Retail leads global AI spend

Global artificial intelligence (AI) spending will reach nearly $50 billion this year, according to new figures from the International Data Corporation (IDC).

This marks a 44% increase from 2018, and forecasts suggest that spending on AI systems will more than double to nearly $108 billion by 2022.

Retailers are leading the way in AI investment, with a projected spend of $8 billion on solutions such as automated customer service agents, product recommendation and shopping advisers. With e-commerce sales driven by personalisation and customers demanding better consumer experiences, retailers are looking to AI for solutions.

59% agree AI will help them better identify prospective customers

The banking sector is also likely to invest big in AI this year, with an estimated spend of $7.7 billion going towards cybersecurity technology such as automated threat intelligence and prevention systems, fraud analysis and investigation. Other big AI spending sectors this year, according to the IDC, will be discrete manufacturing, healthcare providers and process manufacturing.

Looking at specific technologies, automated customer service will see the biggest investment this year, followed by sales process recommendation and automated threat intelligence and prevention

As well as helping with personalisation and customisation, AI can also be used by marketers to boost the effectiveness, revenue and targeting of a campaign. According to research by EverString and Heinz Marketing, more than 30% of B2B marketers believe AI will enable more detailed insight and analysis of campaigns. Meanwhile, 59% agree AI will help them better identify prospective customers.

Marketers clearly recognise the benefit of AI, however just 9% have a hyper-personalised strategy (i.e. one that leverages AI and real-time data) in place. A recent study by Ascend2 also revealed that 62% of marketers questioned are still only talking about hyper-personalisation (not yet acting on it). Those surveyed had made improving the customer experience and applying data insights their key priorities for putting hyper-personalisation into practice.

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