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Qualtrics to invest $500 million in AI as it launches new XM platform

Derek du Preez Profile picture for user ddpreez July 19, 2023
Experience management (XM) vendor, Qualtrics, has said that XM/os2 will use AI to personalize content and deliver recommendations across every product line.

Happy customer experience concept © Black Salmon - shutterstock

Qualtrics has announced that it will invest $500 million over the next four years into artificial intelligence, as the vendor reveals the latest evolution in its experience management platform - now called XM/os2 (previously known just as XM/os). During a press conference this week, CEO Zig Serafin said that whilst Qualtrics has been using AI for years, the new ‘supercharged’ AI platform will help users receive personalized content and recommendations for both customers and employees.  

Serafin said that XM/os2 will make use of both structured and unstructured data to feed the AI models being used, whilst he also was keen to make the point that the vendor has a competitive advantage in this area given the scale of data it already holds. He said: 

Everyone knows that in the world of AI, data wins. And this is because the precision, the quality, and the reliability of the output of AI is directly a function of the data that it's built on top of.

At Qualtrics we have a massive head start on this. Qualtrics is analyzing more than 3.5 billion conversations every year. We have the largest XM database in the world, with 12 billion experience profiles that capture sentiment, expectations and preferences across the entire customer journey. 

And we're automating more than 2 billion actions that drive the business outcomes that really matter to our customers. On top of that, we have 20,000 customers building on Qualtrics from industries all over the world. 

This means that our AI models are already helping companies analyze vast amounts of unstructured data, such as call center interactions and social media, along with structured feedback and customer and employee surveys. Put that together, that's tens of millions of interactions every single day that Qualtrics AI is learning from. This enables our AI to problem solve, and to learn, just like humans. 

Given the growing concern around how AI will change the nature of the workforce, particularly with regards to how it will impact people’s jobs, and even how customers will be pushed to increasingly interact with machines instead of humans for customer service, Serafin was keen to allay some of these fears. He said that artificial intelligence will “bring more humanity to business, not less” and that the technology will help organizations to understand “connections” in entirely new ways. 

Product details 

It’s worth noting that Qualtrics made a series of product announcements not too long ago at it’s user conference in March, but given the speed at which the industry is adopting new AI tools, particularly generative AI tools, the vendor obviously thought it necessary to push ahead with the release of XM/os2 now.  

The key product announcements this week include: 

  • Generative AI for frontline teams - Qualtrics will now recommend and generate personalized responses based on each customer’s profile data in Qualtrics ExperienceID. The aim being that managers can respond to customer feedback more quickly on review sites, social media, and other channels, whilst the AI takes into account a customer’s history with the company and the tone required for the situation. 

  • Real-time agent assist - users will now see AI-generated summaries during a service conversation, highlighting key points so that the agent has guidance around what steps to take next. Qualtrics says that the AI will aim to offer solutions based on each caller’s needs, emotions and history with the company. 

  • Automated call summaries - Qualtrics will automatically summarize calls and allow agents to instantly generate support tickets, send personalized follow up emails and create support knowledge base articles using information about customer issues and historical customer data. 

  • XM for People Teams - the platform will capture structured employee feedback from engagement surveys, as well as unstructured feedback from sources like Slack channels and job site reviews. The AI tooling will summarize employee feedback and behavior data – such as how many hours they’re working, how full their calendars are, and whether they are answering work messages after hours – and then correlate that data to each employee’s overall well-being. The aim is to give managers a continuous insight into how their employees are feeling and what they can do to support them. 

  • Attrition insights - new predictive AI capabilities in XM for People Teams will analyze behavior data to identify teams with a high risk of attrition over the next six months and surface the most likely reasons employees might leave. 

  • Generative AI for Qualtrics Research Hub - researchers or product managers will now be able to ask a question in Research Hub and get insights and answers automatically, without having to trawl through an organization’s brand studies, customer feedback and market data. 

  • Qualtrics Video Feedback - AI capabilities in Qualtrics Video Feedback surfaces key trends and associated quotes and insights from customers' video feedback and generates a summary that can be shared and understood across the organization. 

Supercharging experience management

Many of these systems will be released in a phased approach, with some of them only becoming available in private beta later this year, or for general release early next year - and of course we won’t have the full picture of their efficacy until customer stories begin to emerge. But what’s clear is the intent from Qualtrics that AI tooling will be featured heavily across a significant portion of its product portfolio over the coming months. 

Further commenting on the announcements, Serafin said: 

Companies want to quickly understand where the greatest friction points are in their businesses. They want to retain and engage their top talent. They want to know if you've got the right products and the right services in market. They want to deliver them in a way that's efficient and convenient for their customers, especially as consumer and business priorities are rapidly shifting. 

Companies have troves of experience data. They have chat logs, they have social media feeds, they've got feedback surveys, call center recordings. But they often struggle to leverage this data to drive tangible business outcomes. AI is accelerating the ability to take action in the right way, to help companies act quickly, decisively and more precisely on their experience data. And to automate critical actions and to create more meaningful and relevant interactions. 

And this deepens relationships between organizations and the people that matter most, all while respecting privacy and operating transparently and responsibly, which is critical. 

So we're here today, because the rate at which AI is accelerating is creating an inflection point. We're responding by supercharging experience management with AI. For the very first time, we're bringing the power of generative AI to every part of our platform. 

My take

Experience management feels like an obvious area where AI could potentially be increasingly useful to organizations. Managing relationships, either internally or externally, is a resource intensive process that takes time to listen and build understanding. And is often fraught with errors. If AI can help segment profiles, build case summaries, provide recommendations for responses effectively - and I place a very heavy emphasis on the ‘if’ here - then there’s an opportunity for organizations to build deeper connections with the people that make a business successful. 

But accuracy of this AI understanding is going to be key and I believe that most organizations will want to retain a large element of human oversight in the process. Bad experiences that are the result of poor automation or generated content, not only pose a risk for customer/employee attrition, but also huge reputational damage. 

I’m sure that Qualtrics understands that it can’t afford to execute on this poorly, and it is right to highlight the quality of the data it has at its fingertips as a huge competitive advantage. But we the reassurance will be found in the customer use cases and stories that emerge, with those buyers that learn how to implement this effectively and can showcase how using AI for experience management can deliver their own competitive advantage. Early days, but the next 12 months will be telling. 

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