Industry

Artificial Intelligence

Driving the Digitalization Strategy

In our dynamic digital landscape, artificial intelligence (AI) has evolved from a visionary concept to an integral part of technological systems. Thanks to machine learning, AI technologies have grown significantly in recent years, becoming a crucial component in many digital solutions, such as trend analyses or search engines.

The synergy of advanced computing capabilities and the growing availability of data has exponentially accelerated AI research. The introduction of Large Language Models (LLM), like OpenAI’s ChatGPT at the end of 2022, marked a significant milestone in AI development.

For businesses, AI changes how data is processed and new data generated. In a corporate context, this influences three main areas:

  • Knowledge & Insights: AI analyzes vast data sets from various sources, synthesizing them into well-founded insights. This provides easy access to a broad spectrum of knowledge.
  • Productivity: AI streamlines repetitive tasks and simplifies extensive operational workflows. This promotes efficiency and enables a focus on more complex tasks.
  • Creativity: AI autonomously generates new ideas and content based on given information, thus expanding human capabilities for creativity.

For businesses, the question is: How can they leverage the opportunities AI offers in these areas?

€500 bn

The economic potential generated by AI in Germany by 2028 is estimated to reach up to €500 billion.

70%

Amidst global AI developments, 70% of the German middle class fear falling behind.

50%

Over 50% of German companies see a lack of personnel, data availability, and know-how as primary barriers to AI adoption.

Challenges

Integrating AI offers businesses promising potentials to deepen knowledge and insights, boost productivity, and enhance creativity. However, this integration is often non-trivial, requiring navigation through technical and organizational hurdles, including legal and ethical considerations.

Training and Development of Staff

The adoption of AI fundamentally changes how employees work, posing a challenge for many to familiarize themselves with AI for the first time. It is crucial to provide not only functional and technical knowledge but also actively manage change to address fears and uncertainties. This involves educating staff about the possibilities and limitations of AI solutions and offering them practical experience.

Technological Integration

Introducing AI may necessitate the evolution of existing IT infrastructure. It’s essential not only to find the right AI solution but also to ensure it integrates seamlessly into the current IT environment. Decisions regarding the choice of foundational models need to be made, weighing the options between proprietary models and open-source solutions. This can, in turn, impact the existing IT infrastructure.

Data Management

The effectiveness of AI systems heavily depends on the quality and quantity of data available to them. Thus, a robust data provisioning model that considers data protection and technical requirements is crucial. Especially for qualitative data, a comprehensive and structured repository for all proprietary information is often not yet in place.

Interpretability

AI solutions often resemble a black box, making their decision processes not fully comprehensible. LLMs can hallucinate and “dream” about content and contexts. To build trust in AI usage, companies must invest in AI solutions that are transparent and understandable. Employees also need clear guidelines for interpreting and verifying results.

Integrating AI raises legal and ethical questions. Companies must ensure that their AI solutions comply with regulatory requirements and uphold ethical standards. Regular compliance checks must be adapted to the changing risks to identify and address them.

Economic Evaluation

The decision for AI is not only technical but also economic. Initial investments can be significant. Therefore, it’s crucial to carefully assess the expected Return on Investment (ROI). As we are just at the beginning of the AI revolution and many use cases are still unclear, assumptions need to be made more frequently.

Opportunities Through Artificial Intelligence

AI is becoming a crucial factor in the business context, fundamentally transforming work processes, innovations, and customer interactions. AI technologies open diverse opportunities to optimize existing workflows and simultaneously venture into new, innovative paths in product design and services.

Access to Expertise

AI enables companies to efficiently analyze and link extensive data sets from various sources, considering both quantitative and qualitative information. This facilitates direct and interactive access to a broad knowledge spectrum, which can be made available to employees, for example, via chatbots.

Automation of Office Tasks

AI can automate traditional administrative tasks in businesses, previously performed manually. This includes tasks involving data capture, categorization, and processing. AI is capable of handling not only simple tasks but also complex ones requiring human-like interpretation, decision-making, and interaction, such as processing and reviewing insurance claims.

Expansion of Digital Customer Interfaces

AI can not only automate customer interfaces but also make them smarter. Unlike traditional chatbots, modern conversational AI can understand complex customer inquiries or respond to emotions. They can also independently initiate follow-up processes like sending offers or updating customer data, without the need for employee intervention in customer service.

Innovative AI-Driven Products and Services

Integrating AI into products and services opens new possibilities for businesses in product design. This includes enhancing core functionalities of products or developing new ones, like security systems in smart home applications that detect movements in real-time and analyze their risk.

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Partner

Chris Heeg

Contact us About Chris

Prior to joining DevelopX in 2021, Chris had already gained entrepreneurial experience as founder of a start-up in the mobile fitness space and worked as Commercial Lead at an established software engineering boutique. There, he oversaw the implementation and evolution of complex digital products. Prior to that, Chris spent most of his career in management consulting, supporting clients in large-scale transformation and restructuring programs.

Chris studied technical physics at the Technical University of Munich. As a partner at DevelopX, he implements large-scale software development projects across industries and consults as an expert on the use of new technologies such as web3 or AI. Chris has a passion for decentralization and digital art.