Business
10 Surprising Functions of ChatGPT You Never Considered
10 ways to use ChatGPT to boost your business, from boosting SEO to customer feedback analysis—unleash its full potential and save time.
Published
4 months agoon
By
AIinAsia
TL;DR: ChatGPT Business Productivity
- Unleash your ChatGPT business productivity on much more than just emails and social posts
- Use it for SEO strategies, customer feedback analysis, and contract reviews.
- Simplify workflows, create SOPs, and craft lead magnets with ease.
- Save time and money by finding funding opportunities and decoding complex data.
- Unlock its full potential to boost productivity and drive results for your business.
Let’s be honest. When most people think of ChatGPT, they picture it as a glorified chatbot that can churn out emails, draft a social post, or maybe help with brainstorming. But here’s the thing: ChatGPT is like an iceberg—most people are only scratching the surface. Beneath the obvious lies a treasure trove of tools and tricks that can turbocharge your business.
So, whether you’re looking to save time, work smarter, or just flex on your competitors, here are ten ways ChatGPT can help you take your business to the next level. Let’s unpack this now.
Unleshing Your ChatGPT Business Productivity
1. Speed Up Your Workflow with Custom Keyboard Shortcuts
Who doesn’t love a good shortcut? Imagine shaving seconds (or minutes!) off repetitive tasks in Photoshop, Excel, or any other software. ChatGPT can create a cheat sheet tailored to your workflow.
Let’s say you use Photoshop daily to adjust images, manage layers, and switch tools. Instead of fumbling around menus, ask ChatGPT to map out the best shortcuts for you. Now, your team won’t just work faster—they’ll feel like pros while doing it.
Why it’s a game-changer: Minutes saved every day = hours saved every month. Simple maths.
2. Turn Contract Confusion Into Clarity
Ah, contracts—those dense documents no one wants to read. But ignoring them can land you in hot water. While ChatGPT won’t replace a good lawyer, it can give your contracts a once-over to flag any red flags, like sneaky clauses on data privacy or liability.
For small businesses, this is a lifesaver. You can go into negotiations feeling more confident and less “wait, what does this mean?”
Quick hack: Paste a contract into ChatGPT with a prompt like the below—and voilà, instant insights.
“Highlight any clauses that mention data privacy or liability concerns.”
3. SEO Strategy, Sorted
If your website isn’t bringing in the traffic it should, it’s time to let ChatGPT play SEO consultant. It can help you identify high-impact keywords, write catchy meta descriptions, and even suggest a content calendar to keep your blog buzzing.
For example, let’s say you run an online store selling eco-friendly homeware. ChatGPT can generate keywords like “sustainable kitchen products” or “zero-waste living tips” to help you attract your dream customers.
Pro tip: Get ChatGPT to analyse your competitors’ websites to see what keywords they’re ranking for. Then, do it better.
4. Turn Rambles Into SOPs
Ever tried explaining a process to your team, only to get blank stares in return? ChatGPT can help you turn your spoken instructions into crystal-clear Standard Operating Procedures (SOPs).
Let’s say you record a Loom explaining how to onboard a new client. Upload the transcript to ChatGPT, and it’ll transform your ramblings into a step-by-step guide. Want tables? It can do that too.
Why this matters: Everyone’s on the same page, and training new hires gets a whole lot easier.
5. Find Free Money (Seriously!)
Let’s talk funding. Whether you’re a startup chasing grants or a small business looking for an accelerator programme, ChatGPT can help you find hidden opportunities.
Tell it your industry, location, and goals, and it’ll pull up grants, competitions, or funding schemes you didn’t even know existed. The best part? You can focus on applying instead of wasting hours Googling.
Best ChatGPT quote ever: “Money exists that could be yours.”
6. Make Sense of Customer Feedback
Every business loves customer feedback—until it comes time to analyse it. Instead of drowning in reviews and surveys, let ChatGPT do the heavy lifting.
Paste your feedback into ChatGPT, and it’ll highlight patterns, common complaints, and even what customers rave about. Suddenly, “data overwhelm” turns into actionable insights.
Why you’ll love this: Happy customers, better reviews, and smarter decisions. What’s not to love?
7. Write Job Descriptions That Actually Work
Hiring is hard. Standing out to top candidates? Even harder. But ChatGPT can help you craft job descriptions that feel less “corporate speak” and more “this could be your dream job.”
Let’s say you’re hiring a marketing manager. ChatGPT can tailor the description to highlight your company culture, exciting projects, and growth opportunities. The result? A post that attracts the right talent while sounding like you actually care.
8. Break Down Big Data
Got a massive sales report you’re too scared to open? ChatGPT is your new BFF. It can summarise key takeaways into simple bullet points or even visualise the data with pie charts and bar graphs.
Imagine walking into your next meeting with a sleek, digestible report that makes you look like you spent hours on it. (We won’t tell.)
9. Build Lead Magnets That People Actually Want
Lead magnets are marketing gold. The trick? Creating something your audience can’t resist. ChatGPT can brainstorm ideas for checklists, guides, or even mini-courses tailored to your customers’ pain points.
For example, if you’re targeting small business owners, ChatGPT might suggest a checklist on “5 Ways to Cut Marketing Costs Without Sacrificing Quality.” Who wouldn’t download that?
Pro tip: Ask ChatGPT to also generate a killer title and teaser copy to boost downloads.
10. Crack Spreadsheet Mysteries
Struggling with Excel formulas? ChatGPT can give you the answer—and explain it in plain English. Whether you’re calculating revenue, filtering duplicates, or running “if this, then that” scenarios, it’s got your back.
No more Googling and clicking through endless forum posts. Just a quick, clear solution.
Wrapping It All Up
ChatGPT isn’t just a productivity tool—it’s your secret weapon. Whether it’s saving time, simplifying tasks, or finding new opportunities, the potential is massive. And the best part? You don’t need to be a tech wizard to make it work for you.
What’s the most creative way you’ve used ChatGPT for your business? Or do you have a challenge you think it can’t solve? Share your experiences (or dares!) in the comments—let’s push the boundaries of what this tool can do!
And don’t forget to sign up for our regular newsletter and updates too! Let’s help build a brilliant AI community together!
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- Try the free version of ChatGPT by tapping here.
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Business
Build Your Own Agentic AI — No Coding Required
Want to build a smart AI agent without coding? Here’s how to use ChatGPT and no-code tools to create your own agentic AI — step by step.
Published
2 days agoon
May 9, 2025By
AIinAsia
TL;DR — What You Need to Know About Agentic AI
- Anyone can now build a powerful AI agent using ChatGPT — no technical skills needed.
- Tools like Custom GPTs and Make.com make it easy to create agents that do more than chat — they take action.
- The key is to start with a clear purpose, test it in real-world conditions, and expand as your needs grow.
Anyone Can Build One — And That Includes You
Not too long ago, building a truly capable AI agent felt like something only Silicon Valley engineers could pull off. But the landscape has changed. You don’t need a background in programming or data science anymore — you just need a clear idea of what you want your AI to do, and access to a few easy-to-use tools.
Whether you’re a startup founder looking to automate support, a marketer wanting to build a digital assistant, or simply someone curious about AI, creating your own agent is now well within reach.
What Does ‘Agentic’ Mean, Exactly?
Think of an agentic AI as something far more capable than a standard chatbot. It’s an AI that doesn’t just reply to questions — it can actually do things. That might mean sending emails, pulling information from the web, updating spreadsheets, or interacting with third-party tools and systems.
The difference lies in autonomy. A typical chatbot might respond with a script or FAQ-style answer. An agentic AI, on the other hand, understands the user’s intent, takes appropriate action, and adapts based on ongoing feedback and instructions. It behaves more like a digital team member than a digital toy.
Step 1: Define What You Want It to Do
Before you dive into building anything, it’s important to get crystal clear on what role your agent will play.
Ask yourself:
- Who is going to use this agent?
- What specific tasks should it be responsible for?
- Are there repetitive processes it can take off your plate?
For instance, if you run an online business, you might want an agent that handles frequently asked questions, helps users track their orders, and flags complex queries for human follow-up. If you’re in consulting, your agent could be designed to book meetings, answer basic service questions, or even pre-qualify leads.
Be practical. Focus on solving one or two real problems. You can always expand its capabilities later.
Step 2: Pick a No-Code Platform to Build On
Now comes the fun part: choosing the right platform. If you’re new to this, I recommend starting with OpenAI’s Custom GPTs — it’s the most accessible option and designed for non-coders.
Custom GPTs allow you to build your own version of ChatGPT by simply describing what you want it to do. No technical setup required. You’ll need a ChatGPT Plus or Team subscription to access this feature, but once inside, the process is remarkably straightforward.
If you’re aiming for more complex automation — such as integrating your agent with email systems, customer databases, or CRMs — you may want to explore other no-code platforms like Make.com (formerly Integromat), Dialogflow, or Bubble.io. These offer visual builders where you can map out flows, connect apps, and define logic — all without needing to write a single line of code.
Step 3: Use ChatGPT’s Custom GPT Builder
Let’s say you’ve opted for the Custom GPT route — here’s how to get started.
First, log in to your ChatGPT account and select “Explore GPTs” from the sidebar. Click on “Create,” and you’ll be prompted to describe your agent in natural language. That’s it — just describe what the agent should do, how it should behave, and what tone it should take. For example:
“You are a friendly and professional assistant for my online skincare shop. You help customers with questions about product ingredients, delivery options, and how to track their order status.”
Once you’ve set the description, you can go further by uploading reference materials such as product catalogues, FAQs, or policies. These will give your agent deeper knowledge to draw from. You can also choose to enable additional tools like web browsing or code interpretation, depending on your needs.
Then, test it. Interact with your agent just like a customer would. If it stumbles, refine your instructions. Think of it like coaching — the more clearly you guide it, the better the output becomes.
Step 4: Go Further with Visual Builders
If you’re looking to connect your agent to the outside world — such as pulling data from a spreadsheet, triggering a workflow in your CRM, or sending a Slack message — that’s where tools like Make.com come in.
These platforms allow you to visually design workflows by dragging and dropping different actions and services into a flowchart-style builder. You can set up scenarios like:
- A user asks the agent, “Where’s my order?”
- The agent extracts key info (e.g. email or order number)
- It looks up the order via an API or database
- It responds with the latest shipping status, all in real time
The experience feels a bit like setting up rules in Zapier, but with more control over logic and branching paths. These platforms open up serious possibilities without requiring a developer on your team.
Step 5: Train It, Test It, Then Launch
Once your agent is built, don’t stop there. Test it with real people — ideally your target users. Watch how they interact with it. Are there questions it can’t answer? Instructions it misinterprets? Fix those, and iterate as you go.
Training doesn’t mean coding — it just means improving the agent’s understanding and behaviour by updating your descriptions, feeding it more examples, or adjusting its structure in the visual builder.
Over time, your agent will become more capable, confident, and useful. Think of it as a digital intern that never sleeps — but needs a bit of initial training to perform well.
Why Build One?
The most obvious reason is time. An AI agent can handle repetitive questions, assist users around the clock, and reduce the strain on your support or operations team.
But there’s also the strategic edge. As more companies move towards automation and AI-led support, offering a smart, responsive agent isn’t just a nice-to-have — it’s quickly becoming an expectation.
And here’s the kicker: you don’t need a big team or budget to get started. You just need clarity, curiosity, and a bit of time to explore.
Where to Begin
If you’ve got a ChatGPT Plus account, start by building a Custom GPT. You’ll get an immediate sense of what’s possible. Then, if you need more, look at integrating Make.com or another builder that fits your workflow.
The world of agentic AI is no longer reserved for the technically gifted. It’s now open to creators, business owners, educators, and anyone else with a problem to solve and a bit of imagination.
What kind of AI agent would you build — and what would you have it do for you first? Let us know in the comments below!
You may also like:
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- Or tap here to try this out now at ChatGPT by tapping here.
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Business
Is AI Really Paying Off? CFOs Say ‘Not Yet’
CFOs are struggling with AI monetisation, with many failing to capture its financial value, essential for AI’s success in the boardroom.
Published
4 days agoon
May 8, 2025By
AIinAsia
TL;DR — What You Need to Know:
- AI monetisation is a priority: Despite AI’s transformative potential, 71% of CFOs say they’re still struggling to make money from it.
- Traditional pricing is outdated: 68% of tech firms find their legacy pricing models don’t work for AI-driven economies.
- Boardrooms are getting serious: AI monetisation is now a formal boardroom priority, but the tools to track usage and profitability remain limited.
Global Bean Counters are Struggling to Unlock AI Monetisation, and That’s a Huge Issue
AI is being hailed as the next big thing in business transformation, yet many companies are still struggling to capture its financial value.
A new global study of 614 CFOs conducted by DigitalRoute reveals that nearly three-quarters (71%) of these executives say they are struggling to monetise AI effectively, despite nearly 90% naming it a mission-critical priority for the next five years.
But here’s the kicker: only 29% of companies have a working AI monetisation model. The rest? They’re either experimenting or flying blind.
So, what’s the hold-up? Well, it’s clear: traditional pricing strategies just don’t fit the bill in an AI-driven economy. Over two-thirds (68%) of tech firms say their legacy pricing models are no longer applicable when it comes to AI. And even though AI has moved to the boardroom’s priority list — 64% of CFOs say it’s now a formal focus — many are still unable to track individual AI consumption, making accurate billing, forecasting, and margin analysis a serious challenge.
The concept of an AI “second digital gold rush” has been floating around, with experts like Ari Vanttinen, CMO at DigitalRoute, pointing out that companies are gambling with pricing and profitability without real-time metering and revenue management systems.
This is where the real opportunities lie. Vanttinen’s insight?
“Every prompt is now a revenue event.”
So, businesses that can meter AI consumption at the feature level and align their finance and product teams around shared data will unlock the margins the market expects.
Regional differences are also apparent in the study. Nordic countries are leading in AI implementation but are struggling with profitability. Meanwhile, France and the UK are showing stronger early commercial returns. The US, while leading in AI development, is more cautious when it comes to monetisation at the organisational level.
Here’s the key takeaway for CFOs: AI is a long-term play, but to scale successfully, businesses need to align their product, finance, and revenue teams around usage-based pricing, invest in new revenue management infrastructure, and begin tracking consumption at the feature level from day one.
The clock is ticking — CFOs need to stop treating AI as a cost line and start seeing it as a genuine profit engine.
So, what’s holding your company back from capturing AI’s full value?
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Business
Anthropic’s CEO Just Said the Quiet Part Out Loud — We Don’t Understand How AI Works
Anthropic’s CEO admits we don’t fully understand how AI works — and he wants to build an “MRI for AI” to change that. Here’s what it means for the future of artificial intelligence.
Published
5 days agoon
May 7, 2025By
AIinAsia
TL;DR — What You Need to Know
- Anthropic CEO Dario Amodei says AI’s decision-making is still largely a mystery — even to the people building it.
- His new goal? Create an “MRI for AI” to decode what’s going on inside these models.
- The admission marks a rare moment of transparency from a major AI lab about the risks of unchecked progress.
Does Anyone Really Know How AI Works?
It’s not often that the head of one of the most important AI companies on the planet openly admits… they don’t know how their technology works. But that’s exactly what Dario Amodei — CEO of Anthropic and former VP of research at OpenAI — just did in a candid and quietly explosive essay.
In it, Amodei lays out the truth: when an AI model makes decisions — say, summarising a financial report or answering a question — we genuinely don’t know why it picks one word over another, or how it decides which facts to include. It’s not that no one’s asking. It’s that no one has cracked it yet.
“This lack of understanding”, he writes, “is essentially unprecedented in the history of technology.”
Unprecedented and kind of terrifying.
To address it, Amodei has a plan: build a metaphorical “MRI machine” for AI. A way to see what’s happening inside the model as it makes decisions — and ideally, stop anything dangerous before it spirals out of control. Think of it as an AI brain scanner, minus the wires and with a lot more math.
Anthropic’s interest in this isn’t new. The company was born in rebellion — founded in 2021 after Amodei and his sister Daniela left OpenAI over concerns that safety was taking a backseat to profit. Since then, they’ve been championing a more responsible path forward, one that includes not just steering the development of AI but decoding its mysterious inner workings.
In fact, Anthropic recently ran an internal “red team” challenge — planting a fault in a model and asking others to uncover it. Some teams succeeded, and crucially, some did so using early interpretability tools. That might sound dry, but it’s the AI equivalent of a spy thriller: sabotage, detection, and decoding a black box.
Amodei is clearly betting that the race to smarter AI needs to be matched with a race to understand it — before it gets too far ahead of us. And with artificial general intelligence (AGI) looming on the horizon, this isn’t just a research challenge. It’s a moral one.
Because if powerful AI is going to help shape society, steer economies, and redefine the workplace, shouldn’t we at least understand the thing before we let it drive?
What happens when we unleash tools we barely understand into a world that’s not ready for them?
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