The hype surrounding artificial intelligence (AI) is intense. But for most European businesses surveyed in a recent study by SAS, the leader in analytics, AI adoption is still in the early or even planning stages.

The good news is, the vast majority of organisations have begun to talk about AI, and a few have even begun to implement suitable projects. There is much optimism about the potential of AI, although fewer were confident that their organisation was ready to exploit that potential.

It isn’t so much a lack of available technology slowing AI adoption; most attest that there are many options available. More often, the challenges come from a shortage of data science skills to maximise value from emerging AI technology, and deeper organisational and societal obstacles to AI adoption.

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These were some of the findings of the Enterprise AI Promise Study, a phone survey of executives from 100 organisations across Europe in banking, insurance, manufacturing, retail, government and other industries. The SAS study was conducted in August to measure how business leaders felt about AI’s potential, how they use it today and plan to use it in the future, and what challenges they face.

Societal challenges

55% of respondents felt that the biggest challenge related to AI was the changing scope of human jobs in light of AI’s automation and autonomy. This potential effect of AI on jobs includes job losses but also the development of new jobs requiring new AI-related skills.

Ethical issues were cited as the second-biggest challenge, with 41% of respondents raising questions about whether robots and AI systems should have to work “for the good of humanity” rather than simply for a single company, and how to look after those who lost jobs to AI systems.

Data science team and organisational readiness

Are organisations’ data scientists ready for the challenge of emerging AI? Only 20% felt their data science teams were ready, while 19% had no data science teams at all.

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Recruiting data scientists to build organisational skills was the plan for 28% of respondents, while 32% said they would build AI skills in their existing analyst teams through training, conferences and workshops.

Additionally, trust emerged as a major challenge in many organisations. Almost half of respondents (49 per cent) mentioned cultural challenges due to a lack of trust in AI output and more broadly, a lack of trust in the results of so-called “black box” solutions.

Platform readiness

The study also sought to assess AI readiness in terms of infrastructure required. There was a contrast between those respondents who felt they had the right infrastructure in place for AI (24%), and those who felt they needed to update and adapt their current platform for AI (24%) or had no specific platform in place to address AI (29%).

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“While it is increasingly used as an industry buzzword, artificial intelligence has truly astounding potential. When implemented correctly algorithms will be able to perform human tasks automatically like never before,” said Peter Pugh-Jones, head of Technology, SAS UK & Ireland.

“While many organisations are still in the early or even planning stages of adopting AI, it will be those that harness the power of this technology that will not just survive but thrive in the future.”

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