Innovation & Progress: Top AI Trends for 2025

Agentic AI: Autonomous systems for efficiency and innovation

Agentic AI represents a new level of autonomy in artificial intelligence. This technology allows AI systems to independently plan, make decisions and solve complex tasks without the need for constant human intervention. The potential of these agents lies in their ability to take over repetitive tasks and decision-making processes, which enables significant efficiency gains, particularly in areas such as customer service, logistics and data analysis. Agentic AI can thus function as a “virtual colleague” that optimizes routine tasks and relieves the human workforce, allowing them to focus on more strategic activities.

For companies, this not only means increased productivity, but also improved decision quality, as agents have comprehensive data access and can respond more quickly to changes. This is a significant competitive advantage in markets that require rapid adjustments and precise analysis. At the same time, the implementation of robust governance policies is required to ensure that these systems always meet the company's objectives and ethical standards. Agentic AI could thus make a significant contribution to increasing value and ushering in a new era in business process automation that offers both flexibility and scalability.

Worldwide, Agentic AI is seen as a pioneer for autonomous systems that are increasingly able to make their own decisions and dynamically adapt to business objectives (source: Gartner, https://www.gartner.com/en/articles/top-technology-trends-2025).

Regulation of AI systems

With the AI Act coming into force in the EU in 2024, the requirements for AI applications have become even more stringent. This legal framework requires companies to be fully transparent regarding data usage, risk assessment and accountability for AI models. 2025 also brings new compliance requirements and the obligation to undergo regular audits to ensure that algorithms are designed to be transparent, secure and fair. In the US, the regulatory focus remains on data protection, antitrust law and the fight against algorithmic discrimination – particularly with regard to generative AI, which is increasingly the subject of scrutiny due to potential copyright issues and data protection risks (source: Foley & Lardner LLP, https://www.foley.com/insights/publications/2023/12/us-regulation-artificial-intelligence-2024).

Countries such as China and Japan have also adopted comprehensive regulations to establish ethical standards for AI and ensure the protection of personal data. These different approaches worldwide highlight the need for harmonization of AI regulations. The OECD is currently working on a framework to serve as a global standard to ensure international consistency and a level playing field. Companies in the DACH region are thus increasingly obliged to integrate international standards to make their AI systems globally trustworthy and competitive (source: Skadden Foundation, https://www.skadden.com/insights/publications/2023/12/2024-insights/other-regulatory-developments/ai-in-2024).

The balance between innovation and security is at the center of the discussion, as the responsible use of AI is increasingly seen as an economic and social success factor.

Download the free white paper on the European AI Act. In it, we provide companies with a concise explanation of the consequences and most important provisions of the first European AI legislation.

EU AI Act White Paper

ESG and energy-efficient computing

The importance of energy-efficient AI infrastructures is growing as companies worldwide increasingly embrace sustainable solutions. AI systems are known for their high energy consumption, especially when processing and storing large amounts of data. However, by using energy-efficient technologies such as optimized GPUs, neuromorphic chips and modular algorithms, companies can achieve significant CO₂ reductions. This not only benefits the company's balance sheet, but also meets the increasing ESG requirements that investors and regulators are increasingly demanding. By focusing on resource-efficient data centers and renewable energy to meet electricity needs, savings potential can be realized and environmental pollution reduced.

For companies in the DACH region, where environmental awareness already has a high priority, energy-efficient computing could represent a key competitive advantage. In addition to the ecological benefits, there is also the opportunity to realize significant long-term cost savings as new hardware and optimized algorithms reduce energy intensity and operating costs. In view of the increasing importance of sustainability initiatives, energy-efficient computing is expected to play a crucial role in corporate IT strategies for achieving ESG goals and meeting future sustainability requirements.

Generative AI: From disruption to competitive advantage

Advanced systems of AI-driven natural language generation and generative AI models, including the latest developments in multimodality, are revolutionizing the way content is created and interactions are designed. Technologies such as text-to-image, text-to-video, and image-to-text make it possible to generate complex, multimedia content that seamlessly integrates text, images, and video. These multimodal AI models have significant potential for maturation and performance improvement that can be used for advanced and effective communication across different media and platforms.

Generative AI models such as ChatGPT and Google Bard, trained on extensive amounts of data, offer improved capabilities in natural language processing and content creation. However, these models also encounter legal challenges, particularly in the area of copyright. As these technologies mature, the question of ethical use and copyright compliance will also become increasingly relevant. It is expected that the debate around the use of generative AI models will continue to develop and deepen, with the balance between creative freedom and the protection of intellectual property at its core.

In addition, the use of multimodal AI models is leading to increased integration of digital assistants into everyday life, driving demand for interactive and personalized services. Businesses that adopt these technologies can benefit from increased efficiency in their operations while creating innovative customer experiences. However, the challenge lies in managing the impact of these technologies on the workforce, as automated systems increasingly take on traditional job roles.

It is important that companies in the DACH region not only see these disruptive technologies as a tool for increasing efficiency, but also consider the ethical and societal implications. The ability to responsibly integrate these new technologies while developing innovative business models will be crucial to succeeding in an increasingly artificial intelligence-driven economy.

Learn more about generative AI, how it works and matters, and its ability to create and edit innovative content through large neural networks.

Generative AI – An Overview

Disinformation Security: Protection against digital manipulation

As disinformation is now being used specifically to manipulate and deceive, the importance of disinformation security is rapidly increasing. Companies are faced with the challenge of protecting their brand and internal information against deliberately disseminated misinformation and deepfakes. Disinformation security technologies offer specialized verification methods to verify the truthfulness of content and identify suspicious activity. Advanced authenticity verification algorithms can detect manipulated information and thus strengthen the security of communication channels. Companies that invest in such systems not only increase their resilience to digital threats, but also regain the trust of customers and stakeholders.

In particular, adaptive scoring systems and real-time AI-based analysis enable a preventive response to possible risks before they can develop into a reputational issue. Continuous monitoring of communication streams and social networks is necessary to respond to false information in a timely manner. This proactive security measure is becoming increasingly relevant as disinformation campaigns are carried out using ever more sophisticated methods.

Disinformation security is therefore becoming an essential component of a company's digital defense, protecting the integrity of their brand while promoting security across the entire digital ecosystem (source: Foley & Lardner LLP, https://www.foley.com/insights/publications/2023/12/us-regulation-artificial-intelligence-2024).

Quantum machine learning: new dimensions in data processing

Quantum machine learning (QML) is an innovative discipline that combines the principles of quantum computing with the methods of machine learning. While traditional machine learning is based on conventional computers, QML uses the unique properties of quantum computers, such as superposition and entanglement, to process data and recognize patterns. This enables QML models to perform complex calculations and data analysis at a speed and accuracy that cannot be achieved by conventional computers. The ability of quantum computers to consider multiple states simultaneously opens up new possibilities for data processing and machine learning, especially when processing large and complex data sets.

In the DACH region, which is characterized by an advanced research landscape and strong technological infrastructures, quantum machine learning holds enormous potential. The region is home to some of the world's leading research institutions and companies in the field of quantum technology and artificial intelligence, which provides an ideal basis for the development and application of QML. In particular, the use of QML could lead to significant advances in areas such as automation, data analysis and optimization of processes. In addition, QML offers the possibility of solving complex problems in areas such as logistics, energy management and pharmaceutical research more efficiently. The combination of strong academic institutions and a dynamic industrial landscape positions the DACH region as a leading player in the development and application of QML technologies. (Source: Fraunhofer Big Data and Artificial Intelligence Alliance, https://www.bigdata-ai.fraunhofer.de/en/publications/quantum-ml.htmlhttps://www.bigdata-ai.fraunhofer.de/en/publications/quantum-ml.html).

Outlook: AI in 2025 and beyond

The AI trends of 2025 illustrate the ongoing fusion of technology and society and open up a new spectrum of innovation opportunities for companies. Technologies such as Agentic AI and Quantum Machine Learning expand the capacities for data-based decisions and create more powerful autonomous systems. At the same time, disinformation security is becoming increasingly important as companies are having to do more and more to protect their brands and customer relationships from targeted manipulation.

While energy-efficient computing solutions help to reduce environmental impact, the ongoing regulation of AI also plays a central role in ensuring the ethical use of the technologies and minimizing legal risks. For companies, this means not only technical restructuring, but also the opportunity to position themselves as responsible pioneers that meet technological and societal expectations alike. To succeed in this, it will be crucial to remain flexible, to continuously educate oneself, and to actively shape the rapid development of these key technologies in order to successfully compete in an economy and society that is increasingly characterized by AI.