Making the right decisions thanks to artificial intelligence quickly and efficiently – not rarely, this hope is fed by the despair that decisions are becoming increasingly difficult to make in ever more complex structures: Most managers at some point have learned to take risks only if they can be calculated. And that’s where AI can help: It can defuse the problem of over-information if used correctly.
Clarify what AI is about
The key to using AI successfully within a company is developing a clear understanding of what AI is. It is more than mere data processing and system network. AI uses a database of knowledge to
- recognize and extrapolate patterns (perception) and
- draw new logical conclusions (comprehension and learning).
The recent success and exponential developments in the field of AI are primarily attributable to three main factors factors:
- Deep learning. Inspired by the way the human nervous system works, artificial neural networks (ANNs) connect simple computations with each other in multiple layers. An ANN learns by adjusting the weighting of the connections between neurons, forming new neurons and deleting old ones, or changing functions within neurons. The sharp rise in computing power, combined with the dramatic increase in the quantity of data, has allowed neural networks to grow more and more powerful.
- Big data. More than ever before, we have access to data that we can process with mechanical means. The universal acceptance of the Internet and social media, the rise of cloud computing and the increase in digital communication (e-mails, online forms, digital publications) all have created a flood of data that can be tapped into to derive knowledge. The volume of data doubles every two years. Right now, AI is the only tool for understanding the overwhelming volume of data.
- Performance of AI algorithms: Further advancements in computing power and the virtually unlimited ability to store data in the cloud are also associated with a wide range of tools that can offer help when it comes to automating software creation and developing ideas. Developing AI solutions is becoming increasingly simple, resilient, and cost-effective.
OpenAI’s ChatGPT, Google’s Bard or Meta’s Llama – the best known and most recent generative AI models – exemplify the synergy of the above elements, demonstrating how extensive training on diverse datasets has led to human-like text generation. This showcases the remarkable progress made in natural language understanding and generation within contemporary AI.
There is no way around AI – even in my company?
With an average share of around 30% of the total effort, business processes play a decisive role in the success of a company. This is where the clever use of AI can have its full effect. By implementing AI solutions for data entry, document management, email handling, and invoice processing, companies can achieve significant cost savings, increased accuracy, and improved customer and supplier relationships. By freeing up human resources for more strategic tasks, companies may be better able to respond to skills shortages. The specific areas for AI automation of business processes depend on the needs of the business and the available AI technologies.
Think big – or someone else will
Improving individual areas through AI helps many companies become more efficient and powerful. It is not so much about replacing jobs with robots using AI technology, but about rethinking entire processes. The logic of Google’s search engine is not based on mapping how we humans search for information by browsing knowledge bases and books, but it has developed its own intelligent algorithm to provide the result we are looking for. With this in mind, we should examine the value creation process in our companies, become more aware of customer expectations and goals, and then consider all the possibilities of AI in systems and processes.
Implementing business transformation in the corporate culture
How are established workflows to be adapted to the special requirements of new technologies? A reassessment of work processes often entails changed roles and responsibilities – new ways of working trigger a cultural change in the company. It is therefore essential to accompany and moderate this change. Only in this way the integration of AI-driven processes can be sustainably anchored in a company.
This example shows you how we transformed a business process.
