Generative AI has arrived with the panache of a rock star. The World Economic Forum (WEF) couldn’t help but remark that the arrival of the technology “has been nothing short of seismic.” If, for a moment, we get away from the chorus of hosannas, the question is: If Gen AI is shaking up the world so quickly, are reliable trends starting to emerge around it just as fast? Can these trends be used to determine how an enterprise should think about adopting the technology? Our best bet is to look for trends in industries known to be early risk-taking adopters of technology. For example, the gaming industry is always ready to break the rules by adopting new technology. The gambling industry is ever willing to place bets on anything that can draw in more players.
However, looking at early adopters of technology is difficult. We are far too distracted by the deluge of eye-popping use cases for Gen AI that are capturing the headlines. For example, McKinsey says that healthcare clinicians could turn patient interactions into clinician notes within seconds using the technology. Gartner says Gen AI could create synthetic data and ensure privacy, optimize component placement in semiconductor chip design, or design spare parts in industries such as manufacturing, automotive, aerospace, and defense optimized to meet specific parameters and constraints.
If we stop to think about it, the use cases in healthcare, chip manufacturing, aerospace, etc., don’t indicate trends; they point to possibilities. Many industries, such as health care, financial services, manufacturing, and energy, are heavily regulated. In their business, any new technology is viewed cautiously (and rightly so). Therefore, their interest in Gen AI currently provides the weakest trend signals. Where should we be looking to find clues that help us adopt the technology?
First, let’s see who is already using Gen AI and setting early trends. A May 2023 study shows that 29% of Gen Z, 28% of Gen X, and 27% of Millennials in the US have adopted it in some form at their workplace. Chances are, they are using free Gen AI tools that have begun to mushroom around chat, search, art, audio/music, video, writing, transcription, summarization, and code generation. If you have a high percentage of Gen Z and X in your organization, it is worth doing a formal study of why they use Gen AI, the tools they use, the time spent using the tools, and the value it unlocks for them. Straightaway, this should offer usable insights for your organization.
The challenge for an enterprise is to find the sweet spot where business value intersects with financial and technical viability. Several organizations are using the technology to improve (and/or reduce the cost of) their communication. This means, primarily, written content, followed by video and image generation and the intelligence required to target the content. This makes sense. The time taken on written communication has been growing, says a Harris Poll, by 18 percent year over year, while its effectiveness has declined by 12 percent. This — creating compelling content — is the perfect use case, regardless of the industry. However, a recent Forrester study commissioned by Grammarly showed that 40 percent of employees were already using Gen AI to augment writing and other related tasks, but 80 percent of those respondents also said that their company had not adopted a Gen AI solution. The shadow IT pointed the report “can open the company up to significant risks if employees are using tools that do not meet enterprise-grade security and privacy standards.”
This is the most significant trend: Gen Z and X employees using Gen AI and the parallel security risk it presents. In the days to come, we are going to see some alarming incidents and disasters around the unfettered use of free Gen AI tools.
The top industries that will truly provide us with valuable insights on deploying Gen AI and using it for innovation are, obviously, the gaming and gambling industries. Traditionally, the two have been quick to explore new technologies such as cloud-based Massively Multiplayer Online (MMO) gaming, Augmented Reality (AR), Virtual Reality (VR), Mixed Reality (MR), Blockchain, and NFT — and use them effectively. For example, online casinos have been highly successful at using AR-based interactive applications to deliver creative content, improve the user experience, and deliver tutorials that help players learn and master new/different games. Now, they could use Gen AI for a number of things. For example, it could be used to predict addictive behavior in users and create interventions that make gambling safe.
In the past, the gaming and gambling industries have pushed the envelope of real-time online interaction, communication, and digital payments, ahead of other industries. Even today, gaming represents the bleeding edge of innovation, with large enterprises busy trying to exploit in-game environments, chats, rewards, exchanges, and payment systems. These are the trendsetters.
If there is something we should keep a firm eye on for future trends in Gen AI adoption and usage, it is the gaming and gambling industries.
