A roadmap for AI in midsize companies
In a world that is rapidly digitizing, medium-sized companies are faced with the challenge of keeping pace with technological developments. The key to success and ensuring competitiveness lies in digitizing, structuring and centralizing data. But how can companies that are lagging behind digitization manage this change? Artificial intelligence (AI) not only offers solutions to optimize existing processes, but also valuable support in achieving these digital milestones.
Where do we start?
The first step towards digital transformation is the transition from analog to digital data. This step is fundamental, as digital data forms the basis for all further digitization and automation processes. AI technologies, such as optical character recognition (OCR), can help companies accelerate this process by efficiently digitizing documents and thus laying the foundation for a digitally connected future.
How can structure be created in data chaos?
As soon as data is available in digital form, the next step is to structure and standardize it. Structured data is easier to analyze and use. McKinsey points out the comprehensive use and analysis of customer information leads to significant economic benefits. However, most companies only use a fraction of the data they own.
Although the data is often available digitally, it is hardly possible to use it due to the lack of structure. AI can play a central role here by helping to classify data, recognize patterns, and automatically organize information. This not only makes it easier to access and analyze data, but also creates the conditions for advanced AI applications. Of course, data protection and secrecy must be ensured, particularly during this step. But AI providers are also thinking about this. With ChatGPT, for example, since April 2024, users have been able to turn off long-term saving of their chat history. As a result, your own data is not used for AI training and does not remain on OpenAI servers in the long term.
The value of centralization
Centralizing data from various sources and systems provides a unified view of information and simplifies its management. Centralized data storage not only improves data quality and availability, but also opens up new opportunities for the use of AI. With access to comprehensive centralized data, companies can get a 360° view of their customers and create personalized customer experiences, develop more efficient operations, and make informed decisions. AI can also help analyze centralized data by providing insights that would be difficult to obtain manually.
Gartner found out that less than 10% of all companies have a 360° view of their customers and only 5% use this perspective to generate economic added value for their company. By using AI, the path to 360° customer management can be significantly shortened.
First steps and long-term vision
Getting started with AI doesn't have to be complex. Even simple AI tools can make significant improvements. The key is to start small, for example by automating repetitive tasks, and then gradually move on to more complex applications. In the long term, companies should develop a strategy that enables them to comprehensively integrate AI into their business processes in order to promote innovation and remain sustainable.
Digital transformation is a journey that requires planning, commitment, and willingness to adapt new technologies. AI enables medium-sized companies to catch up again in the race to a digitalized world. With the right strategies and tools, they can overcome the challenges of digitization and seize the countless opportunities that technology offers.
