This blog is an excerpt from the ebook: “A primer for data readiness for generative AI.” Download the complete version here.

The simplest way generative AI, particularly large language models, can boost productivity is in the same role as search engines: surfacing critical information for users but with a greater ability to simulate human-like semantic understanding of its output. In this regard, generative AI is a general-purpose productivity aid that makes quality information freely available to those who want it.

A more powerful application of generative AI is to leverage the unique data and context associated with an organization from its operations. All organizations produce a huge corpora of text through contracts, blogs, call transcripts, chat applications, project management tools, emails and internal documentation of all kinds. A large language model trained on such a corpus can meaningfully answer domain-specific questions, summarize text, translate between languages, adjust tone, extract issues, themes and sentiments and more. In effect, a large language model with access to an organization’s accumulated data can act as the most knowledgeable “member” of an organization.

Practical, general examples of how this capability can support a business include:

• Supporting customers, whether as a fully automated chatbot or helping human customer service representatives access obscure information or troubleshoot issues
• Shortening turnaround time to create sales and marketing content, including media of all kinds – written collateral, images, animations and more
• Accelerating the software engineering process by generating boilerplate code or translating between programming languages
• Rapidly brainstorming and prototyping new products and concepts

There are countless potential industry-specific use cases, as well. Generative AI may be able to:

• Automatically produce financial documentation
• Enable retail customers to virtually “try on” clothing and accessories
• Accelerate the discovery of new drugs by pharmaceutical researchers by uncovering new configurations of proteins and other molecular structures
• Accelerate legal and paralegal work, such as legal research, drafting documents and communication with clients
• Enable doctors to more readily diagnose rare and unusual diseases and devise personalized treatment plans
• Help aerospace engineers optimize the shape of new airframes
• Procedurally generate CGI assets for video games, films and other digital media
• Help educators create personalized lesson plans and instructional materials

Generative AI can support nearly all creative or intellectual business activities, mainly by decreasing the time and effort required to ideate, iterate and prototype new content of all kinds. 

Although generative AI will primarily affect occupations that heavily engage in intellectual or creative work, there is growing evidence that, within those occupations, relatively lower performers stand to benefit the most. In other words, generative AI stands to raise the average level of performance at a given organization.

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