Gen AI's Assisted Work May May Be Better Than You Think

Discussion around generative AI's predicted fact impact mostly centers on the immediate no-brainer applications for LLM's. Generative AI's current excitement is built around consumer use use of LLM's through services like ChatGPT , 谷歌 Bard, X Grok, Stable Diffusion, and other popular models. But the biggest fastest contribution of Generative AI could be in the soft skills areas of decision-making and collaboration.

According to 麦肯锡 generative AI significantly enhances the potential for automating knowledge work activities, particularly those involving decision-making, collaboration, and the application of expertise, which previously had lower automation potential. In a recent report titled The Economic Potential of Generative AI, McKinsy analysts identify 7 areas where Generative AI can have an outsized positive impact:

1. Applying Expertise (58.5% automation potential with generative AI vs. 24.5% without): Generative AI's advanced natural language capabilities enable the automation of complex decision-making and planning tasks, significantly elevating the potential for automating the application of expertise.

2. Managing (49.0% vs. 15.5%): The ability of generative AI to process and analyze large amounts of data enhances the automation potential in management tasks, particularly in developing talent and decision-making processes.

3. Interfacing with Stakeholders (45.0% vs. 24.0%): Generative AI improves stakeholder engagement through automated, nuanced communication and data-driven insights, thereby increasing automation potential in this area.

4. Processing Data (90.5% vs. 73.0%): The technology's proficiency in handling and interpreting large datasets substantially boosts the automation potential in processing data.

5. Collecting Data (79.0% vs. 68.0%): AI's ability to gather and organize data from diverse sources efficiently contributes to a higher automation potential in data collection.

6. Performing Unpredictable Physical Work (46.0% vs. 45.5%): While generative AI has limited influence here, its integration with other technologies marginally increases automation potential in tasks involving unpredictability in physical environments.

7. Performing Predictable Physical Work (73.0% vs. 72.5%): Similar to unpredictable physical work, generative AI's impact is minimal but slightly enhances automation potential due to its cognitive capabilities augmenting physical tasks in predictable settings.

The 麦肯锡 report is chock full of a ton of valuable and well-researched projects. Click here to get the complete version of The Economic Potential of Generative AI.

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