How generative AI will change the nature of work

Generative AI is a powerful tool for rapidly creating and iterating on content of all kinds
January 17, 2024

This blog is adapted from the ebook: “The data leader’s primer 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:

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.

[CTA_MODULE]

Commencer gratuitement

Rejoignez les milliers d’entreprises qui utilisent Fivetran pour centraliser et transformer leur data.

Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.
Data insights
Data insights

How generative AI will change the nature of work

How generative AI will change the nature of work

January 17, 2024
January 17, 2024
How generative AI will change the nature of work
Generative AI is a powerful tool for rapidly creating and iterating on content of all kinds

This blog is adapted from the ebook: “The data leader’s primer 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:

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.

[CTA_MODULE]

The data leader’s primer for generative AI
Download the ebook now

Articles associés

How generative AI is different from traditional AI
Data insights

How generative AI is different from traditional AI

Lire l’article
Prompt engineering and the responsible use of generative AI
Data insights

Prompt engineering and the responsible use of generative AI

Lire l’article
Comment construire une base de données pour l’IA générative
Data insights

Comment construire une base de données pour l’IA générative

Lire l’article
AI-driven data integration: The future of automation
Blog

AI-driven data integration: The future of automation

Lire l’article
Generative AI: A 2-year retrospective and what's next
Blog

Generative AI: A 2-year retrospective and what's next

Lire l’article
How to use Fivetran and Snowflake to move data and innovate
Blog

How to use Fivetran and Snowflake to move data and innovate

Lire l’article
AI-driven data integration: The future of automation
Blog

AI-driven data integration: The future of automation

Lire l’article
Generative AI: A 2-year retrospective and what's next
Blog

Generative AI: A 2-year retrospective and what's next

Lire l’article
How to use Fivetran and Snowflake to move data and innovate
Blog

How to use Fivetran and Snowflake to move data and innovate

Lire l’article

Commencer gratuitement

Rejoignez les milliers d’entreprises qui utilisent Fivetran pour centraliser et transformer leur data.

Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.