How to Use AI at Work: 10 High Impact Applications

You can now save hours at your workplace using AI. There are tons of high-effort, repetitive tasks that AI can do for you, like sending follow-up emails or updating CRMs. You can do this without constant prompting or back-and-forth with the top AI tools.

In this article, we’ll cover:

• What AI should do in the workplace
• 10 high-impact use cases, from scheduling to CRM updates
• How to get started without prompt engineering 
• What to look for in AI tools 
• How to avoid the common myths
• How to select the right AI tools

Let’s first explore what using AI at work means.

What does using AI at work mean?

Using AI at work means delegating repetitive tasks to advanced software so you can save time and focus on decision-making. It helps with day-to-day execution, like sorting emails, summarizing meetings, or updating your CRM. 

AI at work generates ideas, handles real-time tasks, and reduces mistakes. The top tools won’t require endless prompting or having to learn a programming language.

AI that handles tasks vs AI that just helps you write

AI can help with writing, like drafting emails, summarizing text, or polishing phrasing. But once that’s done, you're still stuck doing everything else manually.

Task-handling AI adds on to the writing abilities and helps you automate related tasks like sending the email, updating your CRM, pinging teammates in Slack, triggering follow-ups, and more. Instead of prompting it step-by-step, you delegate more of the workflow.

Prompting vs automation

Prompting works for occasional tasks. But if you’re doing the same thing every week, like writing updates, chasing approvals, or recapping calls, you don’t want to prompt. You want automation that runs those tasks without extra input.

Workflow automation means giving AI a job once and letting it handle the details every time. No prompt engineering. No back-and-forth.

Next, let’s look at 10 practical ways people are already using AI at work in 2025.

10 high-impact ways to use AI at work in 2025

AI can now handle routine jobs like scheduling and follow-ups. Below are 10 examples of using AI at the workplace to execute tasks:

1. Inbox triage and email response

Most people spend hours each week just sorting through email. AI can cut that time by auto-prioritizing messages, drafting replies, flagging action items, and even routing messages to the right person.

For example: An AI agent monitors your inbox, flags anything high-priority, and drafts responses using your tone of voice. If something needs input from a teammate, it drops it in Slack and tags the right person.

2. Meeting summaries and action items

When you take notes during calls, the conversation gets interrupted and it takes up time. AI can record, transcribe, summarize, and send action items before your next meeting starts.

For example: An AI tool joins your Zoom, transcribes the meeting, writes a clean summary in Google Docs, and can recognize key decisions or action items, then shares them on Slack. It can also create follow-up tasks in tools like Asana or ClickUp.

3. AI scheduling and calendar negotiation

Coordinating schedules is more painful than it should be. AI can handle back-and-forths, propose times, send invites, and reschedule if needed.

For example: A scheduling agent knows your availability, negotiates times with others, books the slot, and adjusts automatically if someone declines or changes it.

4. CRM updates and lead follow-ups

Sales teams often lose hours to manual data entry. AI can pull details from emails or calls, update CRM fields, and send timely reminders to follow up.

For example: After a sales call, the AI logs key info in HubSpot, sets a reminder for follow-up, and drafts the next email based on how the call went.

5. Recap and search across docs or Slack

Information gets buried fast, especially in docs, emails, or chat. AI can surface what’s relevant and summarize past conversations without digging through threads.

For example: Before a meeting, you ask the AI about the decision you took on pricing last quarter. It’ll grab the summary from a Notion doc and link to the Slack thread where the decision was made.

6. Workflow approvals and reminders

Approvals often stall projects. AI can chase people for sign-offs, send reminders, log timestamps, and escalate when someone blocks progress.

For example: A hiring manager forgets to approve a candidate review. The AI agent nudges them on Slack, then escalates to the Director if there's no response after 24 hours. Once approved, it notifies the recruiter and updates the hiring tracker.

7. Voice-to-action: Meetings, calls, call notes

If your day runs on spoken communication, like calls, huddles, and syncs, AI can turn conversations into actions. That means fewer follow-ups and less manual tracking.

For example: After a client call, AI transcribes the meeting, identifies key takeaways, updates your CRM, and sends a summary to the internal team via Slack.

8. Auto-generating reports and updates

Instead of pulling data manually every week or month, AI can generate reports based on inputs from your tools. They can be weekly status updates, CSAT summaries, or revenue snapshots.

For example: Every Friday, an AI agent pulls feedback from Help Scout, assembles it into a customer satisfaction report, and shares it with the CX team on Slack.

9. AI-based onboarding or team SOP docs

New teammates often ask the same questions. AI can build onboarding guides and SOPs by pulling info from docs, call recordings, and past conversations.

For example: A new hire may ask about the process to issue refunds in Slack. The AI returns a clean, step-by-step SOP that pulls steps from internal docs and call transcripts.

10. Decision support: Surfacing relevant information

In quick and layered discussions, it’s easy to lose context. AI can listen in, identify decisions being made, and extract supporting info or past conversations in real time.

For example: During a vendor negotiation, AI surfaces your contract from six months ago and flags the payment terms. You get what you need at the moment, without digging.

Now that we’ve covered specific tasks AI can take over, let’s look at how this applies across different teams. 

‍

{{templates}}

‍

Examples of AI in the workplace 

Different teams face different bottlenecks. But across roles, the pattern is the same: AI helps by handling the stuff that slows people down, whether it’s updating a CRM, pulling a report, or chasing approvals.

Here’s how AI is showing up across five core functions:

Sales & RevOps

AI helps reps follow up faster, log calls, and keep the CRM clean. For example, after a discovery call, an AI agent logs notes in Salesforce, fills in missing deal fields, and sends a follow-up email draft. It also pings the account executive (AE) in Slack with next steps.

Marketing

Teams use AI to track campaigns, generate reports, and update performance dashboards. For example, every Monday, the AI pulls campaign data from GA4 and HubSpot, summarizes it, and drops a Slack update for the team with key trends.

Operations

Ops teams lean on AI to enforce SOPs and move tasks forward. For example, when a new request hits a shared inbox, AI tags it, assigns the right owner, and monitors for blockers. If no one picks it up in 2 days, it escalates.

Customer support

Support teams use AI to tag incoming emails, suggest replies, and create summaries for future training. For example, AI scans support inboxes, tags by issue type, and sends a daily summary of recurring problems to the customer experience (CX) lead.

Healthcare/Admin

In clinical and admin settings, AI handles note-taking, record summarization, and scheduling. For example, after a patient call, AI generates SOAP notes, updates the EMR, and schedules the next check-in on the provider’s calendar.

Misconceptions still hold some people back from trying AI in their workflows. So, let’s address the common myths and how things have changed in 2025.

Common myths about using AI at work

Many teams still hesitate to use AI in daily work, even though tools have improved significantly. Some of that hesitation comes from outdated assumptions, most of which don’t hold up anymore.

Let’s clear up a few of those myths:

AI replaces jobs

AI replaces repetitive tasks and jobs like manual logging, sending the same messages, and copy-pasting data across tools.  This allows people to focus on analysis, decision-making, and teamwork.

It’s just a writing tool

It used to be a writing tool, but it isn’t anymore. AI agents can handle scheduling, CRM updates, onboarding, task routing, and follow-ups. Writing is just one of many functions.

You need to prompt it right

No, you don’t need prompts with workflow-level tools. Prompting works for one-off tasks, but AI agents can run recurring workflows without step-by-step instructions. They don’t need clever phrasing but a clear job description.

What the data says

McKinsey’s 2024 report titled “The State of AI” found that organizations across different domains reduced costs by more than 40% using AI. The biggest ROI came from automating routine operations, not replacing people.

Now, the question is how to start using AI at work. Next, we answer that question in detail.

Simple ways to use AI at work without needing prompts

You don’t need to get good at prompting to start using AI at work. The easiest wins come from automating tasks you already do with fewer clicks and less handholding.

Here’s where to start:

1. Pick repetitive tasks you do weekly

You can start automating follow-ups, scheduling, and inbox cleanup. These are high-effort, low-value jobs. If you’re doing the same task more than twice a week, it’s a good candidate for automation.

2. Use tools that plug into what you already use

Look for tools that integrate with your existing calendar, email, docs, or CRM, so you’re not rebuilding your workflow from scratch. This matters if you want results fast.

3. Choose AI agents that follow goals, not just commands

The best tools don’t wait for instructions. Once configured, they understand context and act on intent. For example, instead of asking an AI agent to send an email, you assign the outcome: Follow up with no-show leads after 3 days.

4. Pilot a real workflow with AI

Instead of testing features, test a full workflow. Set up an AI agent to triage your inbox or send weekly check-in emails. Give it a clear outcome. Then evaluate how well it does the job.

Lindy offers a free plan that automates up to 400 tasks each month without coding. Start by connecting your tools and let Lindy handle the routine work.

If you're evaluating AI tools for your workplace, let’s understand what features and capabilities matter and what to ignore.

How to choose the right AI tools for work

To select the right AI tool for your team, pick software that matches your workflow and connects with your existing systems. Look for integration, context memory, and task ownership.

Here’s what to look for:

Context memory

You shouldn’t have to repeat yourself. Good AI tools remember past actions, client history, or what was discussed last week. These tools make smarter decisions and skip repetitive tasks by using past context.

For example, an AI agent reads the last three Slack messages in a thread and drafts a response that doesn't rehash what's already been said.

Task ownership

AI takes task ownership: It recommends actions and takes them without needing your input. 

For example, instead of saying “You should follow up,” it schedules the email, sends it, and logs the result.

Integrations with your stack

An AI tool isn’t worth it if the AI doesn’t connect to your core tools, like calendar, email, CRM, and docs. Integration is a necessity for automation to be useful. 

For example, a connected agent can pull a Zoom transcript, create tasks in Asana, and update your CRM in one go.

Auditability and transparency

You need to know what the AI did, and why. Look for tools that show logs, trigger history, or give you the option to review and approve during onboarding. 

For example, the tool sends you a Slack message that says: Just sent this follow-up. Want to review before next time?

Lindy supports all of the above, like task ownership, context, 7,000+ integrations, and full activity logs. Use the evaluation framework we just discussed to evaluate the tools, no matter which one you’re considering.

‍

{{cta}}

‍

Let Lindy be your AI workplace automation app

If you want affordable AI automations, go with Lindy. It connects to your calendar, CRM, and inbox and lets you build AI agents to automate CRM updates, scheduling, follow-ups, and more.

Lindy offers 7,000+ integrations and dozens of plug-and-play templates.

Here’s how Lindy supports workplace use cases: 

• AI Meeting Note Taker: Lindy creates structured meeting notes in Google Docs after recording and transcribing conversations. After the meeting, Lindy can send Slack or email summaries with action items and can even send emails or meeting reminders via HubSpot and Gmail.‍
• Sales Coach: Lindy can provide custom coaching feedback, breaking down conversations using the MEDDPICC framework to identify key deal factors like decision criteria, objections, and pain points​.‍
• Automated CRM updates: Instead of just logging a transcript, you can set up Lindy to update CRM fields and fill in missing data in Salesforce and HubSpot — without manual input​. ‍
• AI-powered follow-ups: Gong stops at transcription, but Lindy agents can send follow-up emails, schedule meetings, and keep everyone in the loop by triggering notifications in Slack by letting you build a Slackbot. ‍
• Lead enrichment: You can configure Lindy to use a prospecting API (People Data Labs) to research prospects and to provide sales teams with richer insights before outreach. ‍
• Automated sales outreach: Lindy can run multi-touch email campaigns, follow up on leads, and even draft responses based on engagement signals​.‍
• Cost-effective: Automate up to 400 monthly tasks with Lindy’s free version. The paid version lets you automate up to 5,000 tasks per month, which is a more affordable price per automation compared to many other platforms. 

Try automating up to 400 tasks with Lindy for free.

Frequently asked questions

What are the best AI tools for work?

Some of the best AI tools are Lindy, Zapier, Make, and ChatGPT. 

It depends on what you're trying to do:

• For task automation: Tools like Lindy, Zapier, or Make can run workflows across apps.
• For writing: ChatGPT, Notion AI, or Grammarly work well.
• For meeting notes: Tools like Otter.ai or Fireflies.ai.

Can AI help reduce busywork?

Yes, AI helps reduce busywork, especially when it’s used for high-frequency tasks like inbox management, scheduling, and follow-ups. That's where AI adds the most value with consistent execution and no manual effort.

What are real examples of AI in the workplace?

Some real examples of AI at work include:

• AI updates your CRM after a call
• Sends summaries of team meetings
• Reminds your manager to approve a request
• Creates onboarding docs for a new hire
• Flags repeated support issues in your inbox

Is using AI at work safe and secure?

Yes, using AI at work is safe and secure, as long as the tools offer enterprise-grade encryption and comply with the security norms. Lindy, for example, uses AES-256 encryption and complies with HIPAA and SOC 2 standards.

Always check a provider’s security and compliance page before connecting sensitive data.

How can I use AI if I’m not technical?

You can use AI if you’re not technical with tools that offer chatbots, pre-built agents, templates, or integrations with apps you already use. You shouldn’t need code or prompt engineering to get value.

Can AI agents manage tasks like inbox and scheduling?

Yes, a well-configured AI agent can manage tasks like triaging your inbox, sending replies, scheduling meetings, and following up on missed invites without needing your input each time.

What’s the difference between AI assistants and AI agents?

AI assistants wait for prompts while AI agents act on intent. An assistant might write a reply when asked, but an AI agent will notice you haven’t replied in 3 days, draft the email, and send it without being asked.

How does Lindy compare to other workplace AI tools?

Lindy, compared to general-purpose tools like ChatGPT or automation tools like Zapier, combines AI-powered automation, context awareness, and integrations into one platform. It helps reduce manual work by automating repetitive tasks across popular business tools, though some workflows may still require manual setup or oversight.