Survey shows organisations’ AI capabilities lag far behind ambitions

Fivetran has published the results of a survey which shows that while 87 percent of organisations consider artificial intelligence (AI) vital to their business survival, 86 percent say they would struggle to fully trust AI to make all business decisions without human intervention. 90 percent of respondents report their organisations continue to rely on manual data processes.

Conducted by Vanson Bourne, the online survey of 550 senior IT and data science professionals across the US, UK, Ireland, France and Germany also found that only 14 percent of organisations consider their AI maturity “advanced” – meaning that they use general purpose AI to automatically make predictions and business decisions. More than two in five respondents (41 percent) conceded there was vast room for improvement in how their organisation used AI.

“This study highlights significant gaps in efficient data movement and access across organisations. A successful AI programme 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.”

Inefficient data processes curtail AI advancements and revenue gains

Organisations appear to be laying the foundation for more sophisticated AI projects and plan to invest 13 percent of their global annual revenue into them within the next three to five years – compared to the eight percent being invested today. Almost all of the organisations surveyed already collect and use data from operational systems, but their ability to use this data for AI models is hampered by deep-running data challenges:

71 percent struggle to access all the data needed to run AI programmes, workloads and models

At least 73 percent find each of the stages of extracting, loading and transforming the data, to translating it into practical advice for decision-makers a challenge

Such inefficient data processes force companies to rely on human-led decision-making 71 percent of the time. Organisations in the UK and Ireland had the highest average proportion (77 percent) of decisions made by people rather than technology. Underperforming AI programmes are also hitting organisations financially, with respondents estimating they are losing out on an average of five percent of global annual revenues because of models built using inaccurate or low-quality data.

AI talent is left untapped

The prevalence of low-quality, siloed and stale data means that data scientists, employed by all large organisations surveyed, dedicate less than a third of their time to building AI models, spending the rest of it on tasks outside of their job role. Organisations in the UK and Ireland perform the worst in this regard, with data scientists spending, on average, 77 percent of their time on preparing data.

As a result, 87 percent agree that data scientists within their organisation are not being utilised to their full potential. Yet, recruitment is cited (by 39 percent) as the biggest barrier to AI adoption, highlighting the responsibility of organisations to urgently empower the talent they already have.