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This article was written by Troy Gedlinske (CDI’s Expert in Residence) along with US-based colleagues at CDI. This is the first article in a series designed to help CS leaders develop a realistic, effective Conversational AI strategy.
Through all the hype and hyperbole about AI, one big truth stands out: AI is transforming Customer Service as we know it. As a CS leader, how can you craft an AI strategy without getting tripped up by all the little lies?
First, don’t forget all the little truths you’ve learned/earned over the years: about the real cost of technology investment, about managing change and risk, about starting small and following fast. Your experience matters more than the futurologists like to admit.
Second, develop a “good enough for now” understanding of AI technology, focusing on the killer app that will soon be central to CS operations: the AI-powered chat or voice bot.
Third, lean into the five pillars of Customer Service (Quality, Finance, Scale, Flexibility, Risk) to frame how you think about AI. This tried-and-true methodology for measuring/monitoring performance should be central to your AI strategy.
Finally, get advice from people who know what they’re talking about. Find an expert who can answer your questions and help you craft an AI strategy that makes sense for you and your org.
Everybody is talking about AI. If you’re of a certain age, this may remind you of the heady dotcom days, which even had their own clever IBM commercials that were more about selling a mindset (and rebuilding a brand) than a specific product or service. But one truth cannot be denied: Conversational AI is transforming Customer Service as we know it.
Indeed, this transformation is happening so quickly that it’s hard to define – especially in the actionable, quantifiable terms CS leaders need to make decisions. It doesn’t help that the big truth about AI is polluted with big promises also reminiscent of the dotcom boom, e.g., AI makes everything you know irrelevant; AI can solve every problem; if you aren’t using AI today, it’s already too late. And so on.
As a CS leader, this presents you with a dilemma. You know AI is transforming CS, and you’re under pressure to come up with a strategy. What do you do?
As an experienced CS professional, I’ve been working with my colleagues at CDI on a way to reframe how CS leaders should think about AI and its operational impact. What has emerged is a flexible framework worthy of a detailed discussion, but easily summarized in these four simple steps:
AI will eventually change the world, but it's unwise to forget certain facts that are still relevant today, including:
Technology investment is expensive in terms of money, time, confusion, and opportunity costs. And new technologies are always more expensive than anyone imagines, especially their most ardent (and often self-interested) proponents.
The risk of waiting is often smaller than we think, especially compared to the risk of jumping in. Of course, we should plan for an AI future. But we must also be disciplined in the face of herd FOMO when the actual risks of implementing AI at scale is still TBD.
Starting small is often your best bet for minimizing your downside risk and preparing you to move quickly when your initial bets pay off. In the challenging and chaotic realm of business strategy, following fast is the closest thing to having your cake and eating it too.
The goal here is to be conversant – to have enough understanding to ask the right questions of the experts advising you. That said, it may help to go a little deeper on the killer app that will soon be central to CS operations: the AI-powered chatbot or voice assistant.
In particular, it will help to understand the difference between bots powered by LLMs (like ChatGPT) and their more conventional, ready-for-scale predecessors, as this topic is likely to feature in and possibly confuse your AI strategy discussions.
Your mastery of the art and science of monitoring and managing Quality, Finance, Scale, Flexibility, and Risk probably hasn’t earned you a TED talk, but it has helped you outperform your peers and sleep well at night (most of the time).
Don’t abandon this tried-and-true methodology under the assumption that “everything is different”. Instead, put the five pillars at the center of your Conversational AI strategy and vet every investment, including POCs and pilots, against their impact on what really drives your CS operations.
Your instinct is correct: AI adoption is being driven more by FOMO than fundamentals. And your confusion about the underlying technology puts you in very good company (even though not everybody wants to admit it).
The good news is that there are experts available to answer your questions and fill in the details. Find one or two who are honest about the current state of AI, then leverage them to craft an AI strategy that makes sense for you and your organization.
This article is an introduction to a hands-on workshop program designed exclusively for CS leaders at the VP level and above. To learn more about CDI’s suite of workshops offerings, you can contact Ben Taylor ([email protected]), CDI’s Global Head of Sales.
