November 17, 2017
Businesses exploring potential of AI to improve customer experience and the bottom line
Despite the growing interest in the potential of artificial intelligence, there is a sense of confusion amongst business leaders about how it is being used and how to take advantage of its potential. Independent research from SAS claims that while nearly two-thirds (65 percent) of business leaders are convinced AI can generate value for their business, nearly half (46 percent) are being held back by concerns around AI still being in its infancy. Nearly a third (30 percent) of companies are not sure if they are ready for the technology, citing concerns over a lack of required skills (66 percent), ROI (55 percent) and fears over stories of AI malfunctioning (38 percent). Many also expressed reservations over the cost of solutions (39 percent) and lack of trust in the technology (36 percent), reinforcing fears that AI would not deliver sufficient ROI.
Yet, despite the misgivings that impede its implementation, businesses are broadly ramping up their investment into AI and expanding its use to enhance customer-facing services, often without realising it. More than three-quarters (77 per cent) of businesses claim to be actively using AI in marketing, communications or customer service. Of those that don’t currently use it, 37 per cent are planning to adopt the technology within the next two years.
“Whether we realise it or not, AI has already arrived. From financial services to retail, AI has become more commonplace and we are seeing its use progress from solely back-office support to increasingly front-end, customer-focused roles,” said Peter Pugh-Jones, Head of Technology, SAS UK & Ireland. “With the ability to unlock accurate insights from vast amounts of data – in near real-time where required – AI is the key to providing the exceptionally responsive and personalised experiences that customers are demanding and businesses are seeking to deliver.”
Almost two-thirds (62 per cent) of millennials admit they would gladly use automated customer service systems if they provided a better or quicker service. And nearly a quarter (23 per cent) of consumers would be happy to let robots choose, purchase and deliver gifts to their friends and family at Christmas. To meet customers’ expectations, AI is being used to analyse massive volumes of data and supplement consumer-brand conversations. In total, 41 per cent of businesses are using AI-enabled chat bots to respond to common customer service requests and engage with customers more frequently and on-demand but without increasing labour costs.
AI is also becoming the computerised extra that aids businesses in drawing insights from large amounts of customer data and use it to build meaningful relationships and personalised experiences. Nearly a third (30 per cent) are using AI to proactively interact with customers based on their behaviour and mood. A larger proportion (36 per cent) are using AI to build more meaningful relationships with their customers by targeting them with relevant messaging and offers at the right moment, and even predict how their customers will respond or act. With the ability to analyse large datasets concerning the digital footprint of individual customers, AI can translate the results into natural language to provide a human-like medium for meeting customer expectations on-demand.
However, to use AI effectively requires good sources of data and proper data management processes in place. With the velocity and volume of customer data increasing, organisations need to use advanced analytics to automatically derive insights from historical data and use it to predict what is likely to happen in the future. Reflecting this, over a third (37 per cent) of businesses believe analytics provides the data to enable AI systems to respond in the moment.
“We can now generate what was once unimaginable volumes of data of all varieties, and even apply analytics to that data as it is being generated. However, the concept of machine learning where we programme machines to understand, learn and improve algorithms applied to that the data is not a new one,” said Pugh-Jones. “However, what’s needed to take AI and machine learning to the next level is a scalable, advanced analytics platform, where accurate insights can be quickly extracted from all the data. This gives organisations both the fuel and the engine to begin experimenting with AI and successfully explore the boundaries of what is possible.”