The $40/seat/month problem
Every major SaaS vendor now offers an AI add-on. It's usually $20-50/user/month on top of the base license. Sounds reasonable for one tool. Now multiply it across your stack.
| Vendor AI add-on | Per user/mo |
|---|---|
| Microsoft 365 Copilot | $30 |
| Salesforce Einstein GPT | $50 |
| ServiceNow Now Assist | $40 |
| Atlassian Intelligence | $25 |
| Slack AI | $10 |
| Workday AI | $35 |
| Total per user | ~$190/mo |
Illustrative pricing. Actual costs vary by contract and tier.
That's nearly $2,300/user/year in AI add-ons alone — on top of the base SaaS licenses you're already paying. For an org with 1,000 knowledge workers, that's $2.3M/year for AI assistants that can't cross tool boundaries.
15 copilots, zero orchestration
Here's the real problem: each copilot only knows its own tool. Salesforce Einstein can summarize a deal. Jira AI can triage a ticket. Slack AI can search conversations. But the actual work your people do spans all of them.
A real workflow, today
A P1 incident comes in. You check ServiceNow for the ticket. Switch to Jira for the engineering context. Pull up Salesforce to see which customers are affected. Open Slack to notify the team. Draft a status update in Teams. Update the ticket.
Six tools. Six tabs. Six siloed AI copilots, none of which can see the full picture. The human is still the glue. That's not automation — that's a premium subscription to autocomplete.
You're building skyscrapers. You need a city.
Each vendor copilot is a building — impressive on its own, with great interiors and smart elevators. But there are no roads between them. No transit system. No shared infrastructure. Just isolated towers.
A city needs roads, utilities, and zoning — not just buildings. Enterprise AI needs protocols, identity, and an orchestration layer — not just per-tool copilots.
What we actually need from vendors
The ask isn't "stop building AI features." It's: give us the tools to build our own orchestration. Expose your capabilities as programmable APIs and tool interfaces so an enterprise AI agent can invoke them.
MCP-compatible tool APIs
Standardized tool definitions that any AI agent can discover and invoke. Not just REST endpoints — structured tool schemas with input/output contracts.
Read + write access
Not just dashboards and reports. Let the AI agent create records, trigger workflows, update statuses, and take action — programmatically and securely.
Unified auth & identity
One identity layer across tools. The AI agent acts on behalf of a user, inheriting their permissions. No separate auth per vendor copilot.
Event streams
Real-time events (ticket created, deal closed, deploy finished) that an orchestration layer can subscribe to and act on. Not polling — pushing.
What end-to-end actually looks like
Imagine one AI assistant that can handle this prompt:
"Find the open P1 in Jira, pull the related customer from Salesforce, check the SLA status in ServiceNow, draft a customer update, and post it to the #incidents channel in Slack."
One prompt. Five systems. Zero tab-switching. The AI agent calls each system through its tool API, chains the results, and executes the workflow end-to-end. The human reviews and approves — but doesn't have to be the glue anymore.
This isn't science fiction. MCP (Model Context Protocol) and similar standards are making this possible right now. The bottleneck isn't the AI — it's whether vendors expose their systems as programmable tools.
The Technostica direction
Build the city, not more buildings.
Instead of buying every vendor's copilot, we're investing in a shared AI orchestration layer. Vendors provide the tools and APIs. We provide the intelligence, the guardrails, and the governance.
When assessing a vendor, don't ask "do you have an AI copilot?" Ask "do you have MCP-compatible APIs? Can an external AI agent invoke your capabilities?"
Build the orchestration infrastructure once — tool registry, auth, guardrails, audit logging — and every team benefits. This is the roads and utilities of your AI city.
One AI agent with one set of guardrails, one audit trail, one set of permissions. Not 15 copilots with 15 separate security reviews.
Start with the highest-value cross-tool workflows. The ones where humans are currently the glue between five tabs. That's where the ROI lives.
The bottom line
The vendor copilot gold rush is creating the same problem all over again — siloed capabilities, duplicated spend, and no cross-system intelligence. We've been here before with SaaS sprawl. Let's not repeat it with AI.
The future of enterprise AI isn't 15 copilots. It's one intelligent orchestration layer that talks to everything — through open protocols, shared infrastructure, and centralized governance. Build the city.