The democratization of AI: Why it’s time to make the investment

Artificial intelligence doesn't belong to the data scientists any more. As the technology has matured, it's become easier than ever to implement affordable, accessible AI solutions into business workflows. You don’t have to be an expert in the tech — you just need to be an expert in your own operations. And over and over, the success stories from companies that are implementing AI solutions into their workflows prove that the technology has made the leap from sci-fi fantasy to solid solutions delivering real results.

The have and have-not gap is widening

The leap in AI availability and affordability comes just in time. By 2022, 93 percent of companies will have implemented AI and cognitive solutions. That means now is the time to stop waiting and start doing, because companies that don't pilot AI solutions today are falling behind their competitors. The companies that have the best customer experience today, who are growing faster and are more profitable than their competitors, are investing faster in AI, and they’re further widening the gap from laggards, because AI is an accelerant in customer service sophistication and effectiveness.

Where are companies seeing the biggest gains? Because superior customer service is the biggest differentiator today, integrating AI into customer engagement and service workflows offers the biggest leaps in customer acquisition, customer experience, customer support, and front-line employee productivity. And it's easier than ever to integrate these technologies and stay competitive.

Here are just a few of the ways AI is changing customer service, including servicing your own employees.

Customer service chat bots

Today, having an employee answer a phone costs a good amount of money, and that expensive time is often spent on low-value queries that crowd out or leave less time and focus for the interactions that can add real value for a company. But the cost of a bot interaction is just a few cents, and AI unlocks the opportunity here to start engaging more, on a more consistent and more frequent basis, through AI. Think about all those places in a digital customer journey where having a readily available chatbot or virtual assistant can really help deliver better, immediate, and more consistent, customer experience.

For customer acquisition, that means helping a potential customer find the right product, or helping them understand the value of a particular product, service, or solution. In customer service, AI-powered bots can help users track packages, change shipping addresses, or explain warranty information.

Consumers have especially grown accustomed to chatbots in the travel industry. For instance, Thomas Cook, a travel and hospitality company out of the U.K., leverages AI to deliver a consistent experience across all of their channels, including mobile, web, and social, with a chatbot that helps customers locate baggage, flight, and cancellation information, and even answers questions about what terminal you're flying from, whether there are any family offers available, and gives advice about where to go for your next vacation.

Employee-facing service chatbots

On the other side of the counter, in all industries, AI offers a unique opportunity to help customer-facing employees — from bank branches to field locations — who interact with customers and field an enormous variety of complex, sometimes quirky questions. Your customer service employees have a solid grasp of your business of course, but policies change, some issues require more in-depth research, and sometimes more insight is needed.

Currently, that means searching an internal portal or calling headquarters to gain access to the right answer, and that is often time-consuming and sometimes frustrating. AI assistants, or an employee-facing chatbot, can provide that employee with information they need to do their job instantly, reducing operating costs and improving customer satisfaction. Royal Bank of Scotland, for instance, uses internal chatbots in their bank branches to provide contextual and personalized information to their bank employees.

An employee-facing AI chatbot also offers valuable intel about your business and your customer interactions. For instance, if you’re a retailer that has just updated your point-of-sale system, and you suddenly see a flood of questions coming in about how to enter this type of order, or how to process a return with new software, you're getting a real-time view as to what’s happening on the front line of your business through your employees.

Employee-servicing HR chatbots

Internal chatbots can also help employees find things they need for their own work life.

An IT chatbot can help with minor, frequently asked questions – can I install this piece of software, how do I find a file, why isn't my battery lasting as long? It can also automatically open up tickets that require more complex support.

On the HR side, a chatbot can answer questions about vacation policies or tell an employee the number of PTO hours they have left, and field time-off requests. More complex bots can also tackle bigger HR program rollouts. For instance, LogMeIn created a benefits bot called Benny, which leaps into action during the open enrollment period, and can answer any question about the policy, from what's changed to whether the vision plan is a good idea, anywhere an employee can log in, from at your desk to in the coffee shop.

The benefits of implementing AI

Once you implement AI into your customer service workflows, you'll see three immediate benefits. The biggest comes from the cost savings when a customer is serviced by AI instead of a human resource. Some of Bold360's customers report that they've seen a 30-40 percent reduction in inbound call volume, which means they don't need to expand their contact center, hire more people, or outsource. Even as a company grows and the number of customers increases, an AI solution can keep pace.

Then there’s the significant opportunity for increased conversion. An always-on bot can engage with more customers, and improve conversion levels, because it can do more sophisticated qualification, or can simply offer a better customer experience overall, at any time of the day – and so you're not missing those customers who come through after business hours, and you’re not spending money staffing call centers in different time zones.

It means that the phone lines and chat channels don't get jammed during big sales or busy holiday periods, and you can engage every customer that comes to your website, because you’re not limited by the number of human agents.

The last opportunity centers on the quality of customer experience, particularly in boosting net promoter scores or customer satisfaction scores. The AI is always available, consistent, and immediate, offering a high-quality experience. This often means you can eliminate slower, clunkier legacy channels of engagement like email.

Your road map to implementation

While implementation is easier than ever, there are a couple of key points to consider. The first is to know the problem you want to solve and make sure it’s a problem that the organization is interested in or excited about. Approach it as a business case, rather than a laboratory or pilot program, because it's not about validating whether the tech will work, but rather validating the problem you’re solving, how you’re going to measure it, and then setting a time frame and making it measurable.

Secondly, don’t wait too long to measure results. Set a three-month measurement point and then run aggressively toward that goal. You may course-correct after three months, and you may refine up until six months, but typically within six months, companies are seeing run rate success, and they’re getting positive ROI. If you’re not seeing positive ROI after six months, you should probably question if you’ve, A, chosen the right solution, or B, chosen the right problem.

After you get to that three-to-six-month point, determine the next problem to attack. That will also help you with putting proper boundary conditions around what you’re going after. It’s about determining ‘what am I going to do in this first implementation, and then what will I do in my second, and what will I do in my third’?

Thirdly, think about AI implementation as stepwise functions, where you’re approaching goals in three-to-six-month increments in one use case, but then continue to find the next use case and the next use case and the next use case. Use cases can also be wildly different. It could be, hey, we want to address these four problems in our customer experience, or in our employee experience. They can be adjacent issues. But they should be, once again, bounded and measurable.

The two big mistakes to avoid

Once you define your AI project, the most essential step is to make sure you have the right stakeholders at the table. The people and process part of this is just as important as the technology or the solution. In other words, don't only have a technologist or IT person – which many companies make the mistake of – but get marketing, sales, and the customer success team on board, because they need to be involved in everything from content creation to workflow mapping to what happens when a bot can't solve a problem.

Getting ahead of the changes your AI solutions will make is also critical, and too often, this is not thought of till you’re very far along. This means creating new roles and identifying new responsibilities that that no one owns today, but someone will need to own soon. These can range from managing and curating the bot's information – because it's only as good as the content that's put into it– to training your human agents, to handling the business process of implementing AI and managing it as it grows and learns across your organization.

Companies that offer better customer experience, 24/7 support across every channel of engagement, and effective, automated replies are investing in AI. They’re the companies that are gaining superior traction, as AI continues to keep them ahead of their competitors. AI isn't a seven-figure investment any more – it's time to launch your own AI strategy.