Insights into Real-World Usage of Generative AI

As generative AI becomes increasingly pervasive, it’s crucial to understand how people are truly leveraging, using, or just tossing words at this technology in their everyday lives. Despite the hype surrounding large language models (LLMs), there’s a notable gap between theoretical potential and practical application.

By exploring real-life use cases, we uncover the tangible impact of generative AI on individuals and organizations. Sometimes, it’s best to understand how others are using a new technology to gain a new perspective or approach on your own journey.

Key Findings

1) Diverse Applications:

By this point, we should all be seeing that Generative AI finds application across various domains, from technical assistance to creativity and leisure activities. Harvard Business Review research identified six primary themes encapsulating the broad utility of this technology.

• Technical Assistance & Troubleshooting (23%)
• Content Creation & Editing (22%)
• Personal & Professional Support (17%)
• Learning & Education (15%)
• Creativity & Recreation (13%)
• Research, Analysis & Decision Making (10%)

2) Real-World Examples:

The main article by author Marc Zao-Sanders states through extensive web mining, they unearthed concrete examples of how individuals are benefiting from generative AI. These examples span a wide spectrum, including brainstorming assistance, specific search queries, text editing, email drafting, and even legal document editing. I know I’m a personal fan of brainstorming.

3. Human-Machine Collaboration:

Contrary to fears of automation, being an innovation of the past, generative AI often complements existing automated processes, enhancing productivity and efficiency. The most common use case, idea generation, exemplifies this collaborative approach, where AI supports rather than replaces human creativity and decision-making skills or processes.

4) Accessible Professional Services:

Generative AI democratizes access to professional services such as legal advice, coding assistance, and, very soon, medical support. All of these “AI services” are looking into providing on-demand, personalized guidance that empowers individuals to navigate complex domains without reliance on expensive experts. Some of this even uses LAM’s (aka) large action models.

The evolving use of generative AI presents both opportunities and challenges. As organizations navigate the adoption of generative AI, understanding its practical implications and harnessing its benefits become imperative.

Notice: The views expressed in this post are my own. The views within any of my posts or articles are not those of my employer or the employers of any contributing experts.