GenAI is actually starting to pay off

Earlier this year, McKinsey published the result of a survey showing not only that organizations are adopting GenAI in strong numbers—but that we are now seeing tangible returns on their investments.

Specifically, 65% of organizations are reporting that they regularly use GenAI, up from 33% a year ago, a huge rise. The top four areas for GenAI use, in order, are sales and marketing, product development, IT, and support operations.

What’s even more interesting than increased adoption is the accompanying rise in benefits of GenAI. On average, respondents reported revenue increases averaging 58% from using GenAI and cost decreases averaging 35%. Revenue increases are highest, not surprisingly, for sales and marketing (71%) and cost decreases are highest for support (49%).

What the survey does not capture is the type of applications that’s feeding the increased adoption and ROI.

From our experience, here are five critical functionalities we see for Support in three different areas: self-service (users helping themselves), assisted support (staff members helping users), and knowledge management (creating and improving the knowledge base).

1. Search summaries. Searching and summarizing the best answers for self-service users may be the most sweeping change we are witnessing, replacing the typical search-and-select-your-answer functionality. Historically, self-service has been a strong driver for decreasing cost (by replacing costly assisted support interactions) and increasing customer satisfaction (by providing immediate answers).
2. Agent answer generation. Creating answers to customer questions within the context of a support case goes beyond the self-service functionality of suggesting answers and sustain a true dialog with the user. Such copilot functionality saves support agents time and allows them to concentrate on technical tasks rather than writing tasks.
3. Case summaries. Summarizing cases is essential for managers who are reviewing potential escalations and for agents who receive a transferred case. Complex cases can run into dozens or hundreds of interactions. AI summarization is surprisingly effective at isolating the crucial events and saves lots of tedious time.
4. Auto-creation of KB articles. Creating knowledge base articles from cases weaves searching with summarizing cases to allows creating articles from cases semi autonomously (most organizations do require a manual inspection of drafts created by AI, at least for now). This is obviously a time saver but also, less obviously, a way to extract much more reusable information from support cases since it makes it a lot easier to do so.
5. Translation. Translating knowledge base articles can be done quickly, either on the spot, as needed, or by using machine translation to create permanently-stored articles in multiple languages. Most organizations choose to support only one or a handful of languages. AI-assisted translation has steadily improved over time and is now very successful for many languages, allowing accurate on-the-spot translation for users.

What are you doing with GenAI and how is it working for you?