New research from Capgemini calculates a more than $300 billion opportunity for those retail companies that are able to scale and expand the scope of their artificial intelligence (AI) existing deployments.

However, it is not straightforward, as the report also found that just one per cent of use cases by retailers have achieved this level of deployment today.

The Capgemini Research Institute looked at 400 global retailers that are implementing AI use cases at different stages of maturity - a group that represents 23 per cent of the global retail market by revenue - along with analysis of public data from the world’s largest 250 retailers by revenue.

The report revealed that AI deployments saw a seven-fold increase over the last two years. Over a quarter (28 per cent) of retailers are deploying AI today, a significant increase from 2017 figures (17 per cent), and seven times that of 2016 figures (four per cent).

It found that 98 per cent of respondents using AI in customer-facing functions said that the number of customer complaints has reduced by up to 15 per cent, while 99 per cent said AI increased sales by up to 15 per cent.

This marks a significant change from 2017, where respondents gave widely contrasting returns from zero, to more than 15 per cent, to ‘don’t know’. In both business cases, zero respondents reported that they could not quantify AI’s benefit.

Meanwhile, 71 per cent of retailers said AI is creating jobs today, with 68 per cent of the jobs being at coordinator level or above. However, three-quarters declared that AI has not replaced any jobs in their organisation so far, while those who did say jobs have been cut put the number at 25 or lower.

The Capgemini Research Institute analysed 43 working use cases for AI, finding that there is a lack of focus on simple, customer-centric deployments. This lack of scalability is likely caused by retailers focusing on more complex, higher-return projects.

Retailers developing AI were eight times more likely to be working on high-complexity projects than ‘quick win’ projects that are easier to scale. Deployments to date have also lacked a focus on customer usability: the driving forces behind current AI implementations are cost (62 per cent) and return on investment (ROI) (59 per cent), while customer experience (10 per cent) and known customer pain points (seven per cent) are significantly lower priorities.

Only 26 per cent of AI use cases today are operations focused, but these were among the most profitable in terms of cost returns. Standout examples included using AI for procurement tasks (averaging 7.9 per cent ROI), applying video analytics and image detection algorithms for detecting in-store stealing (7.9 per cent) and optimising supply chain route plans (7.6 per cent).

The research showed companies in 2018 have adopted more realistic expectations, with those claiming that they have the skills needed to implement AI have now dropped from 78 per cent in 2017 to 53 per cent today. More than eight out of ten retailers in 2017 were confident that their data ecosystem for implementing AI was prepared, while again this dropped to 55 per cent in 2018.

Kees Jacobs, vice president for global consumer products and retail sector at Capgemini, said that it appears reality has kicked in regarding AI, both in terms of what the technology can achieve and what retailers need to do to get there.

“Our research shows a clear imbalance of organizations prioritizing cost, data and ROI when deploying AI, with only a small minority considering the customer pain points also – these two factors need to be given equal weighting if long-term AI growth, with all of the benefits it brings, is to be achieved.”

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