For a long time, I believed leadership flowed from authority. Titles, reporting lines, decision-making power — these seemed like the essential ingredients for influence. It took working in highly cross-functional, high-stakes environments to realise that leadership is rarely about the position you hold. Instead, it’s about the clarity you bring, the trust you earn, and the consistency of your communication.

There was a point in my career when I had zero direct reports, yet my responsibility was to coordinate and drive execution across a room full of senior leaders across EMEA — VPs, regional leads, seasoned executives. None of them reported to me. All of them had competing priorities. And yet the projects needed to move.

That experience reshaped my understanding of what leadership really is.

Automation has become a central theme in modern Customer Success. As organisations search for greater efficiency, scale and consistency, automation quickly rises to the top of the priority list. It promises speed, accuracy, and relief from administrative overload. Yet there is a risk hidden within that promise: when automation is introduced without a clear strategy, Customer Success becomes mechanical and customers begin to feel processed rather than supported.

Customer Success has never been a function defined by tasks. It is defined by relationships, judgement and trust. You can automate steps in a workflow, but you cannot automate empathy. And this is where many organisations go wrong. They introduce automation before they have clarity on which touchpoints require human nuance, which interactions can be automated reliably, and how customers actually want to engage. The outcome is predictable: generic communications, poorly timed triggers, inconsistent sentiment, and ultimately a deterioration in the relationship rather than an improvement.

The reality is that automation elevates Customer Success only when it strengthens, rather than replaces, the human experience. Automation should free CSMs to be more available, more strategic and more thoughtful—not less. It should create space for real conversations, deeper discovery and more proactive guidance. To achieve this, organisations must treat automation as an enabler of human work, not a substitute for it.

This post explores how to design automation in a way that enhances authenticity, builds trust and protects the relationship at the heart of Customer Success. Ultimately, my advice in this post is about how to scale intelligently without eroding trust.

7 Tips to Automating Customer Success Without Losing the Human Touch

Customer Success leaders love the promise of AI — faster insights, smarter prioritisation, automated admin, better forecasting.

But here’s the uncomfortable truth few organisations want to admit: AI doesn’t fix broken operations. It amplifies them.

If your data is scattered, your processes are inconsistent, your playbooks are unclear, or your teams work in silos, AI will simply automate the chaos. You’ll get faster output — but not better outcomes.

That’s why the real work of AI transformation doesn’t start with AI at all. It starts with building AI-ready operations: the workflows, governance, and data structures that allow AI to actually deliver value.

Because AI only works if your foundations work. 

In this post, we’ll break down what AI-ready CS operations look like, how to build them, and what mistakes to avoid when modernising your CS engine for the AI era.

5 Steps to Designing AI-Ready Customer Success Operations

Customer Success has always been about relationships — understanding customer goals, helping them realise value, and building long-term trust. But as SaaS portfolios scale and digital adoption accelerates, the role of the CSM is changing faster than ever.

Today’s customers expect speed, precision, and foresight. They don’t just want support — they expect guidance, personalisation, and outcomes at scale. Yet many CS teams are buried under manual processes: data entry, meeting notes, follow-ups, and reactive firefighting.

That’s where AI and automation come in — not to replace the human side of Customer Success, but to amplify it.

AI is reshaping the modern CSM from a relationship manager into a strategic advisor: someone who blends human empathy with data-driven insight.Instead of spending hours collecting information, CSMs can spend their time interpreting it — advising customers, aligning with executives, and driving measurable value.

This evolution is not optional. It’s already happening. According to TSIA, 70% of CS leaders say they plan to embed AI into their operations within the next 12 months — but only a fraction have a clear strategy for what that means in practice.

Customer health has always been a cornerstone of Customer Success — yet the way most organisations measure and act on it hasn’t evolved fast enough.

Over the past few months, I’ve explored this transformation — from static health scores to dynamic, AI-driven systems that connect data to outcomes. This post brings all the pieces together in one place and looks ahead to what comes next.

1️⃣ Why Customer Health Is Broken

Most health scores are static and misleading. A “green” account can still churn because the score doesn’t capture context or timing.
👉 Read the post →