g-f(2)1467 Navigating the Path to Successful AI Projects

 

genioux Fact post by Fernando Machuca and Bing Chatbot

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Introduction (By Fernando):

As we venture into the dynamic and rapidly evolving digital universe of the g-f New World, golden knowledge (GK) serves as our guiding beacon, illuminating the path towards tapping into humanity’s boundless potential [g-f(2)1 - g-f(2)1466]. In this genioux Fact post, I harness the exceptional GK extraction capabilities of Bing Chatbot, a tool that benefits from the robust support of Microsoft’s search engine.

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Introduction: 

Artificial Intelligence (AI) projects hold immense potential for transforming businesses and driving economic growth. However, the sobering reality is that most AI projects fail, with some estimates placing the failure rate as high as 80%. This genioux Fact post explores how businesses can navigate the complexities of AI projects and increase their chances of success.

genioux GK Nugget: 

"The success of an AI project hinges on careful navigation through five critical steps: selection, development, evaluation, adoption, and management." — Iavor Bojinov refined by Fernando and Bing Chatbot

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genioux Foundational Fact: 

Despite the immense potential of Artificial Intelligence (AI), most AI projects fail due to various challenges. However, companies can greatly reduce their risk of failure by carefully navigating five critical steps that every AI project traverses on its way to becoming a product: selection, development, evaluation, adoption, and management.

10 genioux Facts:

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1. AI, especially generative AI, is a central theme in corporate boardrooms and leadership discussions.
2. Despite the tantalizing potential of AI, most AI projects fail, with some estimates placing the failure rate as high as 80%.
3. Companies can greatly reduce their risk of failure by carefully navigating five critical steps that every AI project traverses on its way to becoming a product: selection, development, evaluation, adoption, and management.
4. The selection phase involves identifying the right tasks for AI automation or augmentation.
5. The development phase focuses on creating the AI solution.
6. The evaluation phase assesses the effectiveness of the AI solution.
7. The adoption phase involves integrating the AI solution into existing workflows1.
8. The management phase ensures the continuous improvement and updating of the AI solution.
9. A decade ago, AI was of interest only to a small team of people in data science organizations with advanced degrees in statistics or computer science1.
10. Today, topics like “Data Science for Managers” are now a first-year requirement at institutions like Harvard Business School.

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Conclusion: 

While the potential of AI projects is immense, realizing this potential requires careful navigation through various stages from selection to management. By understanding these stages and addressing the challenges at each step, businesses can increase their chances of success and harness the transformative power of AI.

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REFERENCE

The GK article

Iavor Bojinov, Keep Your AI Projects on Track, Harvard Business Review, From the Magazine (November–December 2023).

Iavor Bojinov

Iavor Bojinov is an accomplished academic and professional in the field of data science. He started his career as a data scientist at LinkedIn, where he gained valuable industry experience¹²³. Currently, he serves as an Assistant Professor of Business Administration and the Richard Hodgson Fellow at Harvard Business School¹²³. 

In addition to his teaching role, Bojinov is the co-PI of the Data Science Operations Lab and a faculty affiliate in the Department of Statistics at Harvard University and the Harvard Data Science Initiative¹²³. His research and writings center on data science operations, aiming to understand how companies should overcome the methodological and operational challenges presented by the novel applications of data science¹²³.

Bojinov's work has been featured in top Statistics, Economics, and Management journals such as Annals of Applied Statistics, Biometrika, the Journal of the American Statistical Association, Quantitative Economics, and Management Science¹. His contributions to the intersection of data science and business have earned him recognition as one of the few scholars to have spotlight featured articles in both the Harvard Business Review and the Harvard Data Science Review¹.

Source: Conversation with Bing, 10/17/2023

(1) Iavor I. Bojinov - Faculty & Research - Harvard Business School. https://www.hbs.edu/faculty/Pages/profile.aspx?facId=1199332.

(2) Iavor Bojinov | Assistant Professor | HBS. https://www.ibojinov.com/.

(3) Iavor Bojinov, Harvard Business School - CXOTalk. https://www.cxotalk.com/bio/iavor-bojinov-assistant-professor-harvard-business-school.

(4) Iavor Bojinov | Digital Data Design Institute at Harvard. https://d3.harvard.edu/our-team/iavor-bojinov/.

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Searching for: "Keep Your AI Projects on Track." summary

The article "Keep Your AI Projects on Track" discusses the sobering reality that most AI projects fail, with some estimates placing the failure rate as high as 80%¹. However, it suggests that companies can greatly reduce their risk of failure by carefully navigating five critical steps that every AI project traverses on its way to becoming a product: selection, development, evaluation, adoption, and management¹. 

The author emphasizes that AI, especially generative AI, is a central theme in corporate boardrooms and leadership discussions. Despite the tantalizing potential of AI, beneath the aspirational headlines lies a sobering reality: Most AI projects fail¹. 

The article concludes by stating that despite these challenges, companies can increase their odds of success by understanding and navigating these five critical steps¹.

Source: Conversation with Bing, 10/17/2023

(1) Keep Your AI Projects on Track - Harvard Business Review. https://hbr.org/2023/11/keep-your-ai-projects-on-track.

(2) NVIDIA AI Enterprise Support Services. https://www.nvidia.com/en-us/data-center/products/ai-enterprise-suite/support/.

Type: Bombshell Knowledge, Free Speech

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Reference

“genioux facts”: The online program on "MASTERING THE BIG PICTURE OF THE DIGITAL AGE”, g-f(2)1467, Fernando Machuca and Bing Chatbot, October 17, 2023, Genioux.com Corporation.

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