AI in the company: Opportunities and strategies 2025
Current developments in the field of artificial intelligence, such as investments, implementations and results, make it clear that this technology will become an integral part of every company, regardless of industry.
Results of the Economist Impact Report entitled "Unlocking Enterprise AI: Opportunities and Strategies" show a clear trend: 84 percent of companies in Germany already use generative AI in at least one area of application and 97 percent plan to develop user-defined models with utility value based on company data by 2027.
But just as certain as the success of the technology is the fact that it requires far more from business leaders than adopting the latest and greatest AI model. Staying ahead requires a holistic approach that incorporates data management, security, governance, culture and domain-specific expertise.
Modernizing data platforms and driving forward democratization
Most companies want to integrate generative AI models into their own data. To do this, they need to modernize their enterprise data platform, address the problem of fragmentation and go beyond the capabilities of a single large commercial model. The future lies in AI systems and agents that consist of multiple components and use individual models, each optimized for specific tasks. This approach enables greater accuracy, reduced costs, increased performance and security - critical factors when it comes to AI-powered enterprise applications.
A key driver for AI is democratization. Companies want to make data accessible to a wider range of employees and enable them to create and refine AI models that meet their daily business needs. Natural Language Processing (NLP) is also important here, as Citizen Data Scientists can ask questions in natural language and also receive answers in natural language. In this way, every employee within a company can interact with the model to ensure the broadest possible understanding among all employees. A result of the Economist Impact Report shows that 59 percent of German companies believe that NLP will be the primary, if not the only, way to deal with complex data sets in the future.
Balance between security and innovation
Security and governance are critical in the new AI landscape. Companies that implement AI solutions too quickly must ensure that sensitive data is protected and regulations are complied with. At the same time, implementation must not take too much time in order to remain competitive. Robust security and governance processes are crucial to enable innovation without being held back by excessive caution. According to the report, 40 percent of respondents feel that data and AI governance in their organization is inadequate. Half of data engineers state that governance takes up more time than anything else. Therefore, the introduction of consistent governance is key to unlocking AI in the organization.
Customized AI solutions as a competitive advantage
The future lies not only in AI models that are trained on data from the internet, but in real data intelligence. These are systems that understand and process a company's specific, often sensitive data sets. And this in an AI that understands the context of its own company. This approach relies on agent systems that use specialized models for specific tasks. This enables companies to develop solutions that are precisely tailored to their needs and use their own data as a competitive advantage.
Companies are looking for solutions like the Databricks Data Intelligence Platform that are tailored to their business needs. They prioritize data, centralize governance and provide efficient TCO at scale. The AI revolution is only just beginning, and one thing is certain: the companies that use their data effectively and build AI systems that are tailored to their individual needs will be the market leaders of tomorrow.
Source: www.databricks.com
