5 Tips for Mapping Out a Contact Center AI Strategy

There's been a lot of buzz around artificial intelligence (AI), and in particular, generative AI, lately. We've been talking about AI and its role in customer experience (CX) for a long time, but now it's getting real: Today, you don't need a team of data scientists, years of development, or a mammoth budget to take advantage of AI to drive greater productivity, reduce costs, and improve customer and agent experience.

However, for the uninitiated, AI can be scary. The potential benefit for business in productivity is huge, but so are the potential risks. Just like any technology, AI can be used for good and bad things. Trust will be a big factor moving forward, and understanding ethics in data use, model training, and transparency when AI is used will be big topics in the coming months and years.

With that in mind, here are some tips for mapping out an AI strategy that will deliver clear benefits:

AI is just another tool.

Remember that this is just technology and its successful application will depend on the humans who make decisions around it. If we think back to when email came out, we got great benefits in productivity and efficiency, but we also got spam, phishing, and people who always replied to all. AI's productivity-increasing potential is exponentially greater than email, but so are its risks.

Focus on a business issue to solve.

Rather than thinking about a broad AI strategy, focus on specific business problems you want to solve. Do you need to improve the usefulness and currency of your knowledge base, reduce escalations, or improve quality management? A clearly defined objective will help you scope out a manageable project, select the right tools, and deliver clear results.

In a recent analysis we did of SupportLogic customers, for example, we found the shift from a manual approach to escalation management to an AI-driven one reduced escalations by 20 to 50 percent. That's in part because AI enables a real-time warning system that can automate case evaluation, allowing managers to proactively review many more cases and get ahead of potential issues. With smart consoles and alerts, service staff can see when cases are likely to result in escalations and take immediate action to avoid that and keep customers satisfied.

Don't recreate the wheel.

Unless your primary business is creating AI solutions, you shouldn't be building from the ground up. Vendors have invested in prebuilt and pretrained models, industry capabilities, and packaged solutions that can deliver relatively rapid results. A good rule of thumb is that you should expect to see measurable benefits within six months of writing your first check. If that's not realistic, you should have either a very good reason or you need to rethink your project.

Trust and verify.

This might seem obvious, but a key part of successful adoption of any technology initiative, particularly AI, is trust, and this starts with your technology partner. This doesn't necessarily mean picking the largest provider or the one with the longest track record or best balance sheet. More important indicators are how open they are about the models and tools they're using, how willing they are to share unfettered access to other customers, and how transparent and explainable their results are.

Genesys, for example, enables customers to apply AI-driven orchestration to different call queues and compare the results so managers can clearly see the outcomes before broadly deploying. Any solution worth considering will provide clear and understandable details on the key assumptions driving a recommendation or action so business users can confidently act on or override its direction.

Keep moving.

In an area where technology is evolving rapidly, few things are certain. First, you will learn things about your customers, your service organization, and your customer data that you didn't know when you started. Second, there will be ongoing improvements in technology that deliver incrementally greater benefits. Third, as you learn from your initial deployment, you'll identify new ways AI can deliver benefit or want to make changes from your initial plan to optimize benefits. That means being flexible, both in your approach and in the tools you select. Picking cloud solutions that enable users to make changes with minimal developer or vendor intervention will give you the flexibility you need to adjust your solution as you learn more about the potential of AI to improve your customer experience.

Rebecca Wettemann is founder and CEO of Valoir.