Artificial Intelligence and the Shaping of Business Contexts
摘要截稿:
全文截稿: 2019-02-01
影响因子: 4.874
期刊难度:
CCF分类: 无
Overview
Artificial Intelligence (AI) is leading to automated and interconnected business processes that have implications for actors (e.g., customers, firms, and other stakeholders), relationships and experiences. The fast pace of AI and digitization, coupled with cloud-based resources, connectivity, and customizable platform-based business models, is enabling new forms of interaction that are causing business strategists and entrepreneurs to rethink their relationships with customers and other actors they serve in context.
Similarly, the workplace is also experiencing an AI-motivated paradigm shift, as “human skills” (e.g. mechanical, analytical, and intuitive) are being enhanced, if not often replaced. Huang and Rust (2018) predict that empathetic machines will become a part of the “new” labor force.
Sales and marketing automation are thus moving towards building intelligent systems that can collaborate effectively with people (Stanford University Report, 2016). According to Salesforce (2016), predictive intelligence, “lead-to-cash" process automation, and artificial intelligence are expected to experience dramatic growth in the next three years. McKinsey has forecast that by 2020 machines will manage 85% of all transactions (Baumgartner et al., 2016). More generally, advances in autonomous technologies provide challenging prospects for integrating human-based interaction with machine-to-machine interaction or more customized and contextual forms of human-to-machine interactions.
The application of AI is already on the agenda for most companies; however, many of the issues related to the impact that AI will have on various actors and their interactions remain underexplored. For example, how will AI change the logic of business models (Wieland et al., 2017) and the (re)shaping of markets (Nenonen and Storbacka, 2018). How will the service context be affected (Hartmann et al., 2018)?
Furthermore, the use of AI raises questions about the characterization of resources and attributions of agency (see Vargo and Lusch, 2017). That is, can AI be seen as an operant resource (Akaka and Vargo, 2014)? Does AI have agency?
Arguably, all of these issues come together in the consideration of market context, especially when viewed in terms of dynamic systems, such as service ecosystems (Vargo and Lusch 2016). AI can be seen as adding new dimensions of ‘resourceness’ as it increases the complexity and thus the emergent nature of markets.
Following is a non-exhaustive and non-exclusive list of issues and questions that might be addressed in response to this CFP. Other appropriately related topics are equally welcome:
- What are the effects of AI on the customer experience? What constructs moderate or mediate this relationship?
- How will AI shape the context for value co-creation? How will it affect resource integration and service for service exchange?
- What is the role of technology as an operant resource?
- How does AI reconcile with the Actor to Actor (A2A) orientation of S-D logic?
- How will value be realized and appropriated when AI is involved? To what extent will automation change pricing strategies?
- How will machine-human interaction nudge decision-making processes with respect to individual and collective well-being?
- How is AI influencing the organization of business networks?
- How will sales, marketing, supply chain management, operations, and (or) communication activities benefit from AI systems? What functions will be difficult to automate? How will AI influence the integration among organizational functions?
- How will automation and AI affect marketing and sales employees and their interaction with other actors?
- Is there a “dark side” to AI? What will be the impact on employment?