Published on February 15, 2024, 1:38 am

Despite the current buzz and widespread adoption, Generative AI still has to go through the disillusionment phase before achieving maximum productivity. The rapid adoption and democratization of Generative AI have been compared to the advent of the lightbulb, which brought about a radical change in the lives of individuals and businesses. Much like the invention of electricity, the lightbulb paved the way for transformative innovations. Similarly, Generative AI is revolutionizing artificial intelligence today.

When technology transitions from labs to everyday life, its widespread diffusion is typically based on increasingly powerful and proven use cases. With this rapid adoption comes excitement for the art of possibility, placing Generative AI at the peak of great expectations defined in the hype cycle. For example, ChatGPT gained over 100 million monthly active users in just two months last year, showing that we have reached mainstream adoption. However, we are still at the peak of expectations.

In navigating the hype cycle of Generative AI, there are five recommendations for CIOs (Chief Information Officers) to prepare for a swift transition from disillusionment to enlightenment:

1. Highlight both positive and negative aspects: While evangelizing the transformative nature of Generative AI and related solutions, CIOs should ensure they also emphasize its drawbacks. Many consulting firms and technology vendors focus on its transformative power but pay less attention to its shortcomings. Realism involves understanding the pros and cons and sharing this information with clients, employees, and colleagues in the C-suite.

2. Establish clear usage policies: Developing an enterprise usage policy for Generative AI can help educate employees about its risks and pitfalls while providing guidelines to maximize its value without jeopardizing company security or ethics. Involving relevant stakeholders in policy creation ensures transparency in how Generative AI is used within an organization.

3. Evaluate use cases individually: It’s crucial to examine each use case individually rather than assuming that Generative AI is a perfect fit for every situation. For instance, Generative AI may not be suitable for writing technical forecasts, as its results often restate existing knowledge and can be plagiarized. It’s essential to consider the trade-offs before applying Generative AI and opt for it only when clear advantages emerge.

4. Educate and train employees: Given widespread adoption, CIOs should focus on training and educating employees about the benefits and drawbacks of Generative AI, using the enterprise usage policy as a starting point. Emphasizing testing and experimentation within the organization’s IT department or other business units can help raise overall awareness and promote best practices throughout the company.

5. Plan for AI errors: It is essential to have a plan in place for when Generative AI makes mistakes. While the enterprise usage policy sets guidelines, governance processes within IT must monitor and react to unexpected situations effectively. How will these processes distinguish correct responses from wrong ones? What impact does an error have on the company, and how easy or difficult is it to rectify?

Generative AI will eventually reach its moment of enlightenment but only after traversing through disillusionment, climbing uphill, and ultimately reaching a plateau of productivity. The gaslighting, experimentation, and learning along the way are all part of this process.

In conclusion, as Generative AI continues to shape various industries with its transformative potential, organizations must approach it with caution. Understanding its limitations and establishing proper governance structures will help mitigate risks while unlocking its full value in driving innovation forward.

Nicholas D. Evans, Chief Innovation Officer at WGI, offers valuable insights into navigating the hype cycle of Generative AI based on his experience as a thought leader in technology innovation.


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