Top 6 AI Agents for Building Workflow Automations in 2027

Many tasks involve multiple steps across different apps, and AI agents can automate these workflows completely, so everything is done on time without needing to switch apps or copy data manually.

Below, you'll see what to look for and how six AI agents compare, so you can pick the one that fits how you work.

What to look for in AI agents for building workflow automations

These six points will help you when you're choosing AI agents for building workflow automations. They show how much work an automation will save after the first week, not just on day one.

Building the AI agent. Look for AI agents you can build and start using without code, mapping, or a long setup. Every step before the first workflow, like coding, creating skills, or waiting on a developer, delays the payoff, so it takes longer before anything runs on its own.
Building workflows in plain language. Look for AI agents that can build the workflow from plain language, instead of making you map every step, and where multiple AI agents can work together on one workflow. Multi-step workflows across multiple apps are easier to build and fix when each AI agent has its own job and tools, instead of one AI agent handling everything.
Updating and fixing workflows. Look for AI agents that learn from your corrections. Most of the cost of automation is maintenance, and workflows that need rebuilding every time the process changes fall out of date.
Connecting tools. Look for AI agents that can connect to the tools you use, with little setup. A workflow is only as useful as the tools it can act in.
Security and control. Look for clear permissions and approvals. Workflows run on their own, often while nobody is watching, so one mistake can spread before anyone notices.
Sharing with your team. Look for AI agents you can share with teammates. Your automations keep working when you're busy or away, and the rest of the team gets the same time back.

Most tools do well on one or two of these points. The ones worth choosing cover all six, so building a workflow is fast, keeping it running is easy, and the whole team can rely on it.

The 6 best AI agents for building workflow automations

In each tool section below, you'll see how easy it is to build the AI agent, how workflows get built and kept up to date, and whether you can share them with your team.

1. Zenzap

Zenzap is one of the best AI agents for building workflow automations. In Zenzap, you can build multiple AI agents that work together on your workflows.

Building an AI agent in Zenzap

To build an AI agent in Zenzap, all you need is the Zenzap app. Download it, name your AI agent, and connect your work tools. Adding an AI agent takes one click, with no code, no developer, and nothing to configure, and it's ready to work within minutes.

Building workflows in Zenzap

To build workflows in Zenzap, you just tell the AI agents what you want in plain language, and they build the workflow in the background. Zenzap AI agents are proactive, so they also suggest what they can do instead of waiting for the request.

Updating and fixing workflows in Zenzap

To update or fix a workflow in Zenzap, you just send the AI agents a message in the group chat where the workflow runs, for example, "send it as a list next time." The AI agents update the workflow and remember the change, so it takes one message.

Connecting tools in Zenzap

Zenzap AI agents can connect to 2,000+ work tools with one click.

Security and control in Zenzap

In Zenzap, AI agents have access levels for each tool, and you have to approve before they create, change, or delete anything.

The AI agents never see your passwords or login keys, and connecting one app gives no access to any other. When working with other people, you can decide who can add AI agents and who can access each one.

You own your data, and it's never used to train AI models. Zenzap is also HIPAA, SOC 2, GDPR, and ISO 27001 compliant.

Zenzap AI agents can be shared with your team, and your teammates can also build their own AI agents and workflows.

Zenzap AI agents are multiplayer. Once your workflows are running, add teammates to the group chat with your AI agents, and everyone can ask them for help, see what the workflows did, and correct them.

Each AI agent has its own memory per topic, so what it knows in one chat stays in that chat.

Limitations of Zenzap

Zenzap AI agents only work in chats their owner is in. If the owner leaves a chat, the AI agents leave with them.

2. Viktor

Viktor is an AI employee that works inside Slack and Microsoft Teams.

Building an AI agent in Viktor

To build an AI agent in Viktor, you need a Slack or Teams workspace and admin rights to install an app. However, you switch on one AI employee rather than building separate AI agents for different jobs.

Building workflows in Viktor

To build workflows in Viktor, you let it watch how the team works, and it proposes automations on its own, so you don't have to spell out every workflow first.

Updating and fixing workflows in Viktor

To update or fix workflows in Viktor, you tell it in Slack or Teams, and it also picks up changes as it keeps observing how people work. Anyone it works with in a channel can do this. However, some users ask for more control over when it acts on its own.

Connecting tools in Viktor

Viktor can connect to your tools during setup.

Security and control in Viktor

Viktor offers granular per-person permissions, approval buttons on irreversible actions, and access to a channel only when invited.

Viktor sits in shared channels and works alongside the team, though every workflow runs through that one AI employee.

Limitations of Viktor

Viktor needs Slack or Teams first, so that's two vendors to run. Teams that want multiple AI agents, each with its own job, tools, and permission level, may find one shared AI employee limiting.

3. Twin

Twin is an AI agent platform for back-office automation.

Building an AI agent in Twin

To build an AI agent in Twin, you need a clear description of the recurring job, your data sources, the output format, and any review rules. Twin is built for non-technical people, but how long it takes depends on how complex the job is and how well it's described up front.

Building workflows in Twin

To build workflows in Twin, you describe the job in conversation, and Twin builds the AI agent around it.

Updating and fixing workflows in Twin

To update or fix workflows in Twin, you need to go back to Twin's platform and update it. However, each time the job changes, someone has to make that update, so keeping workflows current stays on your list.

Connecting tools in Twin

Twin AI agents can work in the tools you connect and can use a web browser for sites that don't have an API.

Security and control in Twin

Twin offers approval workflows on sensitive tasks, plus human review rules you set when building the AI agent.

Twin AI agents can work together with shared memory and send their results to your team in Slack, email, or a dashboard. However, your team only gets the reports. There's no shared workspace where teammates can work with the AI agents directly.

Limitations of Twin

The work runs on Twin's platform, away from where the team talks, and comes back as a report.

4. Grok Bot

Grok Bot is xAI's team of AI agents that work on their own, each on a cloud computer hosted by the platform.

Building an AI agent in Grok Bot

To build an AI agent in Grok Bot, you need a Grok Bot account and the accounts or plugins you want the Bot to use.

Building workflows in Grok Bot

To build workflows in Grok Bot, you ask a Bot to follow along the next time you do the job yourself, and it takes over from there.

Updating and fixing workflows in Grok Bot

To update or fix workflows in Grok Bot, you ask the Bot in your own thread. Bots keep working while you're offline, but since the work happens on the Bot's computer, only the person who owns the Bot can check or change it.

Connecting tools in Grok Bot

Grok Bots reach apps, tools, and websites directly, using the accounts and plugins you grant them.

Security and control in Grok Bot

Grok Bots don't hold credentials, and actions that need approval show the suggested action first.

Grok Bot is built for individuals, so you can't share your Bots or workflows with your team. Its group chats are for several of your Bots working together, not for teammates.

Limitations of Grok Bot

Grok Bot is for individuals only, so your team can't work with your Bots. All of one person's Bots also share that person's computer and access, so permissions belong to the person rather than the job. Audit logging is off until someone turns it on.

5. Buzz

Buzz is Block's open-source workspace where people and AI agents work side by side in channels.

Building an AI agent in Buzz

To build an AI agent in Buzz, you need a developer, a development environment, Docker, a Rust and Node toolchain, and your own AI agent. The developer clones the repo, runs setup and build, and starts the relay and desktop app.

Building workflows in Buzz

To build workflows in Buzz, you need to bring an AI agent, and Buzz gives it a place to work. The workflows depend on what that AI agent can do.

Updating and fixing workflows in Buzz

To update or fix workflows in Buzz, a developer changes the AI agent you brought or the systems wired into it. That takes developer time each time, and keeping workflows current is up to your team.

Connecting tools in Buzz

Buzz can connect to your tools, from databases and CRMs to codebases and file systems.

Security and control in Buzz

Buzz gives each AI agent its own cryptographic identity and configurable permissions, and self-hosting gives you ownership of your data and infrastructure, though that system is yours to run.

Buzz lets you add AI agents to channels as full participants, not assistants attached to one person.

Limitations of Buzz

Buzz is built for engineering teams, so teams without a developer don't have a way in.

6. Instinct

Instinct is a personal AI assistant you can text or call, which works on a cloud computer with browser access.

Building an AI agent in Instinct

To build an AI agent in Instinct, you first need an invite, since Instinct is invite-only and has a waitlist. Once you're in, you just text it, and it starts working.

Building workflows in Instinct

To build workflows in Instinct, you just send a text with what you need, and the Instinct AI agent takes care of it.

Updating and fixing workflows in Instinct

To update or fix how Instinct works, you text it in the same thread. Every task builds up in that one continuous thread.

Connecting tools in Instinct

Instinct can connect to email, messaging apps, screen captures, audio and location, and its browser lets it act on sites with no API.

Security and control in Instinct

Instinct has limited security and control, since it's built for one person rather than a company, so it doesn't offer team admin controls, and its terms allow user materials to be used for model training.

Instinct is a personal assistant with no workspaces or teams, so you can't share it or its workflows with your team.

Limitations of Instinct

Instinct is built for personal life admin rather than work a team does together.

Workflow automations you can build with AI agents

Workflow automations can save you hours every week. Here are workflow automations you can build with AI agents:

Workflow automations for sales teams

Lead handoff alert: AI agents can send hot inbound leads to sales with full context.
Webinar follow-up: AI agents can send attendees the recording and route hot leads to sales.

Workflow automations for marketing teams

Weekly marketing report: AI agents can pull traffic, signups, and spend into one report.
Ad spend alert: AI agents can flag campaigns overspending or underperforming against target.
Content calendar check-in: AI agents can ask each contributor for draft status and flag pieces at risk.

Workflow automations for product teams

Weekly feedback digest: AI agents can roll up customer feedback from every channel into one read.
Roadmap status pulse: AI agents can ask each owner for status and post one update to the team.
Launch readiness check: AI agents can collect sign-off from every team before ship day.

Workflow automations for engineering teams

Incident recap: AI agents can draft the post-mortem from alerts, logs, and the incident thread.
Build failure alert: AI agents can post failed builds to the team with the breaking commit.
Sprint scope watch: AI agents can flag tickets added mid-sprint and commitments at risk.

Workflow automations for design teams

Design request intake: AI agents can turn requests from other teams into briefs in the design queue.
Dev handoff pack: AI agents can bundle specs, assets, and edge cases for the engineering handoff.

Not all AI agents on this list can build these workflows, but with Zenzap, you can build all of these workflow automations and a lot more, with multiple AI agents working together on each one.

Which AI Agents Are Best for Building Workflow Automations?

The right pick depends on how you work today and who will build the workflows.

If you want to build and update workflows in plain language, with multiple AI agents working together, and share them with your team in one chat, choose Zenzap.
If your team already runs on Slack or Teams and wants only one AI employee that suggests automations, choose Viktor.
If you want back-office jobs running in the background and just want to see results reports, choose Twin.
If you want Bots that learn by watching you and keep working while you're offline, choose Grok Bot.
If you have developers and want to host your own workspace for AI agents, choose Buzz.
If you want a personal assistant for your own life admin, choose Instinct.

Whichever AI agents you choose for building workflow automations, think about who will build the workflows, who will fix them when the work changes, and whether you can share them with your team. The answers decide whether your automations keep saving time or end up abandoned.

Start Building Workflow Automations That Keep Running

A workflow automation is only worth building if it's still running a month later. That comes down to how quickly people can get started, how easily the workflow changes when the work does, and whether more than one person can see and fix it.

Start small. Pick one repeat job you do every week, describe it to AI agents, and let it run for a few weeks. Once you trust it, add the next one, and bring your team into the chat so they can use and update those workflows too.

FAQ

What's the difference between AI agents and regular automation?

The difference between AI agents and regular automation is flexibility. Regular automation follows a fixed script and breaks when something changes. AI agents understand plain language, so you tell them what you want instead of setting up rules, and they adjust when you correct them.

How hard is it to build AI agents for workflow automation?

How hard it is to build AI agents for workflow automation depends on the tool. Some need a developer, an existing chat app, or a detailed job description first. In Zenzap, you download the app, add an AI agent in one click, and connect your tools, with no code.

Is it secure to let AI agents run workflows in my tools?

Letting AI agents run workflows in your tools is secure when you can control what they do. In Zenzap, you can set access levels for each tool; you have to approve before AI agents create, change, or delete anything, and you own your data.

What's the difference between asking AI agents something and a workflow?

The difference between asking AI agents something and a workflow is repetition. Asking AI agents something gets a one-time answer. A workflow is the same job running on its own, on a schedule or when something happens, so the value adds up without anyone asking.