Smart automation is an integral part of the digital transformation of operations and services. However, automation goes much beyond the application of digital technologies and data when artificial intelligence (AI) and robotics are recruited to fulfill any task. Smart automation entails using capabilities of learning from data (huge amounts of data), adaptation and autonomous execution of the system’s self-instructions (e.g., self-driving car, virtual service agent). We need, nevertheless, to consider different outcomes and consequences that may arise from utilisation of these advanced technologies.

Artificial intelligence can generate significant benefits in complementing and augmenting human cognitive and executive capabilities in performing various jobs — analysing and learning from large data sets (e.g., discovering latent patterns), accuracy and reliability of execution, problem-solving, time-saving. Many professionals, consultants and experts, agree that AI and robots can assist and complement humans by collaborating with them rather than by replacing the humans, at work but also in leisure. In other words, the smart advanced technologies are supposed to benefit humans, and not necessarily making them redundant, whether in making decisions or executing mental and physical tasks.

In spite of those recommendations, the adverse economic conditions induced by the Corona pandemic, specifically the negative prospect of a prolonged period of depression, might lead companies even more vigorously to seek those opportunities offered by AI to do with fewer human employees. They might do so to reduce labour costs as their incentive, or wherever they find that AI, virtual or embedded in physical robots, can do jobs in manufacturing, administration and service more efficiently than humans, and at least as satisfactorily.

The elimination of some jobs performed by humans may be unavoidable, and could possibly be justified (e.g., mid-level skills, technical, routine). A solution suggested is to educate and train more people to perform higher-skilled, knowledge-based jobs in the fields of advanced technologies, or at the very least train employees how to work productively in collaboration with the AI and robotic applications. Yet, companies might be discouraged in the near term by the dire economic conditions from investing in solutions that create new employment opportunities for their human workers.

The crisis due to the coronavirus apparently hastens processes of digital transformation and utilisation of AI-enabled applications. Nonetheless, it may also enhance less desirable responses of companies to the implications of deploying those AI-enabled technological applications.

Under these circumstances, consumers are going to be negatively affected by the deployment of AI, and subsequently there may be fewer consumers prepared to respond positively to marketing efforts of companies offering consumer products and services. Moreover, suppose a company is using an intelligent recommendation engine able to create individually-informed product recommendations, better tailored to the preferences of their targeted customers (or prospects); however, the latter could be more reluctant to accept some of the offers, appealing as they may be, because they have lower financial resources (unless they are occupied in the ‘right’ well-paying jobs). Consumers will surely continue to accept offers that best-fit their specific needs and wants at the right time. However, consumers may become more critical and selective in their choices, applying greater scrutiny more often.

Virtual assistants are getting increasingly intelligent, equipped with granular knowledge about individual consumers, products, companies and markets. A ‘talented’ virtual personal shopping assistant can quickly understand the problem or need its consumer-client is trying to resolve from a short query in natural language, cross-check between different types of information, and narrow-down the options to just a few appropriate solutions (e.g., 2-3 product offerings). That is, the shopping assistant can save consumers lengthy search and exploration ventures, and it may still be able to trace better answers than the consumer. Online retailers may employ AI capabilities in the future to send to customers in advance (i.e., without formal ordering) products they identify as needed, of interest or sought for by the customers at a given time, based on their tracked activities and learned preferences; customers will have the option to confirm the purchase by keeping the product or to return it (a business model Davenport and his colleagues label ‘shipping-then-shopping’ [1]).

Marketing enabled by AI, and its smart assistants, is expected to undertake automated decision-making on behalf of consumers more frequently. It raises delicate issues about the relations between consumers and smart assistants (i.e., are those assistants helping consumers or leading them), and yet will consumers be left with control or autonomy they may wish to preserve in choosing which products they wish to acquire and use [2].

Intelligent technologies and models may enhance the effectiveness and usefulness of marketing actions. At the same time, the applications of such methods in various fields and functions are going to have consequences that may hurt and limit the reach and impact of marketing actions on consumers.

It is important to acknowledge that we are in midst of a period of transition and adjustment to AI-enabled digital technologies and interaction with their applications. Even though the applications now engaged are functional, context- and task-specific (i.e., Narrow Artificial Intelligence), they can still have strong impact in many areas. The Corona crisis may have rushed and complicated this process of adaptation somewhat for consumers. Collaboration between humans and AI-enabled applications and robots will not happen on its own — it will have to be encouraged and facilitated through pro-active initiatives of companies, governments and public agencies. Marketing applications enabled by AI require special attention and care to guard consumers from inadvertent sensitive implications or adverse influences.

Notes:

[1] “How Artificial Intelligence Will Change the Future of Marketing”; Thomas Davenport, Abhijit Guha, Dhruv Grewal, & Timna Bressgott, 2019; Journal of the Academy of Marketing Science, October 2019 (online: Springer), 19p (doi,org/10.1007/s11747-019-00696-0)

[2] For more background see (with reference in particular to shopping assistants and implications of using them):

Consumer Choice and Autonomy in the Age of Artificial Intelligence and Big Data“, Quentin Andre, Ziv Carmon et al., 2018; Customer Needs and Solutions, 5 (1-2), pp. 28-37.

Artificial Intelligence: Marketing Game Changer“, Edward Forrest and Bogdan Hoancra, 2015; in Trends and Innovation in Marketing Information Systems, Theodosios Tsiakis (ed.), IGI Global

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