely together or sequentially in the data

e.g. Predictive Maintenance, Shopping cart analysis, fraud or manipulative behavior, healthcare diagnostic systems

AI Use Cases in Companies

Artificial intelligence offers companies the opportunity to automate repetitive tasks, comprehensively analyze large volumes of data, make forecasts and predictions, recognize patterns in data and information, and derive recommendations for action. This does not require turning the entire corporate structure upside down. Small adjustments are often enough. And a slight increase in productivity can already mean a huge payoff.

The specific use cases of artificial intelligence in companies are diverse:

Artificial Intelligence Use Cases in Practice

AI is changing processes across all industries and areas of responsibility. AI use cases are possible along the entire value chain in companies:

  • Automation of quality control
  • AI-based route planning
  • Optimized warehouse utilization
  • Defect or anomaly detection
  • Automation of quality control
  • AI-based assistants (e.g. data glasses) for employees
  • Further development of smart products for new business models
Supply chain
  • Optimization of the supply chain
  • Intelligent sales forecasting
Purchasing and procurement
  • Automated warehousing through autonomous vehicles
  • AI-based processing from order transaction to delivery
Service and customer management
  • Automated customer review analyses
  • Intelligent customer interaction (automated CRM)
Research and development
  • AI-based simulation of product behavior
  • Analyses for product development
  • Automation of market analyses
  • Personalized customer interaction
  • Dynamic optimization of the product portfolio
  • Digital assistants in the sales process
  • Real-time market analysis
  • Support of presentation and sales process

Artificial Intelligence and Data Management – The Importance of Fundamental Data for the Implementation and Operation of AI

In the past, only transactional data was collected, such as the sales value of a purchase, a customer's complaint, sales figures for a product group. Nowadays, movement and behavioral data is also collected: the click behavior of users on websites, the geographical position of users during the ordering process, the time of day at which a user seeks interaction or the voice pitch with which a voice assistant is addressed.

Huge amounts of new data are generated and stored by companies every day. In our increasingly digitalized world, it has become a considerable success factor for companies.

The requirement: excellent data analytics – whoever analyzes data in a targeted manner, derives important insights and exploits potential, wins.

Artificial Intelligence Needs Data

According to the IDC study "Data Age 2025", the global volume of data will continue to grow significantly. By 2025, the analysts expect exponential growth to a data volume of 175 zettabytes.

It is also predicted that 2/3 of this data volume will originate from enterprises in 2025. A foundation for successful AI applications would thus be created, as these are based on machine learning processes that require large amounts of data. The challenge is to keep the data in the necessary quality.

Economic success of AI projects is inseparably linked to high data quality. For this reason, comprehensive data management with a strategic focus belongs on the business agenda of every company.

Data must be properly collected and ideally prepared in order to generate correct and meaningful analyses and to derive useful forecasts. This is the only way for companies to exploit the hidden potential of data as a raw material.

Modern master data management (MDM) solutions, customer data platforms (CDP) and product information management systems (PIM), are a major asset. These modern systems for data management create the basis for making a large volume of master and transaction data as well as Big Data accessible for AI analysis.

Machine learning methods support data management. However, data management is also the precondition for machine learning. An AI system can only be as intelligent as the data it is based on. Bad data = bad results. This is a challenge that many companies still have to face.

Link Tipp:

In projects with Artificial Intelligence, an average of 80% of the processing time is invested in the collection and aggregation of data. This proportion can be significantly reduced by appropriate data management. Tackle your data strategy now. Our whitepaper shows you the ideal roadmap for planning, implementing and ongoing management.

Master Data Management

Invisible Challenges, Visible Solutions. Better Prepared in 7 Steps

Artificial Intelligence Needs Rules

Anyone who uses a technology such as Artificial Intelligence in a company bears responsibility. In the interaction of strategic data management and AI-supported data analysis, large volumes of data can be processed quickly and effectively, and data science can be used to its full potential.

However, collected data is subject to strict legal regulations, for example to protect the interests of a natural person. Data must not be processed randomly. Data governance introduced throughout the company protects against legal risks. The data governance strategy defines guidelines, responsibilities, and standards for data-related processes – also for the use of AI.

For trustworthy Artificial Intelligence solutions, it is important to regulate the accompanying processes consistently. This enables companies to achieve the best possible quality, performance, data security and user acceptance.

A powerful team: Big Data, Data Management, Data Governance, Artificial Intelligence

Forms of Artificial Intelligence – Three Terms Explained

Forms of Artificial Intelligence – Three Terms Explained

Frequently Asked Questions About Artificial Intelligence

Do you have plans for AI in your business?

Build your competitive advantage with AI-based business processes. Use Artificial Intelligence to leverage the potential of your data faster and more extensively. We will be happy to consult you.
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