Artificial Intelligence is everywhere, but it may not be as advanced as some think it is. According to a Fivetran survey, only 14% of organisations consider their AI maturity ‘advanced’.
‘AI vital to business survival, but not yet trusted’
Artificial Intelligence (AI) is no longer a buzzword. Year-by-year, it has progressed into a full-timer in the world of recruitment technology. That notion is backed up by the fact that 87% of organisations consider AI vital to their business survival, according to a recent Fivetran survey. But there’s a flip-side to its future importance. The same survey found that across 550 senior IT and data scientists only 14% of organisations consider their AI maturity ‘advanced’. In a nutshell, it means that only 14% uses general purpose AI to automatically make predictions and business decisions.
86% say they would struggle to fully trust AI to make all business decisions without human intervention.
Meanwhile, there is still a lack of trust when it comes to AI usage. 90% of respondents report their organisations continue to rely on manual data processes. 86% say they would struggle to fully trust AI to make all business decisions without human intervention. More than two in five respondents (41%) said there was ‘vast room for improvement’ in how their organisation used AI. That number lies even higher among US respondents: to 64%.
‘Significant gaps in efficient data movement’
The quality of data is a big issue, according to the report. It leads to 71% saying they struggle to access all the data needed to run AI programs, workloads and models. Meanwhile, 73% find each of the stages of extracting, loading and transforming the data, to translating it into practical advice for decision-makers a challenge
“This study highlights significant gaps in efficient data movement and access across organizations. A successful AI program depends on a solid data foundation. Starting with a cloud data warehouse or lake as its base”, said George Fraser, CEO of Fivetran. “Analytic teams that utilise a modern data stack can more readily extend the value of their data and maximise their investments in AI and data science.”
AI talent is being under-utilised
As data scientists are as scarce as they come — it seems they are far from utilised correctly, the survey found. In all, 87% of organisations agree with the notion that their data scientists were not being utilised to their full potential. The problem lies mainly on the data side of things, as per the report. “The prevalence of low-quality, siloed and stale data means that data scientists, who are employed by all large organisations surveyed, dedicate less than a third of their time to building AI models. Instead, they spend the majority of their time on tasks outside of their job role.”
