A report by London-based Tesseract Academy has found that most project managers believe that current methodologies are not sufficient to manage AI projects.

LONDON, UNITED KINGDOM, July 27, 2022 /EINPresswire.com/ -- The Tesseract Academy, a London-based data science consultancy and educational organisation, released the following report: Tesseract Report: Project management for AI and data science (at https://tesseract.academy/tesseract-report-project-management-for-ai-and-data-science). The Tesseract Academy examined the current beliefs and practices of project managers in the space of data science and AI. It enquired 17 experts a set of questions such as what methodologies they are using to manage data science projects, and what tools they prefer.

The report revealed some interesting findings. It looks like the majority of project managers are using existing project management methodologies for software development (like AGILE) and try to apply them to data science. However, the majority believes that these methodologies are not sufficient, and there are many ways in which they can be improved. More specifically, only 29% of the respondents believes that the current methodologies are enough, whereas 65% of the respondents are not really using any scoping methodology for data science projects, like IBM's CRISP-DM or Microsoft's Teams Data Science Process.

The majority of the respondents reported that the main challenges related to the fact that data science is often considered an esoteric topic, which is misunderstood by stakeholders. Therefore, this makes adherence to deadlines more difficult and slows down the adoption of data science.

Dr Stylianos Kampakis shares his views:
"It's clear that as data science and AI become more and more important, organisations find that existing tools are not enough to deal with the complexity and the uncertainty of data science projects. Not only we need new and better methodologies and tools, but we also need to educate decision makers and stakeholders on how data science operates and how it can add value to a business".

Expert data strategist Angelo Tzimopoulos said,

"There’s great need of good project and product management in AI and Data Science as the space is still not mature yet apart from Enterprise businesses. At the moment there are various leads (analytics, data science or data engineering) that are trying to do project management alonside managing the team and developing the practice, which is ok for small organisations, but that doesn’t scale. The leads need to be technical leads and help their teams cope with project work and upskill them in collaboration with a delivery/pm/change function which would be their main role to drive change and delivery.”

The full report can be found here: https://tesseract.academy/tesseract-report-project-management-for-ai-and-data-science

About Dr Stylianos Kampakis

Dr Stylianos (Stelios) Kampakis is a data scientist with more than 10 years of experience. He has worked with decision makers from companies of all sizes: from startups to organisations like, the US Navy, Vodafone and British Land. His work expands multiple sectors including fintech (fraud detection and valuation models), sports analytics, health-tech, general AI, medical statistics, predictive maintenance and others. He has worked with many different types of technologies, from statistical models, to deep learning to blockchain and he has 2 patents pending to his name.

He is a member of the Royal Statistical Society, honorary research fellow at the UCL Centre for Blockchain Technologies, a data science advisor for London Business School and CEO of The Tesseract Academy.

He blogs regularly at https://thedatascientist.com/blog/

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