5 mistakes to avoid when implementing AI

Companies all over the world are experiencing the next wave of technological transformation. From implementing machine learning and natural language processing, to help teams improve productivity, or text-to-speech and intelligent virtual agents to boost customer services, the standout companies have been quick to take advantage of all that AI has to offer.

Generative AI has the potential to transform the customer experience (CX) space because it will become part of every interaction. For a customer interacting with a brand, calls, meetings, and chats can be supported throughout by AI technology. With AI working in tandem with human agents, the opportunities for creating a more fluid CX experience are endless.

As an assistant to customer service teams, generative AI can add value to every conversation on the planet. The benefits are clear to see: providing consumers with real-time information, recommendations, and guidance during complex calls, and helping human agents triage and summarise customer queries more effectively.

AI is on everyone’s mind, but to deliver real value it must be implemented with practical outcomes in mind. As Christina McAllister, Senior Analyst at Forrester highlights – whilst AI can deliver “enormous value”, it needs to be leveraged intentionally. It’s understandable that CX professionals are excited by the opportunities new technologies offer. However, it’s also imperative that they draw up plans for implementation where the customer experience underpins every decision.

Here are five common pitfalls that are often made when implementing AI across a business, as well as the strategies to avoid them.

1) Learn from industry AI use cases in the CX space

When incorporating AI into any organisation, many see it as another stand-alone tool that can be bolted onto an existing strategy. Make no mistake, AI will fundamentally transform how your customer communications work, and will dramatically alter the customer experience journey. 

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 ripple effect of offloading swathes of work to AI that can free your employees to become an entirely new resource. 

2) Look beyond the AI hype

It is easy to get swept up in the excitement of futuristic technologies, but vital that any plan for AI adoption contains a clear vision, with achievements and aims outlined as well as metrics for success. There are numerous ways AI can deliver impact, but you must ensure you’re measuring the right metrics for your business. Whether that is more accurately routing calls, improving call handle time, first-call resolution, call abandonment or completely automating certain tasks, or a mixture of all – make sure your vendor 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 that you understand exactly what the customer will experience with the AI and how you are going to measure its impact on their journey. Work with a vendor that can help you understand the impact at every stage. 

3) Consider a collaborative approach to AI

While AI is helping contact centres 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, 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 agents oversight to ensure accuracy? For example, if AI is creating automatic call summaries, human agents 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 clear and transparent when implementing AI

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. It is important to counter this by communicating that AI is not designed to replace humans, but to assist and free them to engage in more valuable customer interactions. 

Walk people through the changes AI creates and bring them in on the process, being clear about why it is being adopted and what it cannot replace. AI provides many benefits, but it can never replace the empathy and kindness that your people have to offer your customers.

Likewise, include your customers in change management. Let them know you’re creating new ways of engaging with them and give them the opportunity to provide feedback. When a call is transferred from IVA or a bot to an agent, ask the customer if the AI was helpful.

Acknowledge that AI isn’t perfect and let customers know that you are working to continually improve it.

5) Explore for flexibility with AI

Not all AI is built equally. Whilst almost all vendors in the CX industry will showcase AI as an essential element of their cloud contact centre 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, so that you can continuously take advantage of the latest developments as and when they occur.

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. Another vital consideration should be the agent user experience.

Collaborative intelligence will unlock new opportunities in the CX space

Leaders need to ensure they are combining the speed and scale of AI with human emotion – not using it in isolation. Then, generative AI can empower businesses to create more personal experiences at scale and improve reliability at the same time. This approach, collaborative intelligence, must underpin any and all AI strategies. When human experience underpins strategy, and you take a thoughtful approach to implementation, AI enables automation, responsiveness and agility that extends and elevates human abilities.

Though it takes time to ‘bake-in’ such collaboration, brands will reap significant rewards if they consider this approach. AI has the potential to provide customer experiences that go above and beyond every expectation, but it’s imperative that plans for implementation are targeted and considered. Leaders don’t need to tackle digital transformation alone, they can draw on the expertise of partners who are well-acquainted with the challenges the road ahead can present.