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Cheryl
Haggerty
Chief Client Officer
Shalion
Cheryl Haggerty is Chief Client Officer at Shalion, with more than 25 years of experience spanning sales, marketing, operations and customer success. Throughout her career, Cheryl has led teams ranging from individual contributors to global organisations of more than 2,500 people, combining strategic leadership with a hands-on approach to execution. She is passionate about turning strategy into action, building high-performing teams and creating strong client partnerships that deliver measurable business value. As Chief Client Officer at Shalion, Cheryl is responsible for global client partnerships and Customer Success, as well as leading Shalion’s focus on data quality, ensuring that as technology, data and AI capabilities evolve, clients remain at the heart of how Shalion operates and grows. A strong advocate for progress over perfection, Cheryl believes the best leaders combine big-picture thinking with the willingness to roll up their sleeves, challenge convention and make things happen.
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01 December 2026 16:15 - 17:00
Proving the value of AI: What the c-suite actually wants to see
AI is everywhere in Customer Success right now, from churn prediction to automated health scoring to AI-assisted QBRs, but adoption alone doesn't secure budget. Boards and C-suites want to see hard evidence that AI investment translates into retention, expansion, or efficiency gains they can defend in front of their own stakeholders. This panel brings together senior CS leaders who have taken AI initiatives from pilot to boardroom, to unpack what actually lands with the C-suite, what metrics get scrutinised, and what separates a compelling business case from one that gets quietly shelved. Key takeaways: - What ROI metrics and proof points genuinely move the needle with CFOs and CEOs, versus what sounds good in a CS meeting but falls flat at board level - How to build a business case for AI investment before you have the data to prove it worked - Common mistakes CS leaders make when presenting AI outcomes upward, and how to avoid them - How to separate genuine AI-driven impact from noise or correlation in your reporting - What a credible AI roadmap looks like to a sceptical executive audience, and how to sequence quick wins against longer-term bets