Wednesday, January 17, 2024

g-f(2)1863 Beyond the Hype Horizon: Where AI Goes Next


genioux Fact post by Fernando Machuca and Claude


This piece "Five Key Trends in AI and Data Science for 2024highlights five crucial developing issues in AI and data science that business leaders must track in 2024 - spanning generative assistant adoption, industrialized analytics, data product proliferation, shifting data science roles, and consolidated leadership.

genioux GK Nugget

"While 2023 spotlighted generative ingenuity, 2024 calls for scaling its benefits through ethical data strategies, workflow integration, and brave technology leadership." — Fernando Machuca and Claude

genioux Foundational Fact

Surveys of 500+ data executives reveal high confidence but early days for generative AI's value proposition despite profound potential. Realizing the upside requires revisiting data flows, orchestrating MLOps, and reskilling workforces. Industrializing analytics and productizing repeatable models will accelerate adoption. But confusion on strategy and aspirations persists, demanding simplified solutions and confident digital leadership rallying fragmented efforts under a north star.

The 10 Most Relevant genioux Facts

  1. Generative excitement outpaces economic gains demanding data and process upgrades before scale deployment.
  2. Platforms and automation boost analytical productivity as reuse expands.
  3. Packaging analytics into internal/external data products powers consumption.
  4. Proliferating complementary roles reduces data scientist bottleneck risks.
  5. AutoML empowers business-led modeling, lifting citizen data science.
  6. Unified digital chiefs subsume technical specializations to reduce confusion.
  7. But only with sharp business acumen and influencing skills beyond tech.
  8. Success requires planning before simply plugging in new features.
  9. And measured material impact beyond marveling innovations.
  10. But with care and foresight, this year AI bears its first fruits for many.


The way forward reveals itself to those who lift their eyes from devices towards horizons, beckoning bravery. By surveying landscapes first, adventures prepare provisions for risks that await. And through voices unified around worthy pursuits, fractured bands meld into cohorts capable of conquering frontiers. Onward together!


The GK Article

Thomas H. Davenport and Randy Bean, Five Key Trends in AI and Data Science for 2024, MIT Sloan Management Review, January 09, 2024.

Bing Chatbot's Summary:

The article "Five Key Trends in AI and Data Science for 2024" discusses the following key trends based on surveys of over 500 senior data and technology executives¹:

1. Generative AI: While generative AI has garnered significant attention, it has yet to deliver substantial economic value. Despite this, 80% of respondents believe it will transform their organizations, and 64% consider it the most transformational technology in a generation¹.

2. Investment in Generative AI: A large majority of survey respondents are increasing their investment in generative AI. However, most companies are still in the experimentation phase, with only 6% of companies in the AWS survey and 5% in the Wavestone survey having any production deployment at scale¹.

3. Organizational Change: Production deployments of generative AI will require more investment and organizational change, not just experiments. Business processes will need to be redesigned, employees will need to be reskilled, and the new AI capabilities will need to be integrated into the existing technology infrastructure¹.

4. Data Quality: Perhaps the most important change will involve data — curating unstructured content, improving data quality, and integrating diverse sources¹.

These trends suggest that while generative AI holds great promise, its successful implementation will require significant investment, organizational change, and improvements in data quality¹.

Source: Conversation with Bing, 1/17/2024

(1) Five Key Trends in AI and Data Science for 2024.

(2) Five Key Trends in AI and Data Science for 2024 - MIT.

(3) Top 8 Data Science Trends for 2024 - DataSpace Academy.

(4) Five Key Trends in AI and Data Science for 2024 From MIT Sloan ....

(5) Five Key Trends in AI and Data Science for 2024 From MIT Sloan ....

(6) Five Key Trends in AI and Data Science for 2024 From MIT Sloan ....

Thomas H. Davenport 

Thomas H. Davenport is a renowned American academic and author specializing in analytics, business process innovation, knowledge management, and artificial intelligence¹. He serves as the President’s Distinguished Professor of Information Technology and Management at Babson College¹. He is also a Fellow of the MIT Initiative on the Digital Economy¹, Co-founder of the International Institute for Analytics, and a Senior Advisor to Deloitte Analytics¹.

Davenport has written, coauthored, or edited twenty books, including the first books on analytical competition, business process reengineering, and achieving value from enterprise systems¹. His work has been published in numerous prestigious publications such as Harvard Business Review, MIT Sloan Management Review, and Forbes². He has also been a columnist for The Wall Street Journal, CIO, InformationWeek, and Forbes magazines¹.

In 2003, Davenport was named one of the world’s 'Top 25 Consultants' by Consulting magazine¹. In 2005, he was named one of the world’s top three analysts of business and technology by readers of Optimize magazine¹. In 2012, he was named one of the world's "Top 50 Business School Professors" by Poets and Quants and Fortune Magazine¹.

Davenport initially trained as a sociologist, with a BA in Sociology from Trinity University in 1976, a Master's degree in Sociology from Harvard in 1979, and a Ph.D. in Sociology from Harvard in 1980¹. After graduating with a Ph.D. in Sociology, Davenport worked as an academic before being offered a research and consulting job at Index by James Champy¹. He became Director of research at Index, studying business process improvement¹.

Source: Conversation with Bing, 1/17/2024

(1) Thomas H. Davenport - Wikipedia.

(2) Home - Tom Davenport.

(3) About - Tom Davenport.

Randy Bean

Randy Bean is a recognized industry thought leader, author, founder, and CEO, who currently serves as an Innovation Fellow for Data Strategy at the global consultancy, Wavestone². He has made significant contributions to the field of data-driven leadership in an age of disruption, big data, and AI². His book, "Fail Fast, Learn Faster: Lessons in Data-Driven Leadership in an Age of Disruption, Big Data, and AI" (Wiley, 2021), is a testament to his expertise and thought leadership². He is also a frequent speaker and contributor to various publications². Prior to his role at Wavestone, he was the Founder and CEO of NewVantage Partners². His work focuses on helping Fortune 1000 organizations with data strategy, innovation, and transformation³.

Source: Conversation with Bing, 1/17/2024

(1) Randy Bean - Forbes.

(2) Randy Bean Data.

(3) Obituary: Randy Bean |

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This genioux Fact post is classified as Breaking Knowledge which means: Insights for comprehending the forces molding our world and making sense of news and trends.

Type: Breaking Knowledge, Free Speech

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