Jonathan Rosenberg, CTO and Head of AI at Five9
Generative AI is poised to transform every interaction a brand has with its customers. The combination of AI intelligence and human empathy offers endless opportunities to create more fluid customer experiences – from providing consumers with real-time recommendations and guidance to helping human agents triage and prioritise the most complex cases and summarise customer queries more effectively.
While AI is a top priority for 2024 tech investments, to deliver real value it must be implemented with practical outcomes in mind. Next year, it’s imperative that business leaders devise implementation plans in which the customer experience underpins every decision. So, let’s delve into the five common AI implementation pitfalls that leaders should be aware of, as well as strategies to help mitigate them.
1). View AI investments as a productivity enabler.
When incorporating AI into any organisation, many see it as another stand-alone tool that can be bolted onto an existing tech stack.
Let’s take the example of a contact centre. In practical terms, adding conversational IVAs to your contact centre means adding a new ‘digital workforce’ that can collaborate with your agents and deliver service alongside them. This goes beyond simply deploying new software. AI transforms how work is done and creates the opportunity to re-think the purpose and role of the contact centre.
For example, if AI handles the bulk of transactional calls, can your live agents focus on proactive, outbound service? Do they become sales agents as well as service agents? There can be a huge snowball effect of offloading swathes of work to AI that can free up employees to become an entirely new, more productive workforce.
2). Look beyond the buzzwords.
While it’s easy to get swept up in the hype, it’s also critical that any plan for AI deployment contains a clear vision, with achievements and aims outlined as well as metrics for success. Leaders must ensure they’re measuring success against metrics that are aligned with their unique business needs. Whether that’s more accurately routing calls, improving call handle time, or completely automating certain tasks, make sure you can provide proof points and customer references to back up any ROI claims.
At the same time, remember that AI itself does not create better CX. Ensure you understand exactly what the customer will experience because of AI adoption and how you’re going to measure its impact along their journey. Work with a tech vendor that can help you understand the impact at every stage.
3). Take a collaborative approach to AI deployments.
While AI is helping brands achieve amazing things, it isn’t magic and mistakes can happen. AI relies on constant learning and uses models to train and improve outcomes. When deploying AI solutions, consider how the technology handles mistakes.
How is it trained, and who is responsible for training it? Can it work in real-time, and does it provide staff oversight to ensure accuracy? For example, if AI is creating automatic call summaries, human employees should be able to quickly review a summary for accuracy before it’s placed in the CRM. This step ensures accurate information and helps the AI learn and continually improve.
4). Be transparent with both staff and customers.
AI is transformational in all senses, bringing about change for employees and customers alike. There has been a lot of speculation and fearmongering over the impact of AI on employees, so it’s important to counter this by communicating that AI is not designed to replace humans but to collaborate with them and free up their time to engage in more valuable customer interactions.
Walk your employees through the changes AI will create and bring them in on the process, being clear about why it is being adopted and the benefits it will offer their day-to-day role. AI provides many benefits, but it can never replace the empathy and kindness that your people have to offer your customers. You should also include your customers in this change management. Let them know you’re creating new ways of engaging with them and offer the opportunity for feedback. Acknowledge that AI isn’t perfect and let both staff and customers know that you’re working to continually improve it.
5). Don’t rush the tech vendor selection process.
Not all AI technologies are built equally. While almost all vendors in the CX industry will showcase AI as an essential element of their cloud solutions, maturity levels can differ across the board. Not all models are malleable or offer the flexibility required to scale and promote growth.
A good starting point is to look at the conversational AI technologies a vendor offers. Note whether there is scope to switch between the vendors, such as Google Dialogflow, IBM Watson, Amazon Lex, to assess how easily you’ll be able to take advantage of the latest innovations. It’s also important to look at how the platform aligns with back-end systems. It should be relatively easy for non-technical users to make basic changes to the applications.
In 2024, companies have the opportunity to combine the speed and scale of AI with human emotion to enhance productivity and boost customer services. This approach, collaborative intelligence, must underpin all AI implementation strategies. Though it requires extensive change management to master collaborative intelligence, brands will reap significant rewards if they underpin AI deployments with human experience.
Next year, business leaders don’t need to tackle these digital transformation projects alone. Instead, they can draw on the expertise of CX tech partners who are well-acquainted with the challenges and will help ensure that AI deployments are tailored to their unique business needs.
