The last two years have been particularly notable for generative AI’s meteoric rise in both the public consciousness and business adoption. From ChatGPT’s sprint to a hundred million users, to tech giants Microsoft, Google, Adobe and others integrating AI-enabled components into their product offerings, it’s all the rest of us can do to keep up. Using AI to improve the customer experience (CX) represents an exciting new frontier for both businesses and consumers. Over the next several years, AI is poised to make a significant impact, addressing the unique challenges and requirements of customer experience management.
But when it comes to AI for CX, not just any old AI system will do. And just because your organization might have needed an AI solution yesterday, doesn’t mean you should charge ahead without forethought. Purpose-built AI for CX is an important driver for a successful AI integration.
Step 1: Develop a Foundation
Incorporating purpose-built AI starts by ensuring that your systems are AI-ready. This means your organization has available talent and systems that will allow you to seamlessly incorporate AI into your current operations. This is capped off with the drive and leadership buy-in necessary to put such systems in place.
Before you begin your AI-for-CX journey, you’ll need to have a solid foundation to build on. Do you have the right cloud infrastructure to facilitate scalable AI integration? Is your data clean and accessible for AI model training? Is your CX tech stack unified? Do you have leadership buy-in for the project? All these things are crucial for a successful AI integration.
Step 2: Strategize a Framework
As you continue to develop your AI plan, developing a framework will be essential. Your new AI solution will need to adhere to relevant compliance laws. In addition, you should take care to ensure data privacy is baked in. Not only will this ensure you’re in compliance with the latest rules and regulations, but it will also build consumer trust in your brand.
Trust is necessary at this crucial stage of AI’s development. Consumers are skeptical of AI’s abilities to maintain privacy and deliver relevant results. In a recent survey around AI-powered search engines, 39% of US adults don’t trust the solution to respect their data privacy. This mistrust is just one more reason why you need your AI for CX to be purpose-built. Customers are already wary of the relevance of AI-generated results; your solution needs to make relevance front and center.
Step 3: Adopt and Adapt
Even the most revolutionary tools won’t be effective without stakeholder and user adoption. Upskilling and reskilling your workforce on the new AI solution will encourage adoption and use. This step is another area where leadership buy-in is critical to ensure successful adoption throughout the organization. When systems are adopted, used and championed by senior leaders, they stand a greater change of organization-wide adoption.
The importance of upskilling and reskilling cannot be overstated as organizations enter an era of more widespread AI adoption. According to recent research, 43% of HR managers believe their companies will face a skills gap due to increasing AI adoption. Further, 55% of HR managers believe AI is a must-have skill when hiring employees. Whether you’re hiring new employees or reskilling existing ones, AI-related skills are too important to ignore.
Bonus Step: Explore NICE’s AI-Ready Solutions
NICE Enlighten — a suite of purpose-built AI for CX solutions — can take your customer experiences to the next level. The solutions (Enlighten Copilot for Agents and Supervisors, Enlighten Autopilot and Enlighten Actions — are designed to deliver the next generation of intelligent actions, AI-driven conversations and models that can uncover areas of AI-driven optimization within your DCX. Learn more about NICE Enlighten at the link below!
Learn more about NICE’s AI-powered solutions at NICE Enlighten: CX. AI. NOW.
