GenAI is Starting to Pay Off Across the Customer Journey

G enerative AI is no longer just hype—it’s delivering tangible results across the customer journey. Organizations are starting to see revenue accelerate, costs drop, and a positive impact on the customer experience (CX) across sales, marketing, and support. Here’s how GenAI is driving impact—and what you can do now to stay ahead.

Earlier this year, McKinsey published the results 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%.

What the survey does not capture is the type of applications driving the increased adoption and ROI. We compiled the top use case we’ve seen organizations adopting or successfully piloting.

Graphic describing the 6 categories of GenAI use cases for Customer Journey
The 6 categories of GenAI use cases for Customer Journey

GenAI impact on Sales & Marketing

According to the survey, 79% of organizations report revenue gains from GenAI in Sales & Marketing. Generative AI (GenAI) is transforming Sales and Marketing by automating tasks, enhancing personalization, and enabling creativity at scale. By integrating GenAI into Sales and Marketing workflows, teams are starting to achieve higher efficiency, better alignment, and stronger outcomes. We identified four critical functionalities for Sales and Marketing in three different areas: Content, Automation and Intelligence.

  1. Content Creation and Personalization: GenAI makes scaling content effortless—blogs, videos, ad creatives, sales proposals, and hyper-personalized campaigns are now achievable at a fraction of the time and cost.
  2. Lead Generation and Scoring: AI identifies buying signals, predicts funnel stages, and aligns prospects to personas, enabling smarter lead nurturing. Tools are evolving rapidly, but organizations already rely on gains they can’t imagine working without.
  3.  Data Intelligence: From enriching data to categorizing, extracting key trends, GenAI simplifies insights and enhances reporting. It can analyze large text volumes, detect patterns, key topics and sentiment, and deliver actionable intelligence faster than ever in visual, audio or textual form.
  4. Sales Process Automation: Sales teams are saving hours summarizing calls, researching prospects and customers using 10-Ks, annual reports, and the latest news and trends. Doing so, they differentiate from competitors and free up time to focus on relationships and closing deals. Sales Ops team can easily improve pitch decks, generate sales playbooks and best practices, generate sales scripts and competitive analysis. 

GenAI impact on Support

The survey shows that cost decreases are highest for support (49%). We compiled five critical functionalities 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 sustaining 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 create 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 permanent 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.

Generative AI is driving real ROI, but we’re just getting started. The opportunities to improve Sales, Marketing, and Support are limitless. How will your organization use GenAI to deliver better outcomes in 2025?  Let’s talk! 

Note: this article includes content from our partner Francoise Tourniaire, previously published on  her FTWorks Blog at       https://www.ftworks.com/genai-is-paying-off .