*2.2.2 Smart industry 4.0, IoT*

Manufacturing is living a very lively changing with the smart production systems Industry 4.0 is already a reality in many medium-to-large companies [52, 53]. Smart manufacturing, [54], represents integrated systems that respond in real-time to the demand of the factory, the supply network, and the customer. The Internet of Things (IoT) will assist companies in measuring their operational performance by implementing connected sensors to track most of their activity [55].

Suppliers and society: The evolution of the Internet of Things (IoT) coupled with AI to form intelligent cyber-physical systems will also bring new implications for our daily lives [56]. As artificial intelligence grows in its knowledge and intelligence, algorithms will be able to optimize people's daily lives in unimaginable ways. The most interesting phenomenon to study will concern the forms of integration between IoT and AI.

## *2.2.3 Artificial intelligence*

The impacts of AI-based digital innovation are reflected in multiple aspects of society [24]: economy (industry, services, transport, agriculture, etc.), work, energy, collective security (cyberattacks), information (fake news), social media (confusion and manipulation of public opinion), privacy, justice, weapons.

Robots are machines capable of handling complex series of actions that interact, communicate and provide services to an organization or customers [57, 58]. Many studies in the literature investigate the use of AI robots, especially in the context of

services, and their implications for society. There are emerging studies discussing hypotheses that, in the near future, the use of AI robots could become dysfunctional and cause mental disorders and other psychiatric problems in humans [57, 59]. Many researchers argue that the use of artificial intelligence robots can have a huge impact on society, not only because they will be more integrated into service meetings, but they can also put themselves and humans at risk, become able to perform tasks creatively (i.e. leave nothing to humans) and achieve the same level of intelligence as humans [57, 59].

The development of artificial intelligence (AI) and machine learning (ML) offers organizations the possibility of radical changes in products, services, innovation processes, business models, and in the very nature of business activities in industrial ecosystems: indeed, a growing number of studies have endorsed the value of incorporating AI and ML to develop products that effectively address the deepest and most complex customer needs and satisfaction [27, 60]. According to Ford [24] AI is a flexible resource capable of applying cognitive abilities to practically any problem, similar to electricity that can be activated with a simple switch: this new resource will be able to analyze data, make decisions, solve complex problems, and give test your creativity. What will be the future implications of AI? Is it to be understood as a specific innovation or as an extraordinarily scalable technology? Will AI be a resource capable of generating value for people, businesses, and institutions and how?

AI can influence several aspects of society: law and regulations, organizations, diagnostic medicine, industry manufacturing, transportation, marketing, social media, government, etc. [61]. The impact of AI on organizations brings together the impact of AI on different aspects and processes such as [62]: work [63], highlights the critical skills for employees in organizations that use AI and their contribution to solving problems, and stimulates curiosity to create new knowledge; Kolbjørnsrud, et al. analyzes the employee-machine relationships [64]; forecasting, [65]; manufacturing (AI contribution to customizing [66, 67] and to optimizing quality [68]; decision supports, [69]; risk management [70, 71]; problem-solving [72], marketing and social media [73, 74].

In terms of management, AI can be categorized broadly into two different applications within organizations: automation and augmentation [19, 75, 76]. Automation refers to machines taking over human tasks, whereas augmentation implies that humans work in close collaboration with machines to perform a particular task [77]. The scientific community is debating whether 'robots', through automation, will make human workers and certain skills redundant, or whether AI will primarily be assistants or collaborators doing basic jobs, such as data collection, systematization, analysis, and recommendations, thus increasing process performance and human capabilities and preparing people to make more informed decisions [78].

Loureiro [62] analyzes how AI can affect society as a whole in a broader sense, how it affects organizations, what types of systems have been used, and what methodologies are employed; they highlight that, among the different impacts that AI has, one of the major impacts of AI will be seen on governance. Empowering governance using AI-based algorithms poses major challenges to top management as they decide which areas to prioritize and to what extent of delegation. Mele et al. [61] explore how AI and other forms of cognitive technology can influence value co- creation: the authors find that choice architectures and nudges affect value co-creation by widening resource accessibility dynamically, extending engagement, and augmenting human actors' agency.

The implications of a hybrid working environment are humans and AI systems working together and changing how managers and owners need to act to ensure a

#### *Digital Innovation and Sustainable Development: Two Sides of the Same Coin DOI: http://dx.doi.org/10.5772/intechopen.112294*

healthy working balance between multiple different needs [79]. Today, companies are already using AI systems to help managers decide who to hire. A more distant future trend may arise from the use of brain-computer interfaces to enhance cognitive skills for both managers and employees.

What is becoming clear is that, based on its ability to process more ecosystem information, AI is enhancing some business and marketing processes; leading to the reconfiguration and shaping of existing ecosystems and the formation of new ones, through the integration and sharing of more data; and it's leading to more real-time interactions and the possibility of developing a more systemic market vision [62]. If the potential of AI is to be realized, organizations must understand, consider, and engage their customers and employees in the reshaping of the whole value co-creating process [30]. AI is now being applied within enterprises for customer selection, HR, risk assessment in banking and insurance, advertising, scheduling, and routing [79–81].

The analytical skills and expanded knowledge made available by big data and artificial intelligence allow organizations to be supported in all decision-making processes [23]. This point highlights how AI is linked to cultural and social contexts, far beyond just the business aspects. Viewed from a more macro (i.e. social) level, the implementation of AI raises profound ethical questions [82]. For example, Bostrom and Yudowsky have emphasized three important ethical considerations: transparency, accountability, and fairness [83].

As AI continues to develop, it shows the potential to disrupt also the job market and the broader economy on a possibly unprecedented scale. According to Iansiti and Lakhani [27], AI will affect almost every job function. Long before the advent of AI, there were fears that automation and robotization would make humans redundant, assuming that there is only a certain amount of work, and if it is automated then there is less for humans to do [84]. It was concluded that most jobs consist of tasks and routines that could be automated, thus automation could create more opportunities for humans to work more closely with upcoming technological advancements, providing more time to use human capabilities and innate human skills, as machines would take over more of the predictable activities of a normal work day [85]. Basically, everything that can be delegated to software is exposed to the risk of being automated. It can wipe out many jobs but also make products and services available to more people. Manual work, on the other hand, while being replicable, requires very expensive robots: this, paradoxically, could stimulate a potential re-evaluation of craftsmanship. Any job of a routine and predictable nature (i.e. any role where the worker is faced with similar problems) can be fully or partially automated. The greatest risk concerns low-level unskilled jobs, routine professional activities (such as accountants and lawyers), and intellectual work following standard procedures. There are many questions that the change generated by these technologies stimulates: will new non-automatable jobs be created in sufficient measure to absorb all those who have lost their routine jobs? Will workers have the skills and abilities and personal attributes necessary to transition effectively into these new roles?

People work increasingly under the control of algorithms that monitor or scan their activities, practically treating them like robots. Many new opportunities are located in the so-called gig economy where workers are not guaranteed anything in terms of wages and working hours: all this can increase inequalities and risk dehumanizing the living conditions for a growing part of our workforce [24]. A vibrant market economy depends on large numbers of consumers being able to buy products and services: if they have no jobs and therefore no income how will they create the demand needed to sustain continued economic growth? Just as a transition of employment from the primary sector to the industrial sector actually took place during the industrial revolution, one could hypothesize a similar transition in the occupational composition of the current labor market. However, at the moment it is difficult to hypothesize which new spaces in the labor market artificial intelligence will be able to create in order to develop replacement opportunities for more routine and standardized jobs.

Machine learning algorithms will be constantly working to figure out how to automate many of the work and repetitive tasks so almost all types of routine and predictable work will eventually vanish and this could make the challenge for the workers best suited to this type of job very difficult [30]. Just as human beings AI agents are influenced by their experience when developing their creative ideas. AI agents will have more power to learn from their human ancestors to develop new creative and innovative concepts that may be applied in the workplace. This can also contribute to the creation of smart workplaces as AI systems could assist in providing safer working conditions and convenience due to a better understanding of patterns of task fulfillment and creative processes. This opens the door to a concept of qualitative, not just quantitative, transition of work.

In the first round of AI impact on work, creative jobs are projected to be safe from AI replacement. In fact, some researchers argue that AI will always fail to recognize and use human creativity [86] and that a new type of Feeling Economy (based on emotions, empathy, and interpersonal relations) will drive job creation [30]. Actually, the threat does not only concern less educated workers but also clerical jobs focused on routine analysis, manipulation, extraction, or communication of information. The risk becomes greater as the automation of these roles does not require expensive machinery, a good software is enough.
