What are the main challenges of the AI business and specifically the customer experience (CX) industry today?

Ryan Lester: Many companies struggle to understand the value they can expect from investments in AI-powered CX technology. This problem manifests in three ways: a lack of budget, outdated technology and siloed organizations. Those that do prioritize CX face a different challenge of making their data actionable.

Sanjay Mehrotra: I think the fundamental challenge with AI is learning to trust the results when they seem counterintuitive. AI can provide huge efficiencies, but not if we don’t act on the results. AI can give you answers to questions you didn’t know you should ask.

Rob Walker: AI projects are looking for a problem to solve, or don’t meet overhyped expectations. Although AI is incredibly and increasingly powerful, too many failed “hobby projects” may tarnish its reputation. In the CX industry, AI is often being positioned as a solution to optimize real-time conversations with customers. If done well, it delivers unprecedented customer relevance and mutual value to those conversations between the customer and the organization.

What are the business benefits behind AI?

RL: Automating low-level tasks cuts costs, directly impacting the business’s bottom line. AI also drives top-line revenue by increasing the number and quality of customer engagements and gives customers a way to self-serve, reducing the load on support agents and increasing customer satisfaction. 

SM: What is your data trying to tell you? AI can provide answers. It's an essential tool that can give you a better understanding of the insights hidden in your data and how to continually modify what you’re doing to optimize your company’s resources for peak efficiency. 

RW: We’ve only just scratched the surface on how businesses can benefit from AI. It can instantly analyze and assess a large palette of potential options for each customer and then personalize a next best action in the moment. AI deployed in the right way and across the right departments — like marketing, risk, service and other mission-critical business functions — will only increase its value to businesses.

What's the biggest misconception behind AI's use case today?

RL: The biggest misconception today is that adopting AI must be a massive and complex project, taking months to implement and see an ROI. This is far from the truth, with companies seeing a positive ROI in weeks. Companies should prioritize speed to market when initially adopting AI.

SM: AI is often seen as a magic bullet — a switch you flip for instant results. The secret of applying AI effectively starts with your data. AI thrives on data. Where we once saw data as a cost to be managed, AI is now turning data into a new source of competitive advantage.

RW: What people don’t see is how widely it's been adapted. It was reported that 33 percent of consumers “think” they use technology with AI; in reality, 77 percent had already interacted with it. If you are reading this, you have likely used AI today in some capacity. 

What are other business use cases you can tackle with AI?

RL: Offering internal-facing human resources (HR) and IT chatbots helps employees clear daily hurdles so they can spend more time being productive. In addition to making employees more efficient and productive, having employee-facing AI-powered chatbots in the workplace helps businesses hire and retain top talent.

SM: In the semiconductor business, we generate enormous quantities of data across manufacturing. We’ve found that we can prevent costly downtime of our semiconductor tools by asking the AI to analyze the sound patterns a tool makes and how they change over time to proactively schedule maintenance.

RW: Like CX, HR can stand to gain operational strides in their everyday work. AI can help automate tasks, accelerate time to hire, forecast staffing needs with accuracy and provide a number of other benefits across all industries. The opportunities are limitless when businesses understand how to create an AI deployment that is intelligent and based on quality data.