Organizational Adoption of Artificial Intelligence

 

I have been interested in AI for a long time. I remember that my first real contact with AI was when my dissertation advisor handed me a bunch of floppy disks with a state-of-the-art rule-based engine. Working closely with my professors, we researched various cognitive technologies and expert systems applied to engineering problems. I remember writing my first publications on how construction companies can utilize AI in the project's design and construction phases.

Over the decades, I remained focused on AI, especially machine learning (ML) and natural language processing (NLP), and how organizations were using them. There were many shifts in dominant technologies. Currently, deep learning is clearly the biggest deal in town. However, the question of how organizations are getting value from specific technologies was equally always important. Moreover, organizational adoption patterns of various algorithms are probably a force driving the field of AI more so than research.

The most advanced adopters of artificial intelligence have been high tech companies in the private and public (defense) sectors. We need to distinguish the use of AI between internal and external areas of application. The former deals with supply chain optimization or various resource allocation applications, scheduling, design, automation, etc. The latter is selling products with AI embedded in the product.

One of this group's key contributions will be a (hopefully) systematic investigation of AI and its perceived benefits in organizations. When we are dealing with transformative technologies, there will be more or less significant organizational transformations. Some companies will apply AI as a set of background technologies. Others will choose to make AI the focal point of the business model.

There is no doubt that advanced technologies are worth the attention of most organizations—however, the more advanced the technology, the greater the risk of unsuccessful adoption. Organizational, environmental, competitive, and technological issues will have to be a part of the technology adoption model.