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HOW TO SCALE DATA SCIENCE PILOTS TO INDUSTRIALISE YOUR DATA: PHILIPP M DIESINGER

Dr. Philipp M Diesinger has occupied key roles in data science since 2009. His career includes a post-doctoral position at the Massachusetts Institute of Technology, Data Science Consultant at SAP and Head of Global Data Science at Boehringer Ingelheim. Dr Diesinger’s specialisms include Predictica Analytics and machine learning.
Here, Philip considers how the influence of ever-evolving AI and globalisation is prompting a shift from a human-centric to a hybrid workforce. How are workplaces best suited to collaborate with AI, and what benefits does such a collaboration offer over traditional teams?
Consistent and sustainable growth of the world economy will remain critical to overcome the significant challenges that lie ahead of human kind. One of the most promising drivers for economic growth is the creation of new efficiencies in the workforce with AI. The next decade will present the opportunity to move from a human to a hybrid workforce where GenAI technologies support us seamlessly.

Over the next few decades, humanity will face significant global challenges; including the need to transform economic models towards more sustainable growth (not relying on large-scale resource exploitation) and to address global environmental pollution. Meeting these challenges will require significant resources and a sustainable, growing world economy.
History has shown that extended periods of economic growth can not only provide the resources needed to solve urgent problems, but also reduce tensions and create opportunities for global collaboration. Such periods of sustained growth are often based on significant technological breakthroughs that boost workforce productivity across sectors.

The anticipated transition from a purely human workforce to a hybrid workforce, where humans and AI-systems collaborate closely and seamlessly, qualifies as such a technological leap. This new type of workforce will be supported by AI systems that effectively provide every worker with an expert companion for almost every field imaginable, leading to significant jumps in efficiency. GenAI companions will be able to write emails, organise calendars, draft presentations, write code, produce ad-hoc reports leveraging complex data analysis, search through vast amounts of unstructured data and provide relevant information for insightful and fact-based decision making. They will complement human weaknesses by not only providing strong communication skills but also expert domain knowledge where it is needed. This may even turn formerly unsuited candidates into potential hires.

Organisations must begin preparing their workforce to enable a smooth and successful transition to the new way of working. Roles and responsibilities, ways of working, policies, processes and hiring practices need to be adapted for the transition to a hybrid workforce if companies want to benefit from increases in efficiency, robust economic growth and ensure competitiveness.
To learn more about the potential for economic growth a hybrid workforce offers, read the article in full over on our magazine:

https://issuu.com/datasciencetalent/docs/the_data_scientist_mag_issue_4_final/s/43565616

 

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