Intelligent automation or hyperautomation can be defined as “computer-based intelligent programs enabling the automation of knowledge work”. (Bornet, Barkin, & Wirtz, 2020) It includes Robotic Process Automation, AI, Business Process Management (BPM), and cloud, digital platforms.
Essentially, these are all innovations. And there are two big models when it comes to adoption of innovations. The first is the model the model developed by Venkatesh and his colleagues. The second model is developed by Rogers. Let’s discuss them.
Both are empirically tested. Both are focused on human behaviour and change management. We will try to combine them in a new model. In the next table you find the variables in both models.
Unified Theory of Acceptance and use of technology (Venkatesh et al., 2003) | Diffusion of Innovation (Rogers, 2005) |
Performance expectancy | Perceived attributes of the innovation |
Effort expectancy | Communication channel |
Social influence | Nature of the social system |
Facilitating conditions | |
Venkatesh and his colleagues use concepts like perceived usefulness, extrinsic motivation, job-fit, relative advantage and outcome expectations to define performance expectancy. Effort expectancy was defined by perceived ease of use, complexity, and ease of use. Social influence is based on concepts like image, subjective norm and social factors. Social factors refers to how much other individuals in the “social system” are using or supporting the technology. Facilitating conditions incorporated concepts like perceived behavioral control, compatibility and objective facilitating factors in the environement.
Rogers argues that nature of the innovation, communication channels and presence of a social system are key factors when it comes to the diffusion of innovations. Relative advantage, trialability, compatibility, observability, and complexity are used to explain the perceived attributes of the innovation, in our case intelligent automation. When it comes to communication channels, mass media or interpersonal are key channels. Also the communication process has five stages: knowledge, persuasion, decision, implementation, and confirmation. The social system is explained by concepts like communication structure, norms, roles likes change agents and opinion leaders, and type of decision, which can be voluntary, consensus or mandated. Success of opinion leaders and change agents is explained by the effort to contact clients, orientation towards the client, client needs matching the technology, and the change agent having emphaty, credibility and homophily or perceived sameness. Rogers also identifies previous experience, felt need/problems, innovativeness and norms as prior conditions. Also, process is influenced by the characteristics of the innovation and the socio-economic factors of the individual like personality characteristics that guide information seeking and communication behaviour, referring to access to change agents. Different types of communication channels are perceived to be enablers for the whole adoption decision process, where new ideas spread from individual to individual.
Both models exaplain the first-time usage of new technology. However, in order to continue to use the technology, newer models need to focus on experience, enjoyment, and satisfaction as well as the utilitarian aspects that we already covered.
If we consider the most important fact of the first model to be performance expectancy and the most important aspect of the second model to be communication channels, then we can combine these two models and say that the organizations where people adopt intelligent automation are the organizations where people talk a lot about performance, about expected results, right? I made it super simple just for everyone to understand.
Well, yes, but not only that. According to Rogers, organizations that are innovative are organizations where leaders also have an attitude open and supportive to change. Also, there are several characteristics of an organization that determine the diffusion of innovation: centralization, complexity, formalization, interconnectedness, organizational slack, and size. Finally, organizational openness is important, like how much are individuals linked to other individuals in external organizations.