The Technology / Innovation Trigger stage represents the initial discovery or breakthrough of a new AI technology. This stage is characterized by a lot of excitement, media attention, and high expectations. An example of this is Quantum technology. While a promising technology that has the potential to solve complex problems, it’s still in its infancy.

During this stage, it is crucial to closely monitor the development of the technology and assess its potential impact on your industry or business. Thus, we approach Quantum tech with a critical mindset and evaluate its feasibility and practicality.  

The Peak of Inflated Expectations is the stage where the hype surrounding the AI technology reaches its peak. During this stage, there is a lot of buzz and excitement, with inflated expectations about the potential capabilities and impact of the technology. An example of this is Autonomous vehicles, which have been the subject of much hype and excitement in recent years.  

Despite bold predictions, businesses need to be critical and cautious during this stage. It’s essential to evaluate the actual capabilities and limitations of the technology. For example, autonomous cars face challenges relating to safety and regulatory frameworks.  Many technologies fail to live up to the inflated expectations during this stage, leading to disappointment and a subsequent drop in public perception.  

During the Trough of Disillusionment the initial hype and excitement surrounding the technology give way to a period of disappointment and skepticism. This stage is characterized by a realization of limitations, challenges, and practical issues.  A good example of this is Virtual Reality (VR). Once hailed as the next “big thing” in entertainment, it soon became apparent that VR is costly, has limited content and is uncomfortable to wear.  

During this stage, it’s important to maintain a realistic perspective and to learn from the lessons and failures of early adopters. Here businesses can reassess expectations, refine strategies, and address the challenges associated with technology.  

The Slope of Enlightenment stage makes way for technology to mature and businesses have a clear understanding of its benefits and limitations. During this stage, the technology starts to gain traction, and successful use cases begin to emerge. 

An example of this is Natural Language Processing (NLP). Natural language processing has made significant progress in recent years, with advancements in machine learning and deep learning algorithms. It’s being successfully applied in various fields, such as customer service chatbots, voice assistants, and sentiment analysis. 

In this stage, it’s essential to closely follow the developments and success stories. Learning from early adopters and industry leaders can provide valuable insights and guidance for successful implementation. It’s also important to stay abreast of the latest advancements and emerging trends to leverage the technology effectively.  

The Plateau of Productivity is the final stage of the Gartner AI Hype Cycle, representing the widespread adoption and acceptance of the technology. During this stage, the technology becomes mainstream, and its benefits and value are well understood.

Organisations and individuals have developed the necessary skills and infrastructure to effectively leverage the technology, leading to increased productivity and competitive advantage. Here Machine Learning comes to mind. Machine learning is now widely adopted in various industries. It is used for tasks such as predictive analytics, fraud detection, recommendation systems, and image recognition.  

Businesses must now focus on maximising the value and potential of technology. It may be necessary to refine and optimise existing implementations, explore new applications and use cases and drive continuous innovation to stay ahead of the competition.