Tag Archives: Leadership

Why Customer Success Needs a “State of AI” Report

If you’ve spent any time on LinkedIn recently, you’ll have seen no shortage of posts about AI and Customer Success.

Some predict the end of the Customer Success Manager. Others claim AI will transform everything overnight. Most fall somewhere in between.

The problem is that there’s very little agreement on what’s actually happening.

After dozens of conversations with Customer Success leaders, SaaS executives and founders over the past year, I’ve noticed something interesting.

We’re all talking about AI.

We’re just not talking about the same thing.

Some teams are experimenting with meeting summaries and email drafts.

Others are building AI into customer workflows.

Some are measuring productivity.

Others are trying to rethink their entire post-sales operating model.

These are completely different conversations.

What seems clear is that AI has moved beyond experimentation. It is becoming part of day-to-day Customer Success.

The more interesting questions are no longer whether teams should use AI, but how they should use it and what impact it is really having.

From where I sit, a few themes keep appearing.

AI is removing repetitive work but increasing expectations.
It is exposing weak processes rather than fixing them.
It is making commercial judgement more valuable, not less.
It is forcing Customer Success leaders to rethink what great performance actually looks like.

I don’t think the biggest story is that AI is replacing Customer Success.

I think it’s changing what good Customer Success looks like.

That’s a much more interesting conversation.

Over the coming months, I’m going to capture the patterns I’m seeing through my advisory work, podcast conversations and discussions with Customer Success leaders.

The goal is simple.

To build a practical picture of how AI is really changing Customer Success, separating the hype from what’s happening in real SaaS organisations.

I’d love to hear what you’re seeing too.

What’s been the biggest change in your Customer Success team since AI became part of everyday work?

The revenue leak starts after the sale

Most SaaS founders know revenue is leaking somewhere.

They can see it in the numbers.

Renewals are harder than they should be.
Expansion is slower than expected.
NRR starts to drift.
Customers look fine until they suddenly are not.

So the business looks at the usual suspects.

The renewal process.
The onboarding journey.
The sales handover.
The health score.
The CSM cadence.

All useful places to look.

But often, they are not where the leak starts.

The leak starts earlier.

It starts the moment a customer signs and nobody clearly owns whether they achieve what was promised.

The deal is not the outcome

A signed deal feels like progress.

And it is.

But for the customer, nothing has been realised yet.

They have not bought a contract
They have not bought access to software
They have not bought an onboarding plan

They have bought an outcome.

That might be faster reporting, lower risk, reduced manual work, better visibility, higher productivity or stronger revenue performance.

Whatever it is, someone inside your business needs to own whether the customer gets there.

Not loosely
Not culturally
Not “the team”

Actually own it.

Because when everyone owns the customer outcome, nobody does.

Where the gap opens

The gap opens between what sales commits and what the customer experiences.

Sales sells the promise
Onboarding gets the customer live
Customer Success runs the cadence
Support handles the issues
Product tracks usage
Finance watches the renewal number

But who owns the customer getting what they paid for?

That is the uncomfortable question.

Because in many SaaS businesses, the answer is vague.

Everyone is involved
Nobody is accountable

And that is where churn starts to build.

Not at renewal
Not when the customer complains
Not when usage drops

Much earlier.

It starts when the business loses sight of the original promise.

Usage is not proof of value

This is where many SaaS teams fool themselves.

A customer can be onboarded and still not be successful.

They can log in and still not see value.

They can attend QBRs and still not believe the product is critical.

They can use the software and still struggle to explain the commercial impact.

Usage matters.

But usage is not the same as value.

Activity is not the same as progress.

A completed onboarding is not the same as a customer who has achieved what they were sold.

That distinction matters because renewals are not won by activity.

They are won by evidence of value.

Customer Success cannot fix this alone

When retention weakens, companies often assume they have a Customer Success problem.

Sometimes they do.

But often, they have a post-sale ownership problem.

Customer Success cannot fully own value if the sales promise was never captured properly.

It cannot prove impact if success criteria were never agreed.

It cannot drive expansion if the customer never reached first value.

It cannot rescue a relationship if the business treated the sale as the finish line.

CS has a critical role.

But post-sale value is not a department.

It is a commercial operating discipline.

That means sales, onboarding, product, support, finance and leadership all need to be aligned around the same question:

Did the customer get what they paid for?

A simple test

Ask five questions after every deal closes:

What outcome did the customer buy?
What did sales promise or imply?
Who owns first value?
How will we prove value has been realised?
When will leadership know if the customer is off track?

If the answers are vague, you have found the leak.

Not a theoretical leak.

A commercial one.

The kind that shows up later as slow adoption, weak expansion, renewal risk and declining NRR.

The real ownership question

The best SaaS businesses do not treat the sale as the finish line.

They treat it as the start of the value obligation.

That is the shift.

From “we sold it” to “they realised it”.

From customer handoff to customer ownership.

From activity tracking to value evidence.

So the real question is not:

“Do we have a Customer Success team?”

Most companies do.

The better question is:

Who in your business owns what happens after the sale?

If the answer is unclear, that is where the revenue is leaking.

Most SaaS Companies Don’t Need A Bigger Customer SuccessTeam

Why Hiring Another CSM Rarely Fixes Churn

Most SaaS companies respond to churn the same way.

They hire…

Another CSM
Maybe a Head of Customer Success
Sometimes a VP

It feels like progress, but it rarely fixes the real problem.

Because churn is not always a capacity issue.

More often, it is a design issue .

Infographic to download and save below…

The Real Problem

If your customer success function is not clearly driving retention and expansion, adding more people usually creates more activity.

More calls
More QBRs
More dashboards
More internal updates

But not necessarily better outcomes and often, no clear link to revenue.

That is where many SaaS companies get stuck.

They build a bigger customer success team before they have built a proper customer success model.

Where A Customer Success Advisor Fits

A customer success advisor does not simply add more hands.

They help fix the operating model.

That usually means:

defining what customer value actually looks like
aligning sales, customer success and product around that value
building a repeatable system for retention and expansion
creating earlier visibility of renewal risk
making customer success commercially accountable

This is not about doing more.

It is about doing the right things consistently.

The Pattern I See Repeatedly

Across SaaS companies, the pattern is often the same.

Sales sells one version of value
The customer expects something slightly different
Customer success tries to bridge the gap
Product is not always close enough to what is happening after the sale
Leadership only sees the issue when churn appears

By then, the problem has usually been building for months.

Why This Matters Now

AI is making this more obvious.

It is now easier than ever to:

automate activity
generate insights
scale customer outreach
produce reports
identify signals

But none of that fixes a broken model.

In fact, AI can make the problem worse.

If the customer success model is unclear, AI simply helps you scale unclear work faster.

That is not transformation. That is organised noise.

What Good Looks Like

When customer success is working properly, the business feels different.

Retention becomes more predictable.

Expansion becomes systematic, not opportunistic.

Customer success has a clear commercial role.

Sales, product and CS are aligned around the same customer outcomes.

Leadership trusts the numbers because the numbers connect to reality.

That is the shift from customer success as support to customer success as a growth engine.

Practical Takeaway

Before hiring another CSM, ask one question:

Do we know exactly how customer success drives revenue in our business?

Not in theory.

In practice.

By segment
By customer stage
By renewal risk
By expansion opportunity
By measurable value delivered

If the answer is not clear, another hire will not fix it.

It may simply make the current problem more expensive.

Final Thought

If you are trying to improve retention or make customer success more commercially accountable, the real work usually starts before the next hire.

It starts with the model.

The team can only scale what the business has designed properly.

👉 Customer success advisor

Why SaaS Growth Breaks After the Sale (and How to Fix It)

Introduction

Most SaaS companies think they have a pipeline problem.

They don’t.

They have a conversion problem after the deal.

Revenue doesn’t just come from winning customers. It comes from what happens next. – adoption, value realisation and expansion.

And this is where growth quietly breaks.

The Real Problem Isn’t Sales

SaaS leaders spend a lot of time optimising:

Lead generation
Conversion rates
Sales efficiency

But once the deal is signed, things become far less structured.

The assumption is simple:

“We’ve sold the value, now the customer will realise it.”

In reality, that rarely happens consistently.

Where Growth Actually Breaks

Growth doesn’t fail at the point of sale.

It breaks in the gap between:

What was sold
What is delivered
What the customer actually achieves

This shows up in familiar ways:

Slow or partial adoption
Customers using features but not achieving outcomes
Expansion opportunities that never materialise
Churn risk appearing late in the lifecycle

By the time it’s visible, the damage is already done.

The Hidden Revenue Leak

Every SaaS business has a flow:

Sale → Adoption → Value → Expansion

If that flow is not connected and managed:

Revenue is lost.

Not always immediately.

But over time:

Deals don’t expand
Renewals become harder
Growth becomes unpredictable

This is why many companies feel like they are working harder for the same results.

Because they are.

Why Customer Success Alone Doesn’t Fix It

This is often labelled as a Customer Success issue.

It isn’t. It’s a system issue.

Common problems include:

Weak handover between sales and post-sale teams
No clear definition of what “value” actually means for the customer
Lack of ownership for outcomes
Misalignment between sales, CS and product

Customer Success can’t fix this in isolation. Because the problem doesn’t sit in one team.

What High-Growth SaaS Companies Do Differently

Companies that scale efficiently do one thing well:

They control what happens after the sale.

That means:

Clear alignment between sales, CS and product
Defined customer outcomes from day one
Strong ownership of value realisation
Early visibility of risk and opportunity
A structured path to expansion

In these organisations, growth feels more predictable. Because it is.

How to Fix Where Growth Breaks

If you want to improve growth, start here:

1. Define Value Clearly:

What does success look like for the customer? Not usage. Not features. Outcomes.

2. Strengthen the Handover:

Make sure context, expectations and goals carry through from sales into delivery.

3. Track Leading Indicators:

Don’t wait for churn. Track adoption, engagement and value signals early.

4. Align Teams Around Outcomes:

Sales, customer success and product need to be aligned around customer success, not just their own metrics.

5. Build a Path to Expansion:

Expansion should not be opportunistic. It should be designed into the lifecycle.

Final Thought

Most SaaS companies don’t struggle to win customers. They struggle to turn those customers into long-term, expanding revenue.

That’s where growth really happens. And that’s where it often breaks.

Call to Action

If growth feels harder than it should, it’s worth asking a simple question:

Where does it break after the sale?

AI in Customer Success: A Practical Guide for SaaS Leaders

AI is reshaping customer success. Not by replacing people, but by changing how decisions are made.

For SaaS companies, growth no longer depends on sales alone. It depends on what happens after the deal. This is exactly how I approach customer-led growth.

Retention, expansion and customer value are now the real drivers of revenue.

AI is accelerating that shift.

What AI In Customer Success Actually Means

AI in customer success is not about automation for its own sake.

It’s about improving how teams:

Identify risk earlier
Spot expansion opportunities
Guide customers towards value
Focus on what actually matters

The goal is not more activity. It’s better decisions.

Why AI Is Changing SaaS Retention & Growth

Traditional customer success models rely on:

health scores
manual check-ins
reactive engagement

These approaches are limited.

They depend on lagging indicators and human bandwidth.

AI changes this by:

analysing usage data in real time
identifying patterns across customers
surfacing signals before problems are visible

This shifts customer success from reactive to proactive and is already visible in how teams are evolving, as outlined in how AI will impact customer success teams.

Where AI Really Creates Value

The real impact of AI in customer success comes from a few specific areas.

Risk detection:

AI can identify churn risk before the customer feels it. Changes in behaviour, usage drops or engagement patterns can be flagged early, giving teams time to act.

Expansion signals:

AI can highlight where value is already being created. This allows teams to focus expansion conversations on real outcomes, not assumptions.

Time to value:

AI can guide the next best action for customers. This reduces friction, shortens onboarding and helps customers reach value faster.

Focus & prioritisation:

Customer success teams often manage too many accounts with too little time.

AI helps prioritise where attention is needed most, improving both efficiency and impact.

What Most Companies Get Wrong

Adding AI on top of a weak customer success strategy does not fix the problem.

It amplifies it.

Common mistakes include:

unclear definition of customer value
misalignment between sales, product and customer teams
over-reliance on generic health scores
focusing on activity instead of outcomes

If you don’t know what value looks like for your customer, AI won’t solve that.

How To Implement AI In Customer Success

The starting point is not technology. It’s clarity.

1. Define customer value clearly

What outcomes does your customer care about? Revenue, efficiency, risk reduction, growth. Be specific.

2. Align teams around those outcomes

Sales, product and customer success need to agree on what success looks like. Otherwise, AI will surface data but not meaning.

3. Use AI for signal, not noise

Focus on:

risk indicators
expansion triggers
usage patterns

Avoid drowning teams in dashboards.

4. Combine AI with human judgement

AI prepares. Humans decide. The best teams use AI to reduce uncertainty, not replace thinking.

Final Thought

AI does not fix customer success. It exposes whether you understand customer value. The gap between average and high-performing teams is about to get much wider.

Want To Go deeper?

If you’re thinking about retention, expansion or how AI fits into your strategy, I work with a small number of SaaS companies on exactly this.

👉 If you’re rethinking your approach, let’s talk.

AI in Customer Success: Stop Chasing Efficiency & Start Driving Outcomes

Most Companies Are Using AI The Wrong Way

Most companies are using AI to move faster but very few are using it to create better customers. And that’s the gap.

AI in Customer Success is being treated as an efficiency tool. Automate tasks, reduce workload and scale coverage. Useful, but limited. Because speed without direction doesn’t create value.

What AI-Enabled Customer Success Should Actually Do

The best teams have shifted the question.

Not: How can AI save time?
But: How can AI improve customer outcomes?

That shift changes everything.

In practice, it looks like this:

AI identifies risk before the customer feels it
AI highlights expansion opportunities based on real usage
AI reduces time to value through next best actions
AI removes noise so CSMs focus on commercial impact

Not more activity, better decisions.

The Real Problem: AI Is Scaling Weak Strategies

This is where most SaaS companies get stuck. They add AI on top of an unclear Customer Success model. And AI does what it always does.

It scales what is already there.

If your definition of customer value is weak, AI won’t fix it.

If your teams are not aligned, AI will amplify the noise.

If your data is messy, AI will generate more confusion than insight.

AI doesn’t solve strategy problems. It exposes them.

The Shift That Matters

The move is simple. But not easy.

From reactive to predictive
From activity to outcomes
From account management to value creation

This is where Customer Success becomes commercial, not operational.

What The Best SaaS Companies Do Differently

They are not replacing Customer Success.

They are upgrading it.

AI handles the signals
Humans handle the decisions

That means:

More strategic conversations with customers
Better judgement on risk and growth
Stronger alignment across CS, Sales, and Product

Human-led. AI-enabled. Outcome-focused.

That’s the model.

Final Thought

If your AI strategy is focused on efficiency, you’ll move faster. If it’s focused on outcomes, you’ll grow faster.

Ask one simple question:

Is your AI improving customer outcomes
Or just making your team busier, faster?

Want To Go Deeper?

If you’re thinking about retention, expansion or how AI fits into your strategy, I work with a small number of SaaS companies on exactly this.

👉 If you’re rethinking your approach, let’s talk.

Why SaaS Companies Outgrow Their Customer Success Model

Customer success rarely breaks overnight. What usually happens is much quieter.

The company grows
The customer base expands
Contract values increase

And the customer success model that worked in the early years slowly stops working.

Most leadership teams don’t notice this immediately.

The team still looks busy
Customers are still renewing
The product still works

But under the surface the system starts to drift.

The Moment SaaS Companies Start Feeling It

There are a few signals that usually appear around the same time.

The team feels constantly busy but mostly reactive.

Customer conversations revolve around product usage rather than business outcomes.

Renewals start to feel less predictable than they used to.

Expansion tends to happen through sales rather than emerging naturally from customer adoption.

None of these issues look dramatic in isolation but together they signal something more structural. The company has outgrown the way customer success operates.

What Worked Lower ACV Customers Doesn’t Work For Bigger Ones

In the early stages of a SaaS company the Customer Success model is usually informal. Customer relationships are close and founders are involved in the customer journey.

Customers are often smaller and more forgiving, but as the business scales two things change.

Contract values increase
Customer expectations increase with them

What worked when customers were small rarely works when customers are larger, more strategic and expecting measurable outcomes.

At that point customer success needs to shift from relationship management to value leadership.

When the Team Looks Busy but Value Feels Blurry

One of the most common symptoms is that customer success teams become highly active but struggle to consistently land the value story with customers.

They have data
Product usage dashboards
Activity reports
Feature updates

But customers are not buying activity. They are buying outcomes.

If the link between product adoption and business impact is not clear, renewal conversations become much harder than they should be.

This is rarely a capability problem inside the customer success team. It is usually a missing framework.

The organisation has never clearly defined how customer value should be articulated and reinforced across the customer journey.

Why Hiring Another Customer Success Leader Doesn’t Always Solve It

A pattern I see quite often is companies trying to fix these issues by hiring new customer success leaders. But if the underlying operating model has never been redesigned, leadership changes alone rarely fix the problem.

Customer success is operating inside the same system. The same segmentation. The same customer journey. And the same expectations placed on the team.

Without addressing those foundations the organisation simply repeats the same challenges with different people.

The Real Work: Designing the Post-Sales Engine

The real question leadership teams eventually face is this:

How should the post-sales engine actually work?

That normally means stepping back and looking at three things.

How customers move through the lifecycle from onboarding to renewal
How Customer Success is structured to support different customer segments
How the organisation consistently connects product usage to measurable business value

When those foundations are clear, customer success teams can focus on proactive work that drives adoption, retention and expansion.

When they are not, the team inevitably ends up reacting to problems rather than leading customer outcomes.

Customer Success as a Growth Function

The most successful SaaS companies eventually recognise something important.

Customer success is not simply about protecting revenue. It is about creating the conditions where revenue can grow.

When the post-sales model is designed well:

customers adopt the product more deeply
retention becomes predictable
expansion becomes natural

And the company stops relying solely on new sales to drive growth. This is when customer success truly becomes a strategic function.

Helping SaaS Companies Reset Customer Success

At certain points in a company’s growth it helps to step back and look at the whole post-sales system. Not just the customer success team itself, but how the organisation connects product adoption, customer outcomes, retention and expansion.

That usually means examining the customer journey, the way the customer success organisation is structured and how value is articulated with customers.

Sometimes those changes are driven internally.

Other times leadership teams bring in external experience to help diagnose the challenges and reshape the operating model.

Either way, when the post-sales engine is designed deliberately, customer success stops being reactive and becomes one of the most powerful drivers of long-term SaaS growth.

Want To Go Deeper?

If you’re thinking about retention, expansion or how AI fits into your strategy, I work with a small number of SaaS companies on exactly this.

👉 If you’re rethinking your approach, let’s talk.

How AI Will Impact Customer Success Teams

For the past two years there has been a loud debate about AI in Customer Success.

Will it replace Customer Success Managers?
Will AI run renewals?
Will customers even want to speak to humans?

These are great questions but they miss the real shift that is happening.

AI will not replace Customer Success. It will expose weak Customer Success teams.

Because when automation removes the operational work, what remains is the hardest part of the role. Helping customers achieve real business outcomes.

The Work That AI Will Remove

A large part of Customer Success work today is operational.

Preparing reports
Updating dashboards
Summarising meetings
Chasing internal teams for updates

This is not where value is createdIt is simply the administrative cost of running a customer-facing organisation. AI is already automating much of this work.

AI is changing how customer success teams operate. I’ve broken this down in detail in this guide to AI in customer success.

Modern Customer Success platforms can:

summarise customer calls
analyse product usage data
identify churn risk signals
generate account summaries
recommend next best actions

According to the Gainsight Customer Success Index, 52% of Customer Success teams already use AI in their workflows, and 91% expect it to significantly impact their strategy.

Source

In other words, the administrative layer of Customer Success is starting to disappear and that is where the real shift begins.

What Remains When Automation Arrives

When AI removes the operational workload, something interesting happens. The role becomes clearer. Customer Success is not about managing activity. It is about creating value.

The companies getting this right focus Customer Success on three things.

(1) Helping customers achieve measurable outcomes:

Not feature adoption. Not product usage. Actual business impact.

(2) Connecting product capabilities to customer strategy:

The best CSMs increasingly look more like advisors than account managers
They understand the customer’s business model and help align technology to it

(3) Identifying growth opportunities

Expansion revenue rarely comes from sales pressure
It comes from customers realising the product is solving real problems
When that happens, growth follows naturally

The Uncomfortable Reality For Many Teams

Many Customer Success organisations were built for a different era. An era where simply maintaining relationships created value.

That model is under pressure. AI will not remove Customer Success roles. But it will remove the work that previously hid weak operating models. Teams that rely on:

manual reporting
reactive engagement
relationship management without measurable outcomes

… will find it harder to justify their role. Because AI can replicate most of that activity.

What AI cannot replace (today) is commercial judgement and strategic thinking.

What Great CSMs Will Look Like In 5 Years

As automation spreads across the industry, the profile of a strong Customer Success Manager will change. Three capabilities will matter far more than they do today.

(1) Business understanding: CSMs will need to understand how their customers actually create value. Industry knowledge becomes more important than product knowledge.

(2) Commercial thinking: Great Customer Success leaders will understand how retention, expansion and customer outcomes connect. They will think like revenue leaders.

(3) Strategic communication: Customers do not need another dashboard walkthrough. They need someone who can translate product capability into business impact.

The role then becomes far less operational and more advisory and strategic.

What Leaders Should Do Now

If you run a SaaS business, AI should not be viewed as a headcount reduction tool inside Customer Success. It should be viewed as a capability shift. The goal is not to remove Customer Success.

The goal is to remove the operational friction around it. This allows teams to focus on the work that actually drives growth. Helping customers succeed.

Because in subscription businesses, customer success is not just a support function. It is one of the most powerful growth levers a company has.

The Real Impact Of AI On Customer Success

The future of Customer Success will not be defined by automation. It will be defined by clarity. Once AI removes the administrative work, the purpose of the function becomes obvious. Customer Success exists to help customers achieve outcomes that make them want to stay. And to expand.

The teams that can demonstrate that clearly will become more valuable than ever.

The teams that cannot will struggle to justify their place.

Because AI does not remove Customer Success, it exposes it.

Want To Go Deeper?

If you’re thinking about retention, expansion or how AI fits into your strategy, I work with a small number of SaaS companies on exactly this.

👉 If you’re rethinking your approach, let’s talk.

The Next Era of Customer Success

It’s Changing

For years Customer Success was framed as a pro-active support function. Helpful. Important. But rarely commercial.

That framing made sense in the early days of SaaS. Companies were still learning how subscription businesses behaved. Retention mattered but growth still came primarily from new logos.

But it’s no longer true and it’s something that many companies still struggle with.

Today many SaaS companies generate as much growth from existing customers as they do from new ones. Expansion revenue, renewals and product adoption have become the most predictable drivers of performance.

Which means Customer Success is changing. It is moving from a relationship function to something far more strategic. A revenue system.

The Signals Are Already Visible

Over the last year the direction of travel has become clearer. AI adoption inside Customer Success teams is accelerating quickly.

According to the Gainsight Customer Success Index:

52% of Customer Success teams are already using AI
91% expect AI to significantly impact their strategy

Source

But at the executive level there is still scepticism. The PwC Global CEO Survey found that 56% of CEOs say AI has not yet delivered meaningful financial returns.

Source

That gap matters. Technology is evolving quickly. Operating models are not.

Many organisations are still working out how AI, Customer Success and revenue growth actually connect.

Customer Success Is Your Revenue Engine

The companies getting this right are changing how they design Customer Success. They are no longer measuring activity. They are measuring outcomes and valued delivered to customers.

Growth depends on what happens after the deal. This is explored in more detail in this guide to AI in customer success.

Instead of focusing on engagement scores, meeting counts or dashboard activity, they focus on metrics that boards understand immediately.

Gross revenue retention
Net revenue retention
Expansion revenue
Time to value
Cost to serve

When Customer Success is built around these metrics it becomes one of the most predictable growth levers in a SaaS business. Often the most efficient one. Because growing existing customers is almost always cheaper than acquiring new ones.

The Mistake Many Companies Still Make

Despite the maturity of the discipline, many organisations still run Customer Success like a relationship management team.

More meetings
More check-ins
More quarterly reviews

But simple activity is not value. Customers do not renew because a meeting happened. They renew because the product is delivering measurable outcomes inside their organisation.

The next generation of Customer Success therefore looks different.

It is more:

Data driven
Operationally scalable
Focused on outcomes

The goal is not to talk to customers more. The goal is to help customers achieve value faster. Let’s call it value acceleration.

Where AI Actually Fits

AI will not replace Customer Success. But it will change how it operates. The biggest impact will be scale.

AI is already helping teams:

Identify churn risk earlier
Analyse product usage patterns
Summarise customer conversations
Automate onboarding steps
Surface expansion opportunities

This allows Customer Success teams to manage significantly larger portfolios of customers while focusing human effort on the moments that matter most.

The work becomes more strategic and yes, more commercial.

The Debate Shaping The Industry

There is still one unresolved question in Customer Success that is being asked too many times – should Customer Success own revenue?

Some companies expect Customer Success teams to manage renewals and expansion. Others separate the roles.

Customer Success focuses on value. Sales focuses on commercial negotiation.

There is no universal answer yet but the direction of travel is clear.

Customer Success is moving closer to revenue ownership whether organisations formally recognise it or not. Because retention and expansion are where sustainable growth increasingly comes from.

What CEOs & Founders Should Focus On Now

If you run a SaaS business today, three questions matter.

(1) Do we know exactly why customers renew?

If the answer is vague, your retention strategy is fragile.

(2) Can we predict churn before it happens?

Most organisations still rely on lagging indicators. By the time a customer is clearly unhappy, it is often too late.

(3) Is Customer Success designed to scale?

Human-heavy operating models break quickly once companies grow beyond a few hundred customers. Digital journeys, automation and AI are becoming essential infrastructure. Not optional improvements.

The Next Phase Of Customer Success

Customer Success is no longer a new discipline. But it is entering a new phase.

The first era focused on customer experience. The next era will focus on something much simpler and that is Revenue retention.

The companies that understand this shift early will build more resilient SaaS businesses.

And the leaders who design Customer Success around revenue outcomes will have one of the most powerful growth levers in modern software.

Want To Go Deeper?

If you’re thinking about retention, expansion or how AI fits into your strategy, I work with a small number of SaaS companies on exactly this.

👉 If you’re rethinking your approach, let’s talk.

AI has already arrived in Customer Success, the question now is what we do with it?

AI isn’t coming for Customer Success jobs. It’s already here.

Most of the work we used to treat as essential has quietly moved into the background.
Health scores. Renewal reminders. Basic check-ins. The admin that once filled our days is now handled by systems that never get tired.

And that’s a good thing.

Because it forces us to confront something the industry has avoided for too long. The value of a CSM has never been in tasks. It’s always been in thinking.

The Shift Nobody Can Ignore

As automation expands across the customer journey, the gap between activity and impact gets wider. CS teams that still define value by volume will struggle. Teams that define value by commercial thinking will thrive.

In 2025, every CSM needs a commercial mindset. Not to sell. But to understand the economics behind every customer conversation.

That’s the real shift.

Why Commercial Thinking Matters

The best CSMs already know the answer to one simple question:

How does our product make this customer more successful in a measurable way?

They understand margins
They understand cost savings
They understand how technology changes the economics of a customer’s business

They talk about return not renewal. Impact not activity. Value not volume.

And that’s where AI draws a sharper line than many expected.

If you’re looking at how AI fits into customer success more broadly, this guide to AI in customer success breaks it down.

Automation Doesn’t Replace Judgment

AI can process. It can surface insights. It can flag risk.

But it can’t replace partnership, judgment or business acumen.

These are the skills that turn a CSM from a task executor into a strategic operator. These are the skills that get Customer Success a seat at the table. And these are the skills that AI only makes more important, not less.

The New Line Between Replaceable & Essential

As more of the workflow becomes automated, the industry is heading towards a split. Not between junior and senior roles. But between replaceable and essential roles.

Replaceable roles cling to tasks. Essential roles understand the customer’s economics and use that understanding to guide decisions.

That’s where the profession is heading. And it’s where the opportunity lies for every CSM who wants to build a durable career as AI scales.

Here’s The Real Question

If Customer Success wants to evolve, it has to speak the language of business, not tasks. It has to show how decisions drive outcomes, not how many activities got logged.

And that means one thing.

Every CS leader needs to help their teams build commercial muscle.

Every CSM needs to learn how to anchor conversations in value.

And every organisation needs to decide whether CS will be a cost centre or a growth engine.

AI has already changed the role. Now it’s on us to decide what Customer Success becomes next.

How are you helping your team develop that commercial edge this year?

Want To Go deeper?

If you’re thinking about retention, expansion or how AI fits into your strategy, I work with a small number of SaaS companies on exactly this.

👉 If you’re rethinking your approach, let’s talk.