By Carlos A. Delcid

The role nearshore teams play in the SaaS vs AI war

Why this matters if you’re a SaaS CEO, COO, or CTO

• AI and no‑code have made it easier than ever to build software, which means your product is easier to copy.

• Your real edge is shifting from “we have this feature” to how fast you ship and how well you support customers.

• With 11–200 people, you can’t just hire endlessly in the U.S. or let support quality drop while you automate.

• Strategy‑first nearshore teams in LATAM give you the human layer you need to win: more engineering velocity and better support, without blowing up burn.

If you’re building SaaS in 2026, this is the game you’re actually playing.

AI didn’t kill SaaS. It killed weak SaaS.

You’ve probably heard some version of:

“AI is going to kill SaaS. Why pay for subscriptions when everyone can build their own tools?”

In early 2026, even Forbes posed the question: “Did AI really kill SaaS?”

The honest answer: no.

AI didn’t kill SaaS.
It killed average SaaS.

Yes, AI and no‑code tools make it easier to:

• Spin up prototypes

• Connect systems

• Automate simple workflows

But none of that replaces:

• Reliable infrastructure

• Ongoing product evolution

• Real support when things break

• Human judgment in complex or emotional situations

AI made execution more important, not less.

The companies that are losing right now aren’t losing because “SaaS is over.” They’re losing because:

• Their product barely evolves

• Their roadmap moves too slowly

• Their support experience is frustrating

• Their team can’t keep up with AI‑accelerated competitors

AI didn’t remove SaaS.
It raised the standard.

The real shift: SaaS + AI + operational excellence

In 2026, the battle is not SaaS vs AI.

It’s:

SaaS + AI + operational excellence.

Almost everyone can plug AI into their stack.
Very few can run a tight operating system around it.

Your differentiation is now:

• How fast you ship meaningful improvements (engineering velocity)

• How quickly and thoughtfully you respond to customers (support quality)

• How well your human teams work with AI, not against it

That’s where nearshore teams change the game.

Where nearshore teams fit in the SaaS vs AI war

1. Nearshore engineering: turning AI into real product velocity

AI coding tools help your developers:

• Generate boilerplate

• Speed up some tasks

• Catch certain issues earlier

They do not replace:

• Architecture and system design

• Managing tech debt and refactors

• Debugging production issues

• Prioritizing what to build next

You still need strong engineers. You just need more capacity than your U.S. budget alone can support.

Embedded nearshore engineering teams in LATAM help you:

• Increase shipping capacity without exploding burn

• Work in real time across similar time zones (no overnight lag)

• Combine senior engineers + AI tools to move from “prototype” speed to “production” reliability

The key word is embedded:

• Same Slack, same repos, same rituals

• In your standups, demos, incident calls, product reviews

• Held to the same bar as your core team

Not “outsiders doing tickets.”
Actual teammates.

2. Nearshore advanced support: AI on the front line, humans where it matters

AI can:

• Answer simple questions

• Handle standard flows

• Trigger basic actions

It still struggles with:

• Edge cases across multiple systems

• Emotional, high‑stakes moments

• Situations where trust and judgment matter more than speed

If a customer gets stuck in a bot loop during an important moment, they won’t care how advanced your model is. They’ll remember that no one helped.

Modern nearshore support teams in LATAM can:

• Sit behind your AI chatbot and automation

• Take over complex or high‑value conversations

• Bring bilingual communication, empathy, and deep product understanding

• Turn moments of frustration into moments of trust

This is not the old call center model.
It’s advanced, AI‑augmented support that protects retention and NRR.

A simple playbook for SaaS leaders in 2026

If you’re a SaaS leader, here’s a practical way to put this together.

Step 1: Use nearshore engineering to increase capacity where it matters most

Ask:

• Where are we consistently behind: features, reliability, integrations, tech debt?

• Which of those workstreams are nearshore‑ready (time zone + context heavy, but not legally tied to location)?

Then:

• Add embedded LATAM engineers into those lanes

• Make AI tooling part of their daily work (code assistants, test generation, analysis)

• Hold them to the same 90‑day success criteria you’d use for a core hire (output, quality, ownership)

Step 2: Use nearshore advanced support to protect and grow revenue

Look at your support today:

• Where are customers getting stuck in automation?

• Which conversations are too nuanced for bots?

• Where are slow or poor responses creating churn risk?

Then:

• Put strong nearshore advanced support teams behind your AI front line

• Let AI handle repetitive tickets, and route complex issues to bilingual, product‑literate humans

In an AI‑heavy market, loyalty will come from how you handle the hard tickets, not just how quickly you auto‑resolve the simple ones.

Step 3: Make nearshore a permanent part of your operating model

The goal isn’t to “try a nearshore dev once.”

The goal is:

• Nearshore engineering and support are baked into your headcount and capacity planning

• AI is an amplifier on top of a strong human system, not a band‑aid for a weak one

• You have a clear, intentional mix: what stays U.S.‑based, what moves nearshore, and how they work together

That’s how you win the SaaS vs AI war:

Not by fighting AI, but by combining it with high‑quality, well‑designed human teams.

Where Puzzle fits

At Puzzle, our mission is simple:

Help bold companies achieve the growth they’re looking for, and give talented people a community where they can grow and thrive.

In the context of SaaS vs AI, that means:

• Designing strategy‑first nearshore teams around your roadmap and customer experience, not just filling seats

• Building embedded engineering teams in LATAM that use AI tools and work inside your existing rituals and stack

• Building embedded advanced support teams that sit behind your AI front line and handle complex, human situations

• Owning sourcing, vetting, payroll, equipment, and secure infrastructure so your leaders can focus on product and customers

AI is not the SaaS killer.

But it is exposing who can truly operate.

The SaaS companies that win in 2026 will be the ones that combine:

• Strong products

• AI as a lever

• Nearshore teams that give them the speed and support to out‑execute everyone else.

That’s the role nearshore plays in the SaaS vs AI war.
And that’s exactly what we help our partners build at Puzzle.