Virtual assistants and robo-staff are quickly becoming reality. But companies walk a fine line between highly customized experiences based on analysis of customer data and appearing intrusive.

Artificial intelligence has been around since the early days of computers. In the 1960s, computers were called “electronic brains,” underlining the idea that machines could have a form of consciousness. Brands have only recently started adopting artificial intelligence for core consumer services.

How good is AI? Google’s voice recognition technology now claims 98 percent accuracy and Facebook’s Deep- Face is said to recognize faces with a 97 percent success rate. IBM’s Watson, which uses artificial intelligence to perform its question-answering function, is 2,400 percent “smarter” today than when it achieved victory on Jeopardy! six years ago.

The relationship between humans and machines is changing, and brands are on the cusp of making artificial intelligence an everyday element of their customer offerings.

Does data know it all?

When a brand integrates AI into the fabric of its core data, the information it can access is much richer. But this poses questions about what a brand should do with that data. Is it ethically appropriate? And can marketers retain trust? In their attempts to demonstrate deep knowledge of customers, companies need to know where their efforts cross into “creepy” territory. If integrated technology runs loose with customer data and begins making its own judgments, there’s a risk of customers feeling a level of intrusion they didn’t necessarily sign up for.

If businesses can strike the right balance between adhering to their brand values while allowing AI to access the right amount of data, the results can be cost-effective and deliver real-time personalization that may not be possible via human observation. However, industry research still indicates that when customers want to complain or talk through a complex situation, not surprisingly, they want to talk to a human.

Hospitality is one sector thinking boldly about the opportunities in AI. Luxury hotel portfolio Dorchester Collection is using AI to identify what guests want, not what marketers think they want. To enhance its customer experience, it is using a special platform that allows it to displace standard hospitality-industry measurement techniques such as mystery shoppers and customer- satisfaction surveys. Instead, they’re tapping directly into digital customer feedback.

The concierge is always available

Also in the hospitality industry, hotel brand Hilton has made AI a key part of the customer experience at the Hilton McLean in Virginia. In partnership with IBM, Hilton is using Connie, the hospitality industry’s first Watson- enabled robot concierge, to cater to guests’ needs for information about the hotel and the surrounding area.

Connie gives consumers quick access to personalized information through cognitive reasoning and robotics. Hilton argues that Connie enhances the customer experience. Examples of guest interactions with the robot include business travelers asking Connie for directions to a conference room or a family asking when the pool closes.

AI is being used across sectors to improve efficiency, reduce costs, increase revenues and boost customer satisfaction by improving on key areas of customer experience. According to Calum Chace, author of “Surviving AI,” this is an interesting time for AI: “In the past few years, machines have got better than us at recognizing images, particularly faces, and recognizing speech,” he says. “Those abilities mean we won’t have people in call centers for long — machines will also be widely responding to requests at hotel reception desks and personal inquiries in all sorts of on- and offline environments.”

The best examples of AI integration are those that use artificial intelligence to augment human capability, generating trust in the technology because it is designed to preserve security and privacy. This requires that intelligent algorithms don’t perform in a black box, creating transparency and opening their work up for inspection.

Here are a few more examples of companies that are using AI to enhance customer experience:

Fukoku Mutual Life Insurance:

Japanese insurance firm Fukoku Mutual Life Insurance is replacing its 34-strong workforce with IBM’s Watson Explorer AI. The artificial intelligence system will calculate insurance policy paypouts which the firm believes will increase productivity by 30 percent and save roughly 140 million yen a year in salaries. The Watson-based system will analyze medical certificates, surgery and procedure data and hospital stays, then calculate the relevant payout.

Royal Bank of Scotland:

Earlier this year, RBS announced the launch of Luvo, a natural language processing AI bot that will answers RBS, Natwest, and Ulster Bank customer questions and perform simple banking tasks like money transfers. If Luvo is unable to find an answer, it will pass a customer over to a staff member.


Food brand Knorr has used cognitive technology, a component of AI, in its recent “Love at First Taste” campaign. A “Flavor Profiler” integrated into the brand’s site offers tailored recipes. Behind this effort is a cognitive engine that can interact with visitors “naturally.” Consumers also learn which recipes suit them best, based on their individual flavor profiles.

Under Armour:

Sports apparel brand Under Armour’s Under Armour Record fitness app integrates machine learning technology to get under the skin of users. The app analyzes personal food, exercise and sleep data in combination with insights from other anonymized members of the community, providing timely advice and motivation.

These examples show that while AI isn’t the sole driver of customer experience — and may not be for the foreseeable future — it’s becoming a key component in a personalized, always-on, efficient experience for consumers across many segments. Where companies are striking the right balance, AI can be a win-win-win for businesses, staff and consumers alike.

If you’re interested in AI, Machine Learning and Data Strategy, uncover even more opportunities at THINK 19. Early-bird discounts apply through October 31. Interested attendees are encouraged to register now, while early-bird discount pricing is still in play. Rates go up on November 1 and will continue to increase in the months leading up to the conference. Special discounts are also currently available for groups of four or more attendees. Visit the THINK site to learn more. Or better: Register now!