Five prerequisites for optimizing the use of AI

Perceptions of AI vary widely. While some see it as a threat, others emphasize the associated benefits. The fact is that AI, when used successfully, brings immense benefits to most companies: it increases efficiency and quality in production; it allows banks and insurance companies to offer their customers perfectly tailored services; it enables chatbots to interactively inform callers about products; and in general, AI can analyze and process data from a wide variety of sources in such a way that it serves as an important basis for business decisions.

However, AI-based applications must be optimally developed and implemented for this. Squirro describes the most important prerequisites for this.

1. use large amounts of data

For the performance of the AI technologies used, such as predictive analytics, machine and deep learning, it is crucial that the algorithms used "learn" from the largest possible amount of data and thus deliver better results in the form of meaningful analyses and recommendations for action. High speed and reliability of the analysis are crucial so that companies can use them as a basis for their decisions, which are often necessary at short notice.

2. make unstructured data accessible

Structured data accounts for only around five percent of all available data; the vast majority is unstructured. This means that companies only use a minimal proportion of their available data capital as a basis for business decisions. Unlike previous tools, AI solutions are also able to analyze data from any source - structured as well as unstructured. Companies must ensure that they are used to analyze both types of data. This takes AI solutions to a whole new level of action recommendations, which immediately improves the quality of business decisions.

3. ensure transparent algorithms

The use of AI technologies is a step into the unknown, at least initially. Due to the large number of parameters and technical processes involved in evaluating and processing data, it can be difficult for companies to understand how AI software has arrived at a result. Transparency of the algorithms is therefore important for user acceptance, regardless of whether they are employees or customers: How and why did the AI solution arrive at the suggestion? In some sectors, such as banking and insurance, transparency is even mandatory for compliance reasons.

4. better qualify developers for AI

Since the beginning of computer history, the principle has been that applications only perform the tasks that have been programmed by developers. This does not change for AI solutions either. This is why the experience, expertise and creativity of developers are crucial to the quality and performance of AI solutions. In addition to the use of AI-based software development assistants, good training and continuous further training of developers is therefore essential: in machine learning, deep learning and natural language processing. This is the only way to create optimal AI solutions.

5. combine artificial intelligence with human intelligence

Current AI technology can process very large amounts of data in a very short space of time and analyze it with regard to patterns and trends. Automated AI tools such as bots and robots are therefore indispensable in many areas, but they only unlock part of the potential. This is only possible with augmented intelligence. This "augmented intelligence" combines the results of automatically working algorithms with the experience and intuition of human experts: in fact, it is not enough for decision-makers to adopt the recommendations of an AI solution 1:1. They can only realize the enormous potential if they augment artificial intelligence with their own cognitive abilities.

"Faster computers and larger amounts of data provide an ever better basis for the use of AI solutions. However, they can only unfold their true potential if they are used optimally," says Dorian Selz, CEO and co-founder of Squirro. "Analyzing even unstructured data, transparent algorithms and, last but not least, highly qualified developers are prerequisites for this. But it is the combination of artificial and human intelligence that massively improves the quality of business decisions."

About Squirro

Squirro offers augmented intelligence solutions. The technology combines artificial intelligence, machine learning and predictive analytics, enabling companies to transform their data into AI-driven insights. Squirro was founded in 2012 and currently has offices in Zurich, London, Munich, New York, San Francisco and Singapore.