The best AI coworkers of 2026 — honest comparison for marketing, sales, and ops teams
AI coworker is a category-defining label, not a marketing buzzword. Here's an honest comparison of the 6 AI coworkers operators are evaluating in 2026 — Mavrick, Dust.tt, Glean, Decagon, Sierra, Maven AGI. Pricing, fit, where each wins.
AI coworker is the term that's emerging for AI agents that operate as collaborative teammates rather than autonomous tools. The defining traits: they live where the team already works, connect to external systems, and propose actions for explicit human approval. The 'coworker' framing distinguishes them from AI chatbots (no action), AI assistants (suggest don't execute), and autonomous agents (execute without approval gate). The pattern is winning in 2026 because high-stakes operational work — paid media, customer success, support ticket resolution, sales qualification — punishes both inaction and unsupervised action.
This guide is an honest comparison of the 6 AI coworkers operators are actively evaluating in mid-2026. We'll cover positioning, target buyer, pricing, and where each genuinely wins. Mavrick is one of the 6 and we're being transparent about that — see the disclosure paragraph below.
Disclosure: this guide is published on getmavrick.com. Mavrick is the marketing-team-native option in this category. Where another tool is the better pick for your team shape, we'll say so. The honest-balance approach is the same as our /blog/best-ai-agents-for-slack and /blog/best-ai-voice-agents-2026 guides.
What makes an AI coworker (vs an AI agent or AI assistant)?
The category-defining traits, in 2026 usage:
| Trait | AI assistant | AI agent | AI coworker |
|---|---|---|---|
| Lives where the team works | Sometimes (browser tab usually) | Often dashboard-first | Yes — Slack, Teams, or the team's existing channel |
| Connects to external systems | No (chat-only) | Yes | Yes |
| Takes action | No — answers only | Yes — often autonomously | Yes — with explicit approval |
| Approval pattern | n/a (no action) | Permissions model (set + forget) | Approval model (propose + confirm per action) |
| Typical price | Free–$30/mo | $100–$1000/mo | $50–$2500/mo depending on vertical |
The approval-vs-permission distinction is the biggest practical difference between agent and coworker. An AI coworker proposes a specific action with specific parameters and waits for confirmation. An AI agent has been granted permissions and decides when to use them. For irreversible actions (sending an email, transferring budget, modifying a customer record) the approval pattern is the safer default — which is why marketing, sales, and customer-success teams have converged on the coworker framing.
1. Mavrick — the marketing-team-native AI coworker
Mavrick is the AI coworker built specifically for marketing and sales teams operating inside Slack. Connects to 3,200+ marketing-stack integrations via Pipedream Connect (Meta Ads, Google Ads, Stripe, HubSpot, Shopify, GA4, every CRM). Ships an AI voice agent for outbound + inbound speed-to-lead via Telnyx + LiveKit + OpenAI + Cartesia. Cleared-hot approval is contractual via the Privacy Charter (no operator can disable). Public Constitution governing behavior at /constitution. Public system prompt at /system-prompt. Public decline log at /decline-log.
- →Best for: marketing teams + sales teams that operate in Slack and want a coworker shipping pre-wired
- →Pricing: Free (10 missions) + $50/mo Pilot (20K credits ≈ 60-100 missions). Enterprise custom. No per-seat.
- →Limitations: not built for engineering or IT teams (we stay focused on marketing-adjacent verticals); not the right pick for pure customer-support workflows (see Decagon, Sierra)
- →Stack: Anthropic Claude + OpenAI GPT-5 + OpenAI Whisper + Cartesia + Pipedream Connect
2. Dust.tt — the customizable AI coworker platform
Dust positions as a build-your-own AI assistant platform for company-wide internal use. Strong customization story — you create specialized assistants for different team functions, each with its own data sources and tools. More configuration-heavy than Mavrick; more flexible. Used by mid-market and enterprise SaaS companies that want to standardize on a single AI infrastructure across teams.
- →Best for: companies with platform/AI teams that want to ship multiple custom assistants under one infrastructure
- →Pricing: $29/user/mo Pro tier + Enterprise custom. Per-seat model.
- →Limitations: configuration is required (it's a platform); not a turnkey marketing coworker out of the box
- →Stack: their managed pipeline on top of Claude, GPT, and Mistral
3. Glean — the enterprise search coworker
Glean is the enterprise search AI coworker — connects to your company's docs (Notion, Google Drive, Confluence), tickets (Jira, Linear), code (GitHub), chat (Slack), and CRM, then answers questions across all of it from the team's existing surfaces. Strongest at the 'where is the answer hiding in our 200 SaaS tools' problem. Less action-oriented than Mavrick — Glean retrieves and synthesizes; it doesn't generally execute mutations.
- →Best for: 500+ employee companies with sprawling internal-tool footprints
- →Pricing: $20-$40/user/mo + Enterprise custom
- →Limitations: enterprise-scoped pricing (per-seat); retrieval-focused, not action-focused
- →Stack: their own retrieval + reasoning pipeline
4. Decagon — the AI coworker for customer support
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Decagon is the leading AI coworker built specifically for customer support — first-line ticket resolution, escalation routing, KB lookup, customer history surfacing. Their bet: AI handles 60-80% of support volume autonomously with high accuracy; humans handle the remainder. Used by Klarna, Eventbrite, Substack. Specialized; not a general-purpose coworker.
- →Best for: support teams handling >5K tickets/month with deflectable common questions
- →Pricing: enterprise custom — typically $5K+/mo
- →Limitations: support-focused (not built for marketing or sales workflows)
- →Stack: their managed pipeline + foundation model partners
5. Sierra — the conversational AI coworker
Sierra (founded by Bret Taylor + Clay Bavor, ex-Salesforce/Google) positions as the conversational AI coworker for customer-facing teams. Handles support, sales-assist, and customer-success use cases across chat + voice + email. Enterprise focus with substantial deployment partnerships. The competition for Decagon at the upper end of the market.
- →Best for: enterprise customer-facing teams that want a single conversational AI across all channels
- →Pricing: enterprise custom — typically high six figures annually
- →Limitations: enterprise-scoped (not SMB-friendly); requires deployment partner typically
- →Stack: their managed pipeline
6. Maven AGI — the agentic AI coworker for support + ops
Maven AGI handles customer support + internal-ops automation with an agentic execution model. Their pitch: AI doesn't just answer — it takes action (refund issuance, account changes, escalation). Used by Tripadvisor, Stitch Fix. More action-oriented than Glean, more general than Decagon, less Slack-native than Mavrick.
- →Best for: mid-market companies wanting agentic action on the support + ops surface
- →Pricing: custom + per-conversation
- →Limitations: not Slack-native by architecture; less marketing-specific than Mavrick
- →Stack: their managed pipeline
How to pick (decision tree)
- 1.If you're a marketing or sales team that operates in Slack and wants a coworker shipping today → Mavrick. Install in 60 seconds, run a real mission.
- 2.If you're a platform/AI team that wants to ship multiple custom assistants across departments under one infrastructure → Dust.tt.
- 3.If you're a 500+ employee company drowning in 'where's the answer in our 200 SaaS tools?' → Glean.
- 4.If you're a customer-support team with >5K tickets/month and want deflection-first AI → Decagon.
- 5.If you're an enterprise customer-facing team that wants a single conversational AI across chat + voice + email → Sierra.
- 6.If you're a mid-market company wanting agentic action on the support + ops surface specifically → Maven AGI.
What's different in 2026 vs 2025
- →'Coworker' replaced 'agent' as the consensus term for AI that takes action with approval — the agent-with-permissions model lost ground after a few high-profile autonomous-AI incidents in 2025
- →Pricing standardized: per-mission or per-conversation for mid-market coworkers, per-seat for enterprise platforms (Glean, Dust)
- →Vertical specialization beat horizontal — Decagon (support) and Mavrick (marketing/sales) both grew faster than horizontal AI agent platforms
- →Slack-native architecture (not just Slack-integration) became table stakes for ops coworkers
- →Public-Constitution + public-system-prompt transparency emerged as a procurement differentiator — Mavrick was the first to publish; others followed in late 2025/early 2026
- →Cleared-hot approval pattern became the regulatory expectation — financial-services and healthcare deployments increasingly require it
Frequently asked questions
What's the difference between an AI coworker and an AI agent?
Both can take action. The approval pattern is the difference. AI agents typically have a permissions model — granted access, autonomous execution. AI coworkers have an approval model — proposes the specific action, waits for confirmation per action. The approval pattern matters most for irreversible actions (sending email, transferring budget, modifying records). See /ai-coworker-vs-ai-agent for the deep dive.
Are AI coworkers safe?
If the coworker has cleared-hot approval architecturally enforced (not just as a setting), credentials never reach the model directly, the system prompt is public, and the decline log is visible — yes. Ask the vendor for evidence on all four before installing. Mavrick scores yes on all four; see /trust for the posture.
What's the typical pricing for an AI coworker in 2026?
Vertical AI coworkers: $50-$200/mo flat (Mavrick Pilot). Horizontal platforms: $20-$40/user/mo (Glean, Dust Pro). Enterprise specialists: $5K+/mo (Decagon, Sierra). Action-oriented mid-market: custom + per-conversation (Maven AGI). Per-seat pricing is regaining ground at enterprise; vertical SMB coworkers are still flat per-workspace.
Can I use multiple AI coworkers together?
Yes, and most companies will. The pattern emerging: one horizontal platform (Glean for search across the org) + 1-2 vertical specialists (Mavrick for marketing, Decagon for support). The vertical specialists are deeper in their domain; the horizontal platforms are broader in reach. They compose rather than compete.
What's the best AI coworker for marketing teams?
Mavrick — we built it specifically for marketing-adjacent verticals (marketing, sales, agencies, ecommerce, SaaS growth, B2B). The other coworkers in this list are either horizontal (Dust, Glean) or non-marketing-specific (Decagon support, Sierra customer-facing, Maven support+ops). For marketing in 2026, Mavrick is the assembled coworker.
What's the best AI coworker for customer support?
Decagon and Sierra are the category leaders, in different price tiers. Decagon is mid-market-friendly with strong deflection rates; Sierra is enterprise-focused with broader channel coverage. Mavrick is not built for support — we stay focused on marketing/sales.
What to do next
If you're marketing or sales-focused and operate in Slack — install Mavrick in 60 seconds. Start free, 10 missions, no credit card. If you're evaluating across verticals, the decision tree above is the fastest path. For deeper dives: /ai-coworker (the category), /ai-coworker-for-slack (the Slack-native pattern), /for/speed-to-lead (the 14-year-old problem Mavrick solved), /constitution (Mavrick's published governance).
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Brian MacDonald
Brian MacDonald is the founder of Mavrick, the AI coworker for marketing teams. Previously ran SetupClaw.tech, an AI deployment service for SMBs. Read more about Brian and the mission.