With pressure on businesses to differentiate on the basis of the experiences they offer their customers, the option to use artificial intelligence (AI) to improve experiences seems obvious. With AI, businesses can automate back end processes, parse through the huge quantities of data to pinpoint insights and lighten the load of customer support.

But as some well-publicized AI failures have proven, successfully implementing AI — as with any technology — requires a well thought out plan, strategy and alignment with business objectives. In a recent Tweet Jam, we discussed the ins and outs of successful AI implementation in the customer experience realm and debated where and where not to introduce AI. 

Where to Get Started With AI?

"Artificial intelligence" can refer to a broad range of capabilities, both internal and external-facing, all of which can improve the experiences companies deliver their customers. So where is a good place to start for a business exploring its options the first time? While the participants didn't necessarily agree, they did have a lot of advice to share.  

Should Any Areas Be Off Limits for AI?

While we've heard the high praises of AI sung for a few years now, guess what: it still is no substitute for humans. 

Artificial intelligence can augment, aid, amplify and automate certain tasks, complex problems still require human intervention. The trick is knowing when and how to do a smooth hand off.

CX Priorities: Where Does AI Land?

The speed with which new software is introduced is putting even the most seasoned companies to the test. So if a company is still struggling to refine its customer experience strategy, should it dip its toes into the AI waters or hold off? The participants disagreed as to timing, but all agreed that any AI initiative needs a solid data foundation to rest on and clear issues it is tasked with solving. 

Learning Opportunities

The AI Skills Question

Although the "War for Talent" was first declared by McKinsey in 1997, the term rings true today, at a time when demand for analytical skills and data scientists outpaces the supply. The ideal candidates balance a deep knowledge of statistics, machine learning and coding with an understanding of business needs, the customer demands and more. Whether to train one (or multiple) employees in house or to hire depends on the talent available.  

Can the Real AI Please Stand Up?

There's a phenomena that happens as a technology or term ascends to the peak of inflated expectations in Gartner's hype cycle: the higher it gets, the louder the marketing chatter gets. When capabilities that previously could be handled in an Excel spreadsheet are suddenly called "artificial intelligence," what can businesses exploring their options do to tell fact from fiction? The overwhelming answer was: do your homework. Ask for case studies, references, customer contacts and more. 

Balancing Cost Savings and Customer Happiness

One of the many benefits AI has been associated with is in the cost savings resulting from automation of processes, introduction of chatbots and more. However entering into an AI initiative for cost savings alone will cost you customer. Handled properly, AI can deliver cost savings while improving customer satisfaction by supporting more self-service options, improving decision support and more. 

Testing AI's Limits

In "The Business of Artificial Intelligence," MIT's Erik Brynjolfsson and Andrew McAfee posited that "In the sphere of business, AI is poised have a transformational impact .... The bottleneck now is in management, implementation, and business imagination." When asked if businesses suffer from a lack of imagination when it comes to AI's use, the participants responded with an overwhelming "no."