According to data collected from attendees at Dataiku’s June 2022 Everyday AI Conference in London, while the ability to extract insights from data still lives largely with data teams or data-centered roles, the needle is moving towards Everyday AI.
According to data collected from attendees at Dataiku’s June 2022 Everyday AI Conference in London, while the ability to extract insights from data still lives largely with data teams or data-centered roles, the needle is moving towards Everyday AI*.
Although 69% of respondents said their data teams (or specific people in data-centered roles) are empowered with adequate tools and training to extract insights from data, a further 40% said the same about people in other business roles — without “data” or “analyst” in their job titles.
The numbers mark a change from the last time Dataiku conducted similar research at its 2019 conference in London, where attendees were asked “Who is responsible for extracting insights from data at your organization?”. In this instance, 48% said only data teams are responsible, while only 14% said it’s the combined responsibility of data teams and non-data-specific roles.
The research was conducted live at the 2022 Everyday AI Conference in London with attendees from a number of industries. Among the 200+ respondents, 41% percent identify as data practitioners on the technical side, 33% as data or analytics-focused managers, executives, or C-level executives, and 12% as data practitioners on the non-technical side.
Thirty-seven percent of survey respondents said they had formal training and education (including certification programs) to help with their understanding of the role data, machine learning, and AI play within their business, with a further 37% saying they had recommended reading, self-guided learning, or similar. Twenty-two percent of respondents said they had mentor or buddy programs.
Still, Work to Do on Responsible AI
While the move towards Everyday AI since 2019 is encouraging, a significant number of attendees indicated that there is still work to do. Nearly a quarter (23%) of respondents said, “I know we don’t do anything to proactively ensure we’re building Responsible AI.” Another quarter (25%) said, “I don’t know or am not sure what we’re doing to address Responsible AI.”
Shaun McGirr, RVP of AI Strategy – EMEA at Dataiku, says the results are reflective of both the progress Dataiku is seeing and the still untapped potential of Everyday AI for enterprises:
“More than 700 data leaders and practitioners from the world’s top global companies attended Everyday AI London, along with 40 industry-leading speakers, and we certainly got to hear how businesses are leveraging data with Everyday AI. However, there is still work to do if enterprises want to see a deeper transformation and truly data-driven business results. Everyday AI must become a reality for non-data focused roles, as well as data scientists and data analysts.”
From a hands-on point of view, the survey results also showed that 45% of respondents identified either “data cleaning, wrangling, or exploration” or “connecting to data, data ingestion” as their top challenges and time resource commitments.
Want to find out more about Dataiku’s Everyday AI conference in London? Read the takeaway blog here: https://blog.dataiku.com/everyday-ai-london.
* “Everyday AI” is the concept pioneered by Dataiku of helping everyone in an organization—from technical teams to business leaders—use data to make better decisions and drive business value on a daily basis.
