Revenue, retention, recruitment: three pillars for any business leader. The problem is the second is by no means guaranteed once the customer signs on the dotted line. Retention has become harder for customer success teams to master, especially in the age of the “SaaS-pocalypse.”

Customer success is a critical arm of the go-to-market apparatus that strives to help customers maximize value and, ultimately, sign that all-important contract renewal. But as many revenue leaders will no doubt attest: It’s a jungle out there. According to 2025 data from SaaS management platform BetterCloud, the average number of SaaS apps used per company dipped from 112 in 2023 to 106 in 2024; midsize firms (companies with 1,500–4,999 employees) saw a 29% decrease in the number of SaaS apps used.

So what’s the AI play for CS teams? While customer success leaders agree it’s too early to tell if AI is going to negatively impact retention, they believe customer success managers (CSMs) need to use the tools to their best advantage.

“CSMs need to be thinking about, if they want to future-proof themselves in this space: What skills do I need to develop to be able to be the best strategic consultant for my customers?” said Abby Hammer, chief customer and product officer at customer success platform ChurnZero.

More bang for your buck

Customer success leaders are trying to optimize AI tools for their specific needs. Efficiency gains will give them the ability to focus more on retention strategies, like building their relationships with clients and understanding why some deals churn.

“A lot of the conversations I’m having are really around: ‘How can we effectively deploy AI in service of retention?’” said Jessica Starr, VP of customer success at Clari + Salesloft.

Keep reading here for the importance of clean data.—LI

It’s clear there is no exact formula for designing a winning tech stack. It varies by organization, by go-to-market strategy, and by leadership preference. There are, however, some broad tactics emerging around tech stack deployment that could deliver positive outcomes for global business leaders.

Best practices

Firstly, most CROs and revenue enablement leaders will likely need to work with the technology they have at first and build upon it in time (throwing out the baby with the bathwater won’t be an option for all, especially the biggest companies).

Secondly, the tech integrations that companies curate will depend on the specific needs of the business. The key is determining those needs early on, avoiding complexity, and ensuring everyone is on the same page.

Finally, it has become clear that no modern-day tech stack can reach its full potential without some form of AI integration. This could come in the form of automated workflows that are more deterministic in nature, or even fully-fledged agentic systems. The winning strategy could be a mixture of both, but silos are not an option (read more about our multiplayer future). Ensuring the applications work seamlessly with existing data and other tools is also a top priority.

Follow the data

Our data shows 36% of those surveyed said new tech or AI tools didn’t succeed in their revenue organizations because of bad or incomplete data (known more colloquially in the industry as the dreaded “garbage in, garbage out”). So-called clean data is the foundation for all accurate insight, and without it, the foundations of your business are faulty.

Read the full Sales Tech: State of the Industry report here.—BS, LI

There’s more than enough AI FOMO to go around in the business world right now.

C-suite executives fret about getting left behind as more and more companies automate their systems and processes. But jumping in head-first on AI, even when IT pros are being directed to do so, can lead to redundant applications, inefficient use cases, and the dreaded “AI sprawl.”

So how do you follow the broad directives from above to incorporate AI and increase efficiency without sacrificing the carefully optimized IT systems already in place? Working IT professionals told Morning Brew that getting AI integration right relies on careful preparation, planning, and supervision.

Secure the foundation

Before adding any AI or automation to IT functions, it’s important to audit current processes and personnel, Dhiraj Sankala, chief AI and technology officer at healthcare subrogation company Intellivo, told Morning Brew. That’s because incorporating AI can be an opportunity to scale the intelligence that an organization already has, in addition to upping efficiency.

“Start with your people,” Sankala said. “What kind of individuals do we have? What are the skill sets? How do we augment their intelligence, human intelligence, with AI? Same thing with the processes.”

Once IT teams have decided what it is they’re hoping to get out of AI, Sankala said the next step is to evaluate potential AI tools to see if they’re a good fit for the company and its goals. To do so, he told Morning Brew, it’s best to look at things through architectural, risk analysis, and financial lenses.

Keep reading here for the importance of identifying AI use cases.—TC

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