Every major industrial revolution produced a corresponding shift in how companies support their customers.
Steam power brought remote, asynchronous correspondence: a letter to the manufacturer, a reply by post. Electricity gave us the telephone and instant, synchronous communication. Computing and the internet created digital, omnichannel support at scale.
Each era unlocked something that wasn't possible before. And each one, eventually, hit a ceiling.
We are now, according to Shan Lilja, Co-Founder of Mavenoid, in the fourth, and potentially last, revolution:
“We have entered the last support revolution. Your phone is now a portal to an alien mind that can pass for human.”
It's a striking claim. But spend any time with the argument behind it, and it becomes harder to dismiss.
Why This Time is Different
The previous three revolutions were about reach and speed. Post made remote support possible, telephony made it immediate, and the internet made it scalable and always available.
What none of them solved was understanding. A support agent reading a letter still couldn't see the problem; a telephone operative still had to rely on whatever the customer could describe in words; and a chatbot, however sophisticated, still operates primarily in language.
When language is all you have, a significant portion of what the customer is actually experiencing gets lost in translation.
Multimodal AI changes the dynamic by altering the information available to the system.
By combining vision, audio, and telemetry from connected devices, the AI is moving beyond interpreting a customer's description of a problem to actually seeing and hearing the problem.
“You can spray unlimited intelligence on the situation,” says Lilja. “The next constraint becomes what the system can perceive. Now that constraint is coming down.”
The implications of that are broader than most support leaders have yet fully reckoned with.
The Three False Trade-offs
For much of the past decade, design decisions in AI-powered support have been framed as either/or choices.
Either you use visual guidance, or you use voice; you don't do both in a single session. Either you use generative AI for flexibility, or you use curated, deterministic workflows for accuracy; you pick a side. Either you automate, or you keep humans in the loop.
Lilja argues that multimodal makes all three of these trade-offs unnecessary, and that they were always a function of technical limitation rather than genuine strategic choice.
Great AI support, in his framing, rejects these binaries: voice and visual together, generative breadth with structured grounding, human direction with AI doing the driving.