We’ve been discussing the role of artificial intelligence (AI) in customer service a lot recently, and we’ve introduced many ways small and midsize businesses (SMBs) can prepare to get in the game.
Here’s a quick recap for those just joining us:
- We’ve discussed ways SMBs can improve the service experience they offer by implementing AI-powered virtual customer assistants.
- We’ve looked at the readiness of customer service chatbots (a closely related technology) and,
- We’ve explained how SMBs can begin laying the groundwork now for a successful future AI implementation.
In this report, we look at a handful of predictions from Gartner analysts on the role AI is expected to play in the near future—through the year 2020.
While these predictions were originally tailored for an enterprise audience, we’ll look at them through the eyes of an SMB customer service department.
Note: These predictions come from Predicts 2017: Artificial Intelligence (content available to Gartner clients.)
4 Predictions for the Next 3 Years
“By 2019, more than 10% of IT hires in customer service will mostly write scripts for bot interactions.”
Importance to SMBs: This is so important and relevant to SMBs that we’ve already looked at how to prepare for the production of chatbot scripts. And, it’s much easier than it sounds, because the first step is to improve your organization’s knowledge management systems and processes.
Effective knowledge management is the key to an efficient, effective customer service team. So much so, in fact, that it’s often included as one of the central applications within a customer service software suite.
“By 2020, 20% of companies will dedicate workers to monitor and guide neural networks.”
Importance to SMBs: This is less important. Neural networks are the behind-the-scenes algorithmic processes that allow AI applications to process information and learn from experience. But, it’s likely that most SMB will use off-the-shelf AI applications, or rely on open-source solutions, and will not need to manage their own neural networks.
The exception, of course, will be with SMBs that compete in the AI space. If it’s hard for you to imagine a small company competing in a field such as AI, then the next prediction might surprise you.
“By 2019, startups will overtake Amazon, Google, IBM and Microsoft in driving the artificial intelligence economy with disruptive business solutions.”
Importance to SMBs: This will be important to be aware of, especially for early adopters. Currently, most of the activity in the AI development space is from the big—really big—names in tech.
While it is currently possible to design a ground-up AI service implementation using tools and platforms provided by the likes of Google, Amazon and Microsoft, the best solutions are yet to come. They’ll come from startups that identify a business need and a compelling use of AI tech to meet them. In many cases, these solutions will be built upon the AI platform technologies that the big names are developing now.
“By 2019, artificial intelligence platform services will cannibalize revenues for 30% of market-leading companies.”
Importance to SMBs: While this prediction won’t directly affect the average SMB, the implications and knock-on effects could. AI tech is developing so quickly that it’s likely to outpace even some of the large enterprises that are funding its development.
For SMBs, the resulting volatility could complicate platform selection. For SMBs offering AI platform integration services and AI solutions for end users, the resulting market shake-ups will present many new growth opportunities.
Suggestions for Planning Ahead
Before committing to any plan of action, make sure you’ve fully assessed and understood the potential for AI tech to disrupt and/or support your business model.
FOMO (fear of missing out) is only helpful as an incentive to begin researching new technology. It should never be used as a motivation to make an uninformed purchase or strategy decision.
We’re still decades away from AI that will be able to respond to unstructured queries outside of very limited contexts. Until that time arrives, customer service AI applications will continue to rely on human input for training, modeling and refinement.
Customer service inquiries and responses, whether from scripts or actual interactions, can all be used to speed up the training, modeling and refinement process.
SMBs can begin today by taking small steps toward improving their customer service offerings. Even if AI technology were to fizzle out, these small steps will still increase a company’s competitiveness by improving the quality of the human-powered service it offers.