Navigating the trough of disillusionment: unpacking the pace of GenAI adoption

Over the past few months now, I’ve been on the ground at conferences and industry happy hours, hearing first hand a phrase that keeps popping up about the slow pace of GenAI adoption. Whether it’s at AWS Summits or Datastax RAG++ events, people are calling this the “trough of disillusionment.” It suggests, to those of us paying close attention, that GenAI hasn’t quite lived up to the initial hype, leaving many feeling disillusioned.

The hype

Every technology has its ups and downs and according to the Gartner Hype Cycle, the notion that GenAI failed to deliver on the initial hype stems from a misunderstanding of how the cycle works. In 2023, Devoncroft Partners presented its Big Broadcast Survey, an annual demand-side study of the global broadcast and media technology sector that tracks factors driving purchase decisions. The survey compared what sellers and buyers ranked as their top technology considerations.

It was no surprise to see sellers excited about AI and Generative AI, rating it as the most important technology investment. Conversely, buyers ranked AI much lower, focusing instead on cost-containment solutions amid an economy already showing signs of weakening. These contrasting perspectives are at the root of the perceived drop in GenAI interest. 

GenAI challenges and opportunities 

While artificial intelligence (AI) dates back centuries, it is ever since OpenAI shocked the world with ChatGPT that companies have been paying close attention to GenAI as a technology. And while interest remains elevated, it is tempered by caution. The impact of this transformative technology on the workplace is akin to when computers became available on every desktop or when the Internet transformed how we do  our jobs. Neither of those transformations happened overnight, and neither has ever been described as disappointing.

The factors slowing adoption of GenAI are well known:

• Lacking skill sets and knowledge
• Need for user education
• Concerns around governance and security
• Intellectual property risks

Many boards initially pushed for mandates to adopt GenAI to maintain market relevance, but the challenges of execution led to a business paradox that has stagnated the adoption curve and led to this perception of failure. Large software engineering firms aggressively promoted GenAI agendas to expand their service offerings, only to encounter hesitation from organizations that first wanted to understand the implications of this new world they were entering.

Now, nearly two years after the initial public release of the seeming magic of ChatGPT, a few encouraging developments have occurred that could further spur GenAI adoption.

The proof of the pace

Research from various firms like EY, BCG, and IDC highlights the productivity enhancements resulting from GenAI in content creation, coding, and other areas. 

These growing bodies of research highlights a clear consensus: GenAI enhances productivity, leading to a resurgence of interest across organizations from a broad swath of industries, now eager to capitalize on cost-saving opportunities. 

The market is responding, too, with an ever-expanding array of GenAI tools. Leading cloud-based LLMs like AWS Bedrock, Microsoft Azure OpenAI, and Google Vertex AI are becoming increasingly accessible, while SaaS solutions powered by GenAI are thriving in sectors like marketing, customer service, education, and software development.

GenAI is also appearing in unexpected places, helping users improve software development, copywriting, logo creation, video production, and data analysis. As individuals and companies grow more comfortable with the technology, the fears of nearly two years ago are slowly fading, and GenAI is on its way to becoming as commonplace as computers on every desktop.

Even the final frontier—security—is seeing great progress. Securing GenAI models’ access to company data, ensuring unbiased model training, and protecting the workforce’s use of public and private GenAI are now possible through a growing number of in market solutions.

GenAI adoption over the next decade will be transformative and our imaginations cannot yet fathom how pervasive the technology will become in our daily interactions

And with that, two questions remain:

1. are we out of the trough and into the slope of enlightenment? and,

2. will we settle into a “Plateau of Productivity” that falls short of the initial high expectations?