For most teams, it stops being optional the moment support volume grows faster than the team can scale. When repetitive questions start taking up the majority of agent time, response times slip, costs rise, and hiring becomes a constant reaction instead of a plan. That s usually the tipping point.
AI becomes a necessity when customers expect instant answers across channels, when agents spend more time copy-pasting than solving real problems, and when managers lose visibility because tickets pile up faster than they can be triaged. At that stage, automation isn t about replacing people, it s about keeping quality and consistency under control as the business grows.
I don t think AI agents will replace support teams by 2026. What we re seeing across every company we work with is something different. AI becomes the foundation that handles volume, speed, and routine accuracy, while human teams shift into roles that require context, judgment, and empathy.
Most support leaders tell us the same thing: once AI removes the repetitive load, teams finally have the bandwidth to do the work that actually matters. They solve complex cases faster, focus on relationship-building, and deliver a better experience overall.
I ve been talking with a lot of founders and support leaders lately, and something interesting keeps coming up. Many teams want to introduce AI into customer support, but the onboarding and setup process often becomes the biggest hurdle. Not because the tech isn t good enough, but because teams worry about training, accuracy, and maintaining a smooth customer experience during the transition.
I m curious how others are navigating this. Are you rolling AI out gradually? Testing it on internal queries first? Letting it assist agents before going customer-facing? Something else entirely?
The year is almost done, and I have started to be curious about what could be stopping companies from adopting AI for their customer support services?? From my experience, I can tell - fear, fear of losing control. Support leaders worry that AI will say the wrong thing, sound off-brand, frustrate customers, or create more cleanup work for the team. Until they see that an AI agent can learn from their own knowledge base, follow rules, escalate when needed, and stay accurate, they hesitate. Once they realize it can actually reduce workload without breaking trust, adoption becomes much easier. What do you think? Do you agree with me?
Most people think users choose products based on features or price. In reality, support decides who stays.
A cheaper tool becomes expensive fast when every issue turns into a ticket nightmare. Meanwhile, teams keep paying more for products that solve problems and support them when it matters.
Support is not a cost. It is part of the product experience. Fast replies build trust. Clear answers reduce churn. Companies that treat support as a growth lever win.
Most people think users choose products based on features or price. In reality, support decides who stays.
A cheaper tool becomes expensive fast when every issue turns into a ticket nightmare. Meanwhile, teams keep paying more for products that solve problems and support them when it matters.
Support is not a cost. It is part of the product experience. Fast replies build trust. Clear answers reduce churn. Companies that treat support as a growth lever win.
me and my co-founder are building an AI agent because at our last startup we just couldn t keep up with support.
we tried every chatbot out there. they all felt robotic. customers hated it.
hiring more people was too slow + too $$$
so we put together this ai chatbot (think intercom fin but deeper) that trains on your old tickets, learns your tone, doesn t hallucinate, and can actually answer stuff like a real support rep.
