How to Use AI to Optimise Your Day to Day Workflows

Most people do not lose time on big strategic decisions. They lose it in small moments.

You open your inbox to reply to one message. Twenty minutes later you are buried in threads, trying to remember what still needs a response.

You sit down to update a spreadsheet. Thirty rows in, your eyes glaze over and you are second guessing every number.

You try to book one meeting. It turns into six emails back and forth to find a time that suits everyone.

This is where AI earns its keep.

Used well, AI becomes a practical assistant that tidies up your day to day workflows. It does not replace your judgement. It simply takes on the repetitive admin so you can focus on the work that actually moves the needle.

In this guide we will walk through how to use AI to optimise:

• Email management
• Data entry and document processing
• Scheduling and calendar management

Then we will look at four leading AI models

GPT, Claude, Gemini and Perplexity and how to pick the right one for different tasks.

This is about making your workday feel lighter, not adding another layer of complexity.
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Why AI is such a good fit for everyday workflows

Most day-to-day workflows share 3 traits:

1. They are repetitive
2. They follow patterns
3. Mistakes and delays add up over time
   

AI is very good at pattern recognition and repetition. Once you set it up, it happily churns through inboxes, forms, calendar invites and messages without fatigue.

At a high level you can use AI tools in 3 ways (this is different from the LLM training and ML projects we do!):

As an assistant inside tools you already use

• For example, ChatGPT inside your browser, or Gemini inside Gmail and Google Docs.

As automation inside workflows

• For example, Zapier flows that pass emails or files through an AI, then update your CRM or spreadsheet.

As a research and thinking partner

• For example, using Claude to analyse a long report, or Perplexity to gather up to date information with citations.
  

You do not need to adopt everything at once. Start with one painful workflow and apply AI there first.

Let us start with the biggest daily time sink for most knowledge workers.
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Using AI for email management‍

If your inbox is constantly overflowing, AI can turn it from a source of stress into a sorted task list.
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1. Prioritise and triage faster

Modern email clients and AI tools can:

• Automatically label and categorise emails
• Identify urgent or important senders
• Sweep low value messages into separate folders

In practical terms, this means:

• Sales and client messages surface at the top
• Newsletters and promotions land in a reading folder
• Automated notifications are tucked away for later

How to set this up in practice:

• In Gmail, turn on all the built in categories and filters, then add rules for your top clients and projects
• In Outlook, use rules and focused inbox, then layer AI suggestions on top
• In tools like Superhuman or Shortwave, lean on their AI powered triage that groups related messages and pulls tasks to the top

AI is not magic here. It simply learns patterns in your behaviour. When you repeatedly open and respond to certain messages quickly, the AI learns that these are important.
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2. Summarise long threads and newsletters

Long threads are a productivity trap. You tell yourself you will just skim them. Ten minutes later, you are still reading.

AI can summarise:

• Long email chains into key decisions and action items
• Newsletters into bullet point takeaways
• Updates from team members into simple status lines

You can do this in a few ways:

• Use the AI button in tools like Gmail with Gemini or Outlook with Copilot to summarise the current thread
• Forward emails to a dedicated AI address or Zap that sends the content to GPT or Claude, then emails you back a summary
• Copy and paste the text into ChatGPT or Claude and ask for a one paragraph summary and list of actions

With practice, this turns a thirty message thread into three lines:

• Decision made
• Owner responsible
• Deadline agreed

You keep the context if you need it later, but you stop drowning in quoted replies.
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3. Draft replies in seconds, not minutes

You do not need AI to write your emails. You do want it to help with the blank page problem.

Use AI to:

• Draft polite responses from a short prompt
• Rephrase messages to match your tone of voice
• Shorten long drafts without losing key points
• Translate emails into other languages if needed

A simple workflow:

1. Open the email you need to respond to
2. Ask your AI tool:
3. “Write a clear, friendly reply that accepts the offer, asks for the contract, and suggests next Tuesday afternoon for a call”
4. Paste the draft into your email client
5. Edit names, dates and any sensitive details
6. Hit send

Over time, you can build a few standard prompts that match your tone. For example:

• “Reply as a friendly but direct project lead. Keep it under 150 words. Avoid jargon. Make the next step very clear.”
• “Rewrite this in a warmer tone while staying professional. Keep the structure, just improve the language.”

The goal is not to sound like a robot. The goal is to reduce the time between understanding what you need to say and getting a polished version ready to send.
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4. Turn emails into tasks and notes automatically

One of the biggest risks with email is hidden work.

Someone asks for something in passing. You fully intend to handle it. Then the message disappears into the archive and the task goes with it.
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AI can help by:

• Detecting action items in emails
• Creating tasks in tools like Asana, Trello, Notion or Todoist
• Adding due dates or priority tags based on the email content
• Logging key information into your CRM

For example, you might:

• Use a Zapier workflow that triggers when you star or label an email
• Pass the email through GPT to extract task name, due date and owner
• Create a task in your chosen project tool with a link back to the email

You can refine the prompts over time. For instance:

“From this email, extract all tasks that require my action. For each task, give a short title, deadline if one is mentioned, and whether it relates to sales, operations or personal admin.”

This turns your inbox from a dumping ground into a structured feed of work items.
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Using AI for data entry and document processing

If you ever copy numbers from one place to another, AI data entry automation can save hours every month and reduce errors.
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1. Extract data from documents and PDFs

Think about common documents in your world:

• Invoices and receipts
• Purchase orders
• Contracts
• Application forms
• Survey responses

Instead of entering this information manually, you can:

1. Feed the document into an AI powered extractor
2. Tell it what fields you want filled
3. Have it export the results into a spreadsheet, database or accounting tool

Some tools do this out of the box for specific document types. Others give you a general interface where you define the fields, for example:

• “Vendor name”
• “Total amount”
• “Invoice date”
• “Due date”

For a simple approach without specialist software:

• Use a PDF to text conversion
• Copy that text into GPT or Claude
• Ask:
• “Extract all invoices from this text into a table with columns: vendor, total, date and due date. Use ISO date format.”

For more advanced, repeatable workflows, document AI tools from cloud providers can handle large volumes once configured.
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2. Automate spreadsheet work

Many people spend half their week inside Excel or Google Sheets. AI can reduce the manual strain by:

• Writing formulas from plain English
• Cleaning and standardising data
• Filling in missing values where appropriate
• Generating text based on row data

Practical examples:

You want to split full names into first and last names

• Prompt: “Write a formula for Google Sheets that splits names in column A into first names in column B and last names in column C.”

You have inconsistent date formats

• Prompt: “Look at this column of dates and give me a formula that converts them all into day, month, year format.”

You need short product descriptions based on a list of features

• Prompt: “For each row, write a one sentence product description using the name in column A and the benefits in column B. Friendly and clear style. Maximum 25 words.”

You can use sidebars or add ons to keep AI inside the spreadsheet, or you can copy and paste between your sheet and a chat window.

The main gains here are speed and fewer mistakes. You spend less time hunting for the right formula and more time thinking about what the data means.
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3. Clean and enrich data

Dirty data creates confusion and bad decisions. AI can act as a quick cleaning crew.

You can ask an AI:

• “Standardise the country names in this list.”
• “Find and merge likely duplicate records based on name and email.”
• “Flag any entries that look invalid, for example telephone numbers with the wrong number of digits.”

You can also enrich data by pulling in extra information. For instance:

• Use AI to guess industry based on company name and website
• Summarise notes into a consistent format
• Categorise open text responses into themes

A sensible approach is:

1. Ask the AI to create a plan for cleaning the data
2. Apply it to a small sample
3. Check the results carefully
4. Only then roll it out to the full dataset

AI does not replace good data management. It just accelerates the boring parts.
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Using AI for scheduling and calendar management

Meetings are necessary. Endless coordination to arrange them is not.

AI scheduling tools aim to protect your time and reduce the friction of booking and rearranging meetings.
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1. Protect focus time

Deep work requires long, uninterrupted blocks of time. Many calendars are full of half hour meetings scattered throughout the day, which makes focus almost impossible.

AI scheduling assistants like Reclaim or Clockwise connect to your calendar and:

• Detect your existing meetings and working hours
• Reserve focus blocks according to rules you set
• Move flexible meetings to preserve those focus blocks

You might tell the tool:

• “I need at least two hours of focus every morning.”
• “Do not book recurring catch ups on Friday afternoon.”
• “Keep one day per week with no meetings whenever possible.”

The AI then rearranges less important meetings to create more continuous time for serious work.

You still have final control, but you stop manually dragging events around and hoping for the best.
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2. Schedule tasks, not just meetings

Calendars are often full of meetings and empty for individual work, even though individual work is where most value is created.

AI can treat tasks as first class citizens and place them on your calendar.

Example workflow:

1. Your tasks live in a tool like Asana, Todoist, ClickUp or Notion
2. A scheduling assistant syncs with that list
3. You set rules such as:
   • “Marketing tasks are low priority and can move.”
   • “Client work is high priority and should be scheduled as early as possible.”
4. The AI schedules blocks of time for each task across your week

When meetings move, the assistant reshuffles flexible tasks automatically.

Instead of a vague to do list, you have a realistic timetable for your work.
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3. Book meetings without email ping-pong

If you have ever written “Does Tuesday at 3pm work for you?” then waited two days for a reply, you have experienced the classic scheduling dance.

AI presents a few options:

• Booking links: Tools like Calendly or Motion let people pick a time from a page that only shows your real availability. AI can adjust which slots to offer based on preferences you set.
• Email based assistants: Some services can join the email thread and do the negotiation for you. You write: “I am copying in my assistant who can find a time for us.”
• The AI then replies with options, checks other calendars and sends the invite.‍
• Chat based scheduling: Inside Slack or Teams, you can ask a bot: “Find a 45 minute slot for the product team next week.”
• It checks calendars and returns options or books the meeting directly.

In all cases, the goal is simple. No more manual checking across calendars and time zones. The AI handles the combinatorics for you.
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4. Reschedule gracefully

Life happens. People get sick, priorities change, urgent work appears.

Rescheduling is often worse than scheduling in the first place. You have to preserve the relationships while shuffling things around.

AI can:

• Suggest alternative times that disturb the fewest other events
• Draft polite rescheduling messages
• Update conference links and calendar descriptions automatically

A typical prompt might be:

“I need to reschedule this meeting for next week. Suggest three alternative slots that avoid my existing focus blocks, then write a short, honest message explaining that a deadline has moved and I would like to find a better time.”

The assistant proposes options, you pick one and send the message.

You remain in control of the tone and decision, while AI does the tedious coordination.

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Comparing GPT, Claude, Gemini and Perplexity for everyday workflows

You now have a sense of where AI fits into daily work. The next question is which AI model or assistant you should use for which tasks.

Here is a practical, breakdown of four popular options.
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GPT (ChatGPT)

Think of GPT as the general purpose assistant that can handle almost anything reasonably well.

Good for:

• Writing and editing long form content
• Drafting and improving emails
• Explaining code and writing small to medium scripts
• Summarising documents and meetings
• Brainstorming and ideation

Why people like it:

• The interface is simple and familiar
• It adapts to your tone of voice with a few instructions
• It handles mixed tasks in one conversation
• It is integrated into many tools through the OpenAI API

If you want one primary AI companion for most day to day workflows, GPT is usually a safe starting point.
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Claude

Claude feels like the thoughtful colleague who reads everything properly.

Good for:

• Analysing very long documents
• Summarising books, legal contracts and transcripts
• Handling big codebases where you need to paste many files
• Editing and rewriting text in a natural, human style

Why people like it:

• It deals well with long context
• It writes with a soft but confident voice
• It is careful with sensitive topics

If you often work with large chunks of text or complex projects, Claude is a great companion for deep research and editing.
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Gemini

Gemini is Google’s new model that lives inside the tools many people already use daily.

Good for:

• Working inside Gmail, Google Docs and Google Slides
• Summarising emails directly in your inbox
• Drafting content with live access to web search
• Handling tasks that mix text and images

Why people like it:

• It is built into Google Workspace, so there is no need to switch apps
• It can use live information from the web
• It can see the context of your document or email

If you live in Gmail and Google Docs, Gemini is strong for workflow optimisation because it turns your existing tools into smart assistants.
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Perplexity

Perplexity is closer to a next generation search engine than a chat partner.

Good for:

• Research and fact finding
• Getting concise answers with citations
• Checking whether something an AI told you is actually true
• Exploring new topics quickly

Why people like it:

• It always shows sources
• It is fast and to the point
• It can follow up on its own answers with deeper queries

If you are doing research for a project, a report or content, Perplexity is useful for gathering information before you use another model to help with writing and synthesis.
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How to design your personal AI workflow stack

You do not need to pick a single AI and stay loyal. In practice, the most effective setup usually looks like this:

• One primary assistant for thinking and writing
• One or two specialist tools inside your email, calendar or project management systems
• One research assistant for fact checking and up to date information

A simple stack might be:

• GPT or Claude as your main day to day chat assistant
• Gemini for Gmail and Google Docs tasks
• Perplexity for research
• One scheduling assistant and one automation platform such as Zapier or Make

When you design your own stack, ask:

1. Where am I wasting the most time every week
2. Which AI tools plug directly into that part of my work
3. Which model feels most natural for me to talk to

Lean on ease of use. The best tool is the one you will actually adopt.
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A step by step plan to optimise your day to day workflows with AI

Theory is nice. Real change happens when you pick somewhere to start.

Here is a simple plan:
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Step 1: Pick one workflow to improve this week

Choose something that annoys you regularly, for example:

• Clearing your inbox each morning
• Updating a weekly report
• Scheduling recurring team meetings

Make it specific. “Email” is too broad. “First pass triage of new messages each day” is clearer.
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Step 2: Map out the current steps

Write down the current sequence you follow. For example, for email triage:

1. Open inbox
2. Scan for anything from boss or key clients
3. Click into each one, decide whether it needs action
4. Star or label emails that need a reply
5. Delete or archive the rest
6. Start writing replies from scratch

Be honest about where you hesitate, switch context or procrastinate.
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Step 3: Identify where AI can help

Look for parts of the workflow that involve:

• Repeated decisions based on obvious patterns
• Rewriting similar content each time
• Copying information between places
• Checking for clashes or gaps in time

In the email example, AI can:

• Sort and label messages
• Summarise long threads
• Draft first version replies
• Extract tasks into your project tool
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Step 4: Choose a specific tool and experiment

Pick one AI tool that fits the workflow. Then run a time boxed experiment.

For instance:

• Turn on Gemini in Gmail and commit to using its summary and draft features for a week
• Connect Reclaim to your calendar and let it schedule your personal tasks
• Use Zapier with GPT to summarise any email you label as “summary needed”

Do not worry about designing the perfect system on day one. Aim for a simple experiment you can run this week.
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Step 5: Review and refine

At the end of the week, ask:

• What felt significantly easier or faster
• Where did the AI get in the way
• What should I change or try next

Then either:

• Scale up that experiment to more of your work
• Or try a different approach if it did not help

If you repeat this loop each month, you will steadily build an AI augmented workflow that feels natural.
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Common mistakes to avoid when using AI for workflow optimisation

Mistake 1: Handing over judgement

AI can suggest priorities, message wording and schedules. It should not decide your values.

Use AI to show you options and drafts. You still choose what matters most, what tone is appropriate and which meetings matter.
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Mistake 2: Ignoring privacy and security

Always check:

• What data your AI tools store
• Whether they use your data to train public models
• How they handle sensitive information

For client data, legal documents or health information, choose tools that offer strong guarantees and, ideally, business agreements.

If in doubt, keep the most sensitive material out of third party systems or work with anonymised versions.

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Mistake 3: Overcomplicating everything

It is tempting to build elaborate automations, multi-step Zaps and complex prompt libraries.

Start small:

• One AI tool
• One workflow
• One clear success metric, such as “reduce time spent on weekly report by 50 percent”

You can always add complexity later once you see real gains.
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Mistake 4: Failing to train your AI on your style

Most tools allow some kind of custom instruction or memory. Use it.

Tell your AI:

• Who you are and what you do
• How formal or informal you want to sound
• Which types of clients you serve
• What you never want it to do, such as making up data or promising timelines on your behalf

This tiny bit of setup makes responses more consistent and reduces editing time.
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FAQs: Using AI to optimise everyday workflows

Is AI really worth it for day to day tasks, or is it just a gimmick?

When you first try AI, it can feel like a novelty. The real value appears when you attach it to routine workflows.

If you save ten minutes a day on email, fifteen minutes on data entry and fifteen minutes on scheduling, that is more than two hours a week. Over a year, that is a full working week recovered, without any dramatic change.

The key is to focus on repetitive tasks, not rare ones. AI is most effective where the patterns are clear and the volume is high.
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Will AI make my writing sound robotic?

It can, if you paste outputs directly without editing or guidance.

To keep things human:

• Set clear tone instructions in your tool
• Share examples of your own writing and ask the AI to mirror them
• Always review and tweak drafts, especially the opening and closing sentences

Think of AI as a junior writer with perfect grammar but no sense of your identity. Your job is to give it direction and apply the final touches.
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Which AI model should I start with: GPT, Claude, Gemini or Perplexity?

For most people:

• Start with GPT or Claude as your main assistant for writing, summarising and thinking
• Use Gemini if you are heavily invested in Google Workspace
• Add Perplexity when you need reliable, up to date research with sources

You are not locked in. Try each for a few hours of real work and see which feels most natural. Different personalities prefer different assistants.
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How do I keep sensitive information safe when using AI?

A few practical steps:

• Prefer business or enterprise plans that clearly state your data is not used to train public models
• Do not  paste confidential client details unless you are sure the tool meets your compliance needs
• When in doubt, anonymise data by removing names, addresses and identifiers
• For extremely sensitive content, consider running open source models on your own infrastructure, or work with providers that offer private deployment

Good AI use respects privacy as a non-negotiable principle.
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Can AI fully automate my scheduling and inbox, or will I always need to review things?

In theory, you could hand over everything. In practice, you probably do not want to.

A balanced approach:

• Let AI handle first draft work: triaging, summarising, drafting replies, suggesting meeting times
• You then scan and approve
• Only in low risk situations, like internal meeting scheduling, might you allow full automation with minimal review

You want a future where you make fewer small decisions, not a future where you are out of the loop.
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Do I need to know how to code to use AI for workflow automation?

No.

Many tools provide point and click interfaces:

• Email clients with built in AI buttons
• Calendar assistants that connect with a simple authorisation
• No code platforms like Zapier and Make that use plain English descriptions of workflows

If you can describe a process you follow, you can usually build a simple flow without code. Coding skills simply expand what is possible, they are not required to start.
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How do I stop AI experiments from turning into another source of distraction?

Treat AI experiments like any other project.

• Set a clear outcome: “Reduce time spent on Monday reporting by 50 percent.”
• Limit the experiment: “Use AI for this task for two weeks and then review.”
• Avoid jumping between tools every day. Pick one stack and give it time.
• Do a short retrospective and either commit or move on.

The goal is not to chase every new feature. The goal is to make your days feel calmer and more focused.
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What should I do if my organisation blocks certain AI tools?

This is common, especially in regulated industries.

Possible options:

• Check whether there is a corporate approved AI tool. Many companies roll out their own chat assistant based on approved models
• Use vendor tools that embed AI inside existing systems. For example, your CRM or help desk might offer AI features that are already cleared
• Focus on workflows that do not touch sensitive data. For instance, using AI for generic writing, learning or planning is often less restricted than using it on customer data

Always respect company policies. The long term trend is clear. Organisations are moving from blanket bans to controlled, secure AI use. Being honest and proactive usually leads to better options than trying to bypass controls.