Modern technology is developing at an exponential rate. The economy is becoming increasingly advanced and efficient, driven in part by the growing popularity of robotization and artificial-intelligence solutions. There are many signs that the future predicted by futurists has already arrived—and that further development may be even faster. The technological leap between 2022 and 2023
Several principal factors drove the rapid technological leap across different sectors of the economy between 2022 and 2023. Developments in machine learning, artificial intelligence, and sensor-assisted robotics make it possible to create intelligent systems capable of increasingly complex tasks. This can be seen in the economy as a whole and in more specific areas such as
RPA trends, including the growth of hyperautomation and the expanding role of robots in the workplace. Labor costs continue to rise in many countries, encouraging businesses to seek alternatives. Both higher costs and faster robotization are consequences of the COVID-19 pandemic. The pandemic forced behavioral change, stimulating technological development in healthcare, manufacturing, banking, and other sectors. Introducing workplace robots increased product and service quality and improved overall efficiency because robots can operate almost continuously. Artificial intelligence developed rapidly during the several months between 2022 and 2023. The widespread adoption of language models such as OpenAI’s ChatGPT completely reshaped many industries. The development of the metaverse, particularly Facebook’s version, has likewise brought digital and physical experiences closer together, contributing, among other things, to improved productivity. These and other technology trends are confirmed by a
Deloitte report. It highlights, for example, the growing flexibility and scalability of technology, visible in multicloud development and decentralized architectures. This increases interest in hyperautomation and autonomous systems of various kinds, including
RPA.
The growing popularity of AI-based solutions
Technological progress is driving the popularity of artificial intelligence. Companies that use AI systems—in industry, retail, or education, for example—can improve efficiency and the quality of products and services while adapting to contemporary trends. As these solutions become more advanced and scalable, their popularity can be expected to continue growing. However, wider AI adoption may create challenges that adversely affect the future of robotization. Demand will increase for specialists who develop and maintain AI systems, which may require companies to expand their Talent Networks. Ethical issues connected with the use of AI will also require solutions. Implementing advanced and often autonomous technologies may, for example, reduce the number of jobs. This can create social problems, so companies adopting such solutions must prepare their employees. They need to analyze possible benefits and risks, provide training in the use of new technologies and management of their social impact, and deploy appropriate security tools and protocols.
The need for large businesses to cut costs
One of the main reasons for the growing popularity of robotization is the need for large businesses to reduce costs. This may accelerate its development because automating business processes and assigning some duties to robots can deliver substantial savings. Cost cutting can also have a negative effect, however. Companies may seek increasingly inexpensive solutions, which could intensify competition in the robotics market but also inhibit technological progress. Development frequently requires major financial expenditure that may not always produce an adequate return on investment. Cost reduction can therefore stimulate investment in robotization, but only after a careful analysis of potential benefits and costs. It is also important to recognize that automation does more than reduce expenditure. It can improve task quality, increase productivity, and minimize errors. One example is the implementation of
scalable RPA at Danone. It enabled 70 company employees to learn how to build robots independently, increasing work efficiency.
Other factors affecting the future of robotization
New developments in robotics and artificial intelligence enable increasingly advanced robots to be built. They can perform progressively more complex tasks almost continuously, which is crucial to achieving a business advantage. Using
RPA in data analysis, for example, supports faster and more efficient decisions based on reliable data and may help transform a company into a data-driven organization. Numerous factors can nevertheless influence the future of robotization in different ways. Manufacturing-process automation increases efficiency and competitiveness, but it can also affect society: the development of robotization may change employment models and the labor market and may require changes to business models.
Environmental issues and the future of robotization
The future of robotization involves pursuing ever greater efficiency, but environmental issues may shape that future. Technological development must comply with increasingly stringent environmental requirements, which may affect financial costs. Robots can reduce the environmental impact of production by minimizing waste and raw-material consumption. Data-storage media illustrate this trend: less material is required to manufacture them while their capacity increases, enabling increasingly advanced operations. Nevertheless, robots and the infrastructure that powers them require considerable energy and resources. Components are produced from rare-earth metals, whose extraction significantly interferes with the natural environment and consumes enormous amounts of water and energy. Operation itself may also affect the environment adversely. In summary, the future of robotization depends largely on society’s response to change and requires social, ethical, and economic considerations to be taken into account. Robotization is unlikely to be stopped; the open question is whether it will culminate in a technological singularity.
