20 Tasks eCommerce Founders Should Delegate to AI

Every hour you spend on product blurbs, tracking returns, or fixing your PDP layout manually is an hour NOT spent growing your revenue.

You may think, “I’ll do it faster myself.” But what if AI could do it *faster, smarter, and at scale*?

In this guide, we break down 12 eCommerce tasks that you should stop doing manually — and hand over to AI.

How to Know Which eCommerce Tasks AI Can Actually Handle?

Before handing a task over to AI, ask yourself:

- Is it something I do (or my team does) daily or weekly? (emails, updating product listings, etc.)

- Is it data-heavy, or does the type of data vary in terms of formats and lengths? (analyzing reviews, taxes, return claims)

- Can it be set to follow a particular pattern, or is independent thinking required? (helps you choose between AI agents or AI workflows)

Above all, would you pay someone else to do it?

Here are the tasks, we’ve seen most eCommerce founders pick:

A. Product & Storefront Tasks

1. Write product descriptions at scale

2. Update product listings (titles, images, background cleanup)

3. Brainstorm product ideas, generate mockups

4. Conduct competitor research

5. Pricing optimization through A/B Testing

6. Identify bundling & cross-selling opportunities

7. Generate category & landing pages

B. eCommerce Marketing Tasks

8. Pick & Research Trends

9. Generate ad creatives, captions, copy

10. Create podcasts, product demo scripts, avatars

11. Monitoring competitors & the market at large

12. Map complex customer journeys

13. Repurpose content across platforms

C. eCommerce Operations & Strategy Tasks

14. Write legal + policy docs (returns, privacy, shipping)

15. Handle taxes, returns, and finance ops

16. Manage internal comms + task flows

17. Translate complex technical tasks for devs/agencies

18. Forecast demand and automate pricing

19. Optimize the supply chain

20. Handle complex customer inquiries

Remember: Nearly 78% of all organizations use AI in at least one function, according to McKinsey.

Types Of AIs To Use: Agentic AI vs. Generative AI vs. Workflow AI?

Generative AI (GenAI): Creates content (text, images, code) based on prompts

Examples: ChatGPT, Claude, Grok, Midjourney

Agentic AI: Takes multi-step actions on your behalf with minimal intervention

Examples: AutoGPT, Agentive AI, Manus, DoNotPay

Workflow AI: Executes actions on Gen AI and Agentic AI, based on a pre-set workflow 

Examples: Zapier, n8n, Make, Pipedream

But you just need two things to start delegating tasks to AI:

– An Open AI API subscription (starts from about $8) – this will help you cover most image, video, and text-based tasks (can also act like an agentic AI) 

– n8n/Make – use any one to create workflows, so that you can route tasks and results to respective APIs (so the AI can process the task by pre-set tasks/independently make decisions)

12 eCommerce Tasks You Must Delegate to AI — By Category

A. Product & Storefront Tasks

1. Write product descriptions at scale

Do you usually try to trim down a full three-pager manual into a product description? Well, no more. 

Most Gen AIs in 2025 know what product descriptions look like on eCommerce websites. So, all you need to do is feed your gen AI of choice: what your product solves, keywords, buyer personas, and USPs.

Once trained, you can set up workflow automation to pull product descriptions from URLs and reformat them in a sheet for you to review.

Run this periodically on: Weekly drops / new SKU batches / seasonal rotations

Tools to try: Chat GPT with Make/n8n and your CMS’s API (like Shopify API), Claude, Shopify Magic, Originality AI (for plagiarism detection)

Here’s a product description generator for Shopify AI workflow on Make, you can try your hands on.

2. Update product listings 

The biggest advantage AI gives you is: you can now match the visual aesthetics of the largest retail brands. That too, without hiring a full studio, crew, and models. 

Some tasks to try out with AI:

• Generate 360-degree shots when a particular product page gets a high bounce rate
• Refresh product backgrounds in bulk whenever you run new promotions 

For example, if you have a Father’s Day sale coming up, you can generate promo visuals from scratch using Canva’s AI: all you need is the product image and the offer.

Tools to try: Pixian, Canva AI, Smartly.io, Flair AI, Product Scope AI, Deepmotion, Dream Machine by Luma Labs

You’ll need: A workflow AI like N8N/Make to trigger refreshes when inventory updates or certain metrics fall below a certain benchmark

Here are two workflows on Make:

• Monitor products on Shopify with ChatGPT
• Enhance Shopify product photos with Picsart

Also read: 52 Ways eCommerce Businesses Can Use ChatGPT

3. Brainstorm product ideas, generate mockups

Estee Lauder’s R&D and marketing teams now get results in minutes instead of hours by just using Open AI’s models, helping them improve response time by over 90%.

But, you don’t need the full bells and whistles, just yet. Test if people want the thing first, without actually fully developing the product.

AI can now generate full-blown visual prototypes, landing pages, and value props. You just need to stack the right prompts with the right tools.

Here’s how you run it:

• Refine your initial product idea with Enzzo AI
• Use Midjourney, DALL·E, or Flair AI to mock up visual variations (colorways, packaging, materials)
• Ask ChatGPT to generate use cases and value props for 3 target personas
• Run UGC-style ads with AI visuals: “Would you pay $49 for this if it solved [insert pain point]?”
• Use IG polls and email waitlists to validate interest, or just use Midjourney mockups to hold Twitter polls and log data on Google Forms.
• Test which mockup + message hits hardest
• If there’s pull, use Sloyd to create 3D spins, unboxing views, and lifestyle renders on landing pages

Tools to try: Ideanote (research product ideas), Enzzo AI (refine product idea), Midjourney/DALL·E/Flair AI (full blown creative for product), Sloyd (3D render of product and 360 degree product shots)

You’ll also need to run tests on : Thumbnails, landing pages, copy, and CTAs

💡 Tip: 3D mockups work great for beauty, wellness, and home decor SKUs — faster than sampling, cheaper than photoshoots.

4. Conduct competitor research

Why check your competitor’s site manually when AI can Slack you the moment they change anything?

You can now track when competitors:

• Drop new SKUs
• Change pricing/bundling
• Have new banners or PDP headlines go up
• Run promos — and how long they run them

Tools to try: Hexowatch/Browse AI/SimilarWeb (monitor websites), Komo AI (use it to find competitors standard search engines don’t show)

Build with: Agentive AI + Webhooks, and then either keep track of data through Slack updates or build a full-blown Notion board.

5. Pricing optimization through A/B Testing

While delegating this eCommerce to AI is a great idea, you’ll have to ensure to keep a firm lookout on the following areas:

Sample size: Some AI tools can run tasks a little too fast, skimming over sample sizes, statistical significance thresholds, and factors like seasonality that can skew results. 

Segmentation: Price sensitivity differs across segments and varies by factors like demographics, purchase history, and geographic regions. It’s important to choose an AI that’s able to read these patterns effectively.

Competitor pricing changes: You may need to do this beyond the purview of AI, as most tools working with pricing still operate in isolation.

Brand perception: Check whether your AI tool is ending up being biased towards short-term conversion rates dramatically by bringing in frequent & aggressive price changes. 

Tools to consider: Prisync as it focuses on competitor data collection and tracking at its core; Competera because it has the capacity for AI-driven demand analysis over and above price optimization and Omnia because it also offers broader market analysis and research insights.

A key caveat: No matter which AI system, platform or tool you end up using, clean & real-time data is non-negotiable if you want significant & impactful results.

Further Reading: 153 A/B Testing Ideas for eCommerce (Homepage, PDP, Cart, Checkout)

6. Identify bundling & cross-selling opportunities

This is a super functional eCommerce task AI can handle, but only as long as you look into the more critical stuff. 

For one, you’ll need to ensure your products have rich meta tags — these can be around materials, ingredients use cases — so that AI has structured info to fall back on. 

Then there’s the need for you to dictate how far AI can go in terms of mixing & matching categories, bundling low margin & high margin products together etc. 

You’ll also need to feed the AI with what it can’t bundle — these typically would include what not to recommend together (for example, deals with premium lines) and styling rules (don't mix metallics and pastels).

Tools to try: Rebuy because it suggests smart bundles at key interaction points like product page, mini cart / cart page and post-purchase; LimeSpot learns from past browsing and purchase behavior to be able to create more visually appealing bundles and Nosto can deeply personalize, especially well for Shopify Plus brands.

UX fallback: If AI bundles aren't relevant, show popular combos or editorially-picked kits. This can bridge the conversion gap because AI can have problems detecting seasonality or even factors like correct campaign timing.

7. Generate category & landing pages

While this is a nifty task for eCommerce AI to handle, uniqueness could become a challenge because AI tools tend to generate lookalike pages. 

This is where you’ll need to bring in content control & evaluation through human editors. Let AI generate the ideas, but have humans personalize them into powerful copy. 

Apart from this, it’s also crucial to run a check on schema markups and meta descriptions as AI tools can potentially miss them or over-genericize them. 

Tools to consider: Writesonic can be a great AI writing tool, especially for brands that cater to audiences across many languages because it can generate copy in 25+ languages. To get your SEO bit sorted, Yext Pages could be a handy AI tool. It extracts structured data to then build SEO-optimized landing pages. Additionally, Content Harmony can read into search intent, identify relevant keywords and assess the structure of competitor content. 

Key to success: Train your AI system to read search queries more effectively — feed it historical data like user behavior patterns and existing search queries to make this happen.

Further Reading: Boost eCommerce landing page conversions: 18 scientific strategies

B. Marketing Tasks

8. Pick & Research Trends

Most AI trend tools now track what people are searching, laughing at, or struggling with, across platforms. Just prompt your AI with your niche and goal.

Ask: “What’s rising in [sleep wellness] that’s relatable to Gen Z women?”

Then: Get 3 angles, 2 hooks, and 1 product tie-in.

For example: Sleep gummies + #deluluszn = a playful ‘dream delusions’ campaign

Tools to try: Komo AI (social + search trend detection), Exploding Topics, Glimpse (micro-trends), Perplexity (deep dive research), Hypeauditor (to find relevant influencers), Manus (research agentive AI)

💡 Tip: Set up a Make/Zapier/n8n workflow to drop trend prompts in Slack every Monday. Here’s one from n8n to scrape competitor Instagram content, regularly, and another from Make for TikTok competitors.

9. Generate ad creatives, captions, and copy

Your product already has dozens of angles. You can delegate AI to pick up angles from the best-performing ads of your competitors and repurpose them according to your brand guidelines.

Or, you can use AI to end creative blocks and actually scale your campaigns – here’s how:

• CTR too low? Generate 10 new headline-image combos
• Launching a promo? Generate 20 creatives in one go
• UGC feeling stale? Auto-generate fresh formats that feel natural

You can also generate copy/image/video combos based on current promos, seasonal angles, or SKU performance.

Tools to try: Magic CX(ad intelligence), Pencil (predictive performance), AdCreative.ai (batch image creatives), CopyMonkey (Amazon-specific copy)

You’ll need: Meta’s Marketing API, + TikTok APIs for Business, + Google Sheets with n8n/Make/Zapier 

💡 Tip: Once creatives for your entire campaign are generated, run your creatives and your landing pages through ChatGPT. Ask it to run a check if you’ve ad-landing page fit, with ideas on how to move shoppers down a funnel.

10. Create podcasts, product demo scripts, and avatars

Scripting, voiceovers, and video editing for every product launch eat up tens of hours and dent your budget.

AI can also help with that: think tools like Descript, Synthesia, or ElevenLabs to spin up lifelike avatars and voices in minutes. That too, without sounding fake. 

You can now build: 

• Product walkthroughs in 60s with a full walkthrough of features, benefits, and outcomes
• Founder POV story (“Why we built this”) with AI-cloned voice & b-roll
• FAQ mini-episodes (“What happens if I cancel?” or “Does this work for kids?”)
• Give a voice to reviews and shoot hooks for your ads

Tools to try: Google Veo 3 (lifelike videos), Notebook LLM (for scripting), Descript (screen + voice editing), Synthesia (AI avatars), ElevenLabs (hyperreal voiceovers), RunwayML (video enhancement), CreatorKit/MakeUGC (to create UGC videos of your customers)

💡 Tip: Repurpose each script into reels, TikTok voiceovers, podcast intro hooks, and help center clips. Here’s a n8n workflow that lets you generate consistent characters for your product images and ads

11. Monitoring competitors & the market at large

The good news is that automated competitive intelligence is one of the best AI use cases in eCommerce. 

Since it is both data-heavy and time-intensive, AI in this department can help you keep an eye on competitor product launches, pricing changes and ongoing marketing campaigns. 

Make sure the AI tool / platform you use integrates both structured and unstructured data properly. While structured data tells you about quantifiable aspects like market share and pricing metrics, unstructured data points at customer sentiment, emerging trends overall and more niche-specific as well as brand perception. 

Tools to try: As far as instant and relevant competitive insights go, Crayon Answers is your go-to. It’s the first Gen AI tool that sales reps can use to gather information on competitors’ strengths and weaknesses. 

A social listening tool like Brand24 can come in handy as far as competitor strategies are concerned and what their customers are saying about their experience. You can also consider using market research integration tools like Brandwatch, Pecan and Speak if you want to use social listening & assess competitors’ marketing assets across audio & video. 

Include human interpretation: When you have to understand context, strategic responses and implications of competitors’ moves & actions. 

Further Reading: 15 Critical Steps In eCommerce Competitor Analysis

12. Map complex customer journeys

Since mapping customer journeys often turns out to be pattern-heavy, it’s an excellent AI use case in eCommerce. 

Take additional help from AI to identify hidden patterns when you’re attempting customer segmentation or mapping key touchpoints. 

Why this AI task delegation works is because with machine learning, you can tap into real-time customer behavior, which wouldn’t be possible through static manual maps.

Tools to consider: Journey AI as far as extracting customer journeys and mining them for feedback and behavior is concerned. MyMap AI, on the other hand, can help you create context-rich diagrams out of prompts, which later can be turned into even more precise journey maps. UXPressia is another tool that excels at customer mapping, and also offers heightened visual capabilities. 

A key caveat: Watch out for fragmented data, as sometimes AI tools don’t scour all channels equally well — missing out key touchpoints can lead to incomplete journey maps that won’t ultimately help you boost conversions.

Further Reading: The Founder's Guide to Customer Journey Map (eCommerce)

13. Repurpose content across platforms

While this is an excellent task to hand over to AI, it’s key to remember that repurposing content isn’t just about AI mimicking and creating new formats for platforms. 

It’s also to define the purpose and the tone for every channel — and this is something you’ll have to do right to get the right results.

For scalable repurposing, original content needs metadata: topic, emotion, goal, format. This lets AI map it more accurately to the right content type (e.g., “X is educational + evergreen → convert to Pinterest carousel”).

Tools to try: ContentBot can transform existing content into new forms without losing out on the tone factor. Opus Clip is an AI-powered tool that can effectively turn long videos into snackable formats for TikTok and Youtube. Descript can be a great tool for podcast-to-clip workflows, offering support across  transcription, editing, and voice cloning tasks. 

Build platform playbooks: This can be an effective guideline for your AI tools to work alongside you and adapt content to platforms systematically — these sets of rules can look like: Instagram: Visual-first + 3-line captions + CTA or LinkedIn: Personal story + takeaway + social proof.

C. Operations & Strategy Tasks

14. Write legal + policy docs (returns, privacy, shipping)

You don’t need a lawyer on retainer. You need docs that actually protect— and convert.

However, AI can spin up GDPR‑compliant privacy policies in 5 minutes—but here’s how to make sure you’re not inviting fines:

• Prompt: “Draft a privacy policy for a US/EU wellness brand, including cookie consent, data subject rights…”
• Validate: Run through Termly’s compliance checker
• Polish: Always get actual human to review against your existing T&Cs

Also, make sure you:

• Cover regions with separate policies (US, UK, EU, APAC)
• Cover unlikely scenarios: “What if the product is partially opened?”
• Sync your general terms and conditions, shipping, and privacy policies

Tools to try: DoNotPay (contracts, policies), Termly (region-specific compliance), Spellbook (legal prompt companion for founders)

💡Tip: Compare your policy vs competitors' policy scope using AI. If yours is more flexible, that’s a CTA-worthy USP.

15. Handle taxes, returns, and finance ops

Miss a tax filing? That’s a fine.

Mess up product returns? That’s a churned customer.

Let AI do the grunt work instead. Here are some tasks you can delegate to AI:

• Auto-categorize Shopify orders by SKU & channel (returns vs fullfills vs samples)
• Prep quarterly filings with AI-generated summaries + send to your CA
• Get AI to review the cause and proof for which the shopper initiates a return, and trigger return shipping labels (on Shipstation) and emails, once approved

Tools to try: Bench (human + AI bookkeeping), FlyFin (tax write-off scanner), Koinly (crypto + global tax reporting)
Stack with: GSheets for expense flags + Slack reminders via Zapier

💡 Tip: Create a Make/Zapier flow that tags high return rate SKUs → triggers ops review + auto-adjusts return window messaging.

16. Manage internal comms + task flows

Do you hold meetings that could have been emails? Well, AI can help with that. Be it summarizing vendor comparisons, or automating your full shipping tasks. 

And we don’t mean using robots, you can use AI to: 

– Shoot emails to respective stakeholders when an order/return is placed

– Auto assign followups based on subscriber and shopper engagement/review (basically track, “What’s blocked? What needs follow-up?”)

– Manage inventory for you, and generate reminders before you have think “did I have to order something"

‍Tools to try: Slack GPT (meeting recaps + promptable threads), Motion (auto-prioritizing schedules), ClickUp Brain (task auto-linking + context summaries)

💡 Tip: Assign urgency + risk rating to tasks via prompt (“What’s the risk of not doing this in 24 hours?”)

17. Translate complex developer tasks

Sure, you may have paid an agency to develop your store. But, who says you need to break out the bank, every time you wanna test a new feature?

After all, a “it’s just a small change” isn’t the same as “This will take two sprints and break three modules.”

Instead of you trying to figure it all out yourself, delegate AI to:

– Understand what your current components actually do (ExplainDev)

– Build lightweight, testable apps on subdomains using past code references (Replit + Cody AI)

– Build references that developers can actually understand (Framer’s great for this)

Tools to try: ExplainDev (reverse engineer tech), Cody AI (contextual coding agent), GitHub Copilot (autocomplete + cleanup)

💡 Tip: Use AI to test if an idea really needs dev time — or if it’s just a prompt + preview link away from being live.

18. Forecast demand and automate pricing

Instead of going through 100 competitor sites daily, you can have your own AI business intelligence task force.

With the right AI stack, you can predict when to restock (before customers hit “notify me”), adjust prices by promotions, current sales, and competitor price changes

Here are some AI task delegation ideas:

• Feed your current sales velocity and your promo calendar into Inventoro to predict how you should adjust prices over the next 30 days
• Set Blackcurve rules like: “If competitors go cheaper but we ship faster, hold price”
• Use Prisync to monitor top 3 rivals’ pricing in real time — and act before they do

Tools to try: Blackcurve (automated pricing engine), Inventoro (forecasting + reordering), Prisync (competitor-based price adjustments)

Make sure you layer in: Google Trends + Email engagement data + internal product sales velocity dashboards

Or you can use n8n as well, here’s a workflow for price scraping.

19. Optimize the supply chain

While this is a wonderful area to explore with AI’s help, it’s essential that you offer a data environment which is predictable and to an extent defined by human intervention. 

However, AI can really speed up work in this area across crucial aspects like recommending order volumes, setting reorder thresholds, optimizing warehouse allocation and suggesting bundle-based inventory moves. 

Tools to consider: ClearMetal can come in handy for sharp demand forecasting. LlamaSoft can help in simulating supply chain scenarios and look at planning automation as well as supplier selection. Cogsy is helpful for proactively telling you what to order, when to reorder, and how much cash to keep tied up in inventory.

Build an internal ops co-pilot: This can scan sales velocity daily while running inventory cross-checks in real-time. Use Notion along with GPT and API plugins to get this going.

20. Handle complex customer inquiries

As long as you make room for human escalation paths and feed your AI system with adequate context, this should be an easy delegation to achieve. 

Give your AI tool access to critical data including order data (status, history, delays), return/exchange rules, customer profile (VIP status, past issues, preferences) and shipping and SLA logic (regionally variable). 

Alongside, teach the AI your brand’s tone as well as contextual empathy so that it knows how to handle complex requests around order delays, discount codes not working etc.

Tools to try: Zendesk AI uses existing ticket history to train its bot and also suggests agent interventions when the query is too complex. Similarly, ChatGPT powered Tidio can work around FAQs, automatic order statuses and partial support escalation. 

Define customer support according to tiers:

Tier 1 (Handled by AI): Order status, refund timelines, exchange process

Tier 2 (Handled by AI with logic): Damaged item claims, wrong item received, discount application confusion

Tier 3 (Escalated): Aggressive customer, legal complaint, repeated issue

Common AI Delegation Pitfalls To Avoid

❌ Mistake #1: Giving AI Vague Inputs

"Write me a product description" will give you results that every other user gets.

✅ Fix: Feed structured context, the more details, the better, but always include:

• Who is this for?
• What's the goal of this asset?
• What brand voice or tone should it mirror?
• What are the don’ts (exaggerations, words you never use, etc.)?

For example, if you want an awesome studio shot, here’s a prompt to try:

Subject + Action + Product
{Describe who/what, what they will do in the image, the key aesthetic of the product, how it’s being held}

Camera Angle, Point of View, lens, Flash or No Flash, Crop

{high-angle, top down view, 85mm prime, wide view, crop around the body}

Lighting, Color Grade, Backdrop

{fluorescent light, neon coloring/pantone, plush red backdrop}

‍Resolution, Realism, Photographic Style 

{2K, hyper realistic, fashion magazine, film burn}

Skin texture, Makeup, Wardrobe, Atmosphere, Aspect ratio

{smooth skin, freckled cheeks, glossy red lips, minimal jewelry, light smoke, vertical, 9:16}

Here’s a prompt like this action, the first is from ChatGPT:

And another from Gemini:

❌ Mistake #2: Assuming AI can work on autopilot

AI doesn’t replace your brain — it removes grunt work.

✅ Fix: Build a QA + feedback loop

• Assign an owner for AI outputs (design, copy, data)
• Rate each output (pass/fail/needs tweak)
• Store top-performing prompts in a shared vault
• Set a cadence to revisit and improve automation flows

💡 Tip: Use ChatGPT to critique its own work before publishing, but in a different conversation. Ask: “Review this email for clarity, CTA strength, and relevance to [segment]”

❌ Mistake #3: Not Assigning Ownership

If “AI did it” is the answer, then who’s responsible when it flops?

✅ Fix: Treat AI as a contributor, not a decision-maker

• Every AI output still needs a human owner
• Even if it’s 80% accurate, that 20% can tank results
• Assign someone to vet, refine, and own outcomes

💡 Tip: Use ClickUp/Notion tags like: AI-generated ✅ | Reviewed ❌ | Owner: [name]. This way you actually have track of what's AI and not AI. 

People Also Ask

Can you automate eCommerce?

Yes — for storefront personalization, social media, and even backend operations. All you need are a few automation tools like n8n, Make, or Zapier – and some API keys from your gen AI of choice, social media platforms, and your store’s CMS.

Need ideas? Read: eCommerce Marketing Automation - 29 “Unique” Ideas For Busy Founders

How can AI be used in eCommerce?

Think of it like this: AI can write, design, predict, reply, and optimize (with the right prompt). 

So, whether you wanna know how fast you will run out of stock or what the right subject line is, AI can help you with almost everything. Except for original thought of course. That's all you. 

You have to know what you want, how you want it, and which way are you gonna express (or prompt it). 

Also read: 20 Ways eCommerce Brands Are Using AI (Real Examples)‍

What are the 5 applications of AI within an eCommerce business?

1. Customer Service – Chatbots, reply suggestions, live call summaries
2. Marketing – Ad copy, product images, email flows
3. Inventory Management – Demand forecasting, reorder logic
4. Pricing – Competitor-aware dynamic pricing
5. Product Development – Market validation, idea generation, 3D mockups

How does Amazon use AI in eCommerce?

• Search & recommendation engines (personalization at scale)
• Dynamic pricing updates in near real-time
• Forecasting demand based on user behavior
• Fraud detection in payments/logistics
• Even logistics pathing is AI-driven

How to use AI for online selling?

• Write better listings with SEO and persuasion dialled in
• Target smarter with auto audience segments based on behavior
• Automatically generate ad creatives based on competition and brand guidelines 
• Predict what SKUs are dying vs scaling