Insightsresearch4 non-tech conditions for AI to influence performance

Over the last years, numerous reports have highlighted the gap between the promises of value creation associated with AI and the value captured by companies in reality. A recent research has investigated the drivers influencing success of AI initiatives and concludes on 4 drivers which ensure AI influences performance. Interestingly, they are not directly related with technology but more with culture and organisation.

In their article Artificial intelligence capability: Conceptualization, measurement calibration, and empirical study on its impact on organizational creativity and firm performance, Mikalef and Gupta  identify the AI-specific resources that jointly create an AI capability and examine the relationship between an AI capability and organizational creativity and performance.

Though their findings provide evidence that an AI capability results in increased organizational creativity and performance, the study helps to understand better what are the conditions for AI to generate performance.

Here are the main conclusions of the study:

  • “Soft” factors matter.  While data, the infrastructure and the techniques used to bring to life AI solutions have mostly dominated practice-based literature, other aspects influence AI success: develop the structures and culture that enable value generation from AI investments. For example, interdepartmental coordination is found to be a necessary condition to enable flow of information and data, as well as a means to develop AI solutions that correspond to the business requirements. Developing an AI orientation within the firm is a necessary precondition for successful deployments.
  • Skills are paramount. Results indicate that practitioners should focus not only on purely technical skills associated with AI, but also on the managerial competencies to direct AI initiatives toward priority areas that generate business value. These findings stress the importance of training technical and business staff with regards to emerging AI techniques and their applications.
  • Bold mindset is necessary. Adopting an organizational culture that embraces risk taking and making bold and radical actions is critical. This is a necessary mind-set when it comes to AI projects, as in many successful business cases using AI, going forward with uncertain initiatives that can possibly yield high returns has proven to be instrumental. Findings from the study show that it is important to embrace a logic of “high risk high gains” when it comes to AI.
  • Internal benchmark to fuel resources allocation.  An important component of becoming an AI ready organization is being able to self-assess the organizations’ strengths and weaknesses. This could show imbalances within the organization and units that are not on par with
    the others or have major weaknesses that could potentially inhibit overall attainment of goals. Such benchmarking attempts could help direct financing and resource allocation more efficiently and help generate business value with fewer uncured costs.

It’s an interesting view on the necessary transformation required in the resource stack of incumbents both at a cultural and organisational level.

AI-led transformation is a cultural transformation.

Photo by John Schnobrich on Unsplash

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