Into the future with machine learning and artificial intelligence

Future technologies such as machine learning (ML) and artificial intelligence (AI) are becoming increasingly popular in Germany. In the current survey “Machine Learning 2021” by IDG Research Services, two-thirds of the companies surveyed stated that they already use machine learning or are in the process of implementing corresponding solutions. The proportion of companies that are completely ignoring the topics of machine learning and artificial intelligence has fallen from 11% to 8% compared to the previous year.

Higher budgets and more projects in the Corona crisis

Innovative technologies are also gaining in importance from a strategic perspective. Around 86% of companies – from large enterprises to upper midmarket and smaller companies – now have a dedicated budget for projects related to machine learning or artificial intelligence. Since the outbreak of the Covid 19 pandemic, about 20% of companies have greatly increased their spending in this area, and the number of projects has increased by 18%.

Rapid results in terms of productivity and efficiency

Part of what makes ML and AI projects so popular is the quick results and high success rate they can achieve. For example, more than 60% report measurable added value after three months at the latest. The most frequent results of such projects are increases in productivity and efficiency as well as cost reductions. A higher degree of innovation and new products and services as effects of machine learning and artificial intelligence are more important for large companies. 40% of them associate ML and AI projects with the primary expectation that their innovative strength will increase. Smaller and medium-sized companies place less value on this.

Success is not guaranteed – but likely

But machine learning and artificial intelligence are not automatic guarantees of success. 10% of the companies surveyed as part of the study have canceled existing budgets for ML and AI again because the realized projects had not brought the desired effects.

However, this case is rather the exception. 63% of the companies have developed business models in which new products are created with the help of ML and AI. Overall, more and more companies are recognizing that they need to increase their reaction speed and agility in times of digitalization in order to continue to be successful. Machine learning and artificial intelligence are making an important contribution to this.

Common examples are automation in the processing of transactions, for example damage reports, and the development of self-service offerings for customers with the help of chatbots. In the area of IT, machine learning algorithms are able to detect cyber attacks at an early stage and automatically initiate countermeasures. AI and ML solutions are also increasingly being used in production environments – in quality assurance, research & development, and logistics.

Skills shortage and other challenges

In practice, companies are struggling with a shortage of experts in ML and AI. 37% state that projects are delayed or cannot be started at all because the right specialists cannot be found on the labor market. One way to address this bottleneck is to build up expertise in machine learning and artificial intelligence among their own employees. In IT departments in particular, the need for further training is correspondingly high (50%).

Another challenge that can be derived from the study is the lack of acceptance of future technologies among employees. Many see them as a threat to their own jobs. Here, it is the task of management to make it clear that ML and AI serve to strengthen the competitiveness of the employer. When introducing machine learning and artificial intelligence, companies should therefore not only keep an eye on the technological component, but also on the human component. Only then will ML and AI projects be successful.