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Updated weeklyAI in practice
Practical write-ups on using AI tools, automating work, and adopting international AI products — written for the people who have to make it work, not just evaluate it.
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Adopting US AI products on Korean terms
How to make US AI products work under Korean conditions — negotiating contract, billing, support and data terms.
How startups and large companies choose AI tools differently
How AI tool selection criteria change with organisation size, and why the same tool fits one and not the other.
Restarting AI adoption after it failed once
How to restart AI adoption in an organisation where it failed once — classifying the cause and designing the second attempt.
Why Indian AI products are undervalued in Korea — and what to check
The structural reasons Indian AI products are undervalued in Korea, and the items that genuinely need checking.
Designing an AI proof of concept to finish in four weeks
How to design an AI proof of concept that reaches a conclusion in four weeks, with weekly goals and stop conditions.
Twenty questions to ask an AI vendor
Twenty questions to ask an AI tool vendor before adopting, written so you can send them as-is and get written answers.
Finding shadow AI — locating unapproved AI use
How to find unapproved AI tool use and what order to respond in, and why providing alternatives beats prohibition.
Six ways to cut AI tool subscription costs
Practical ways to reduce AI tool subscription spend — from reclaiming seats to usage management and plan right-sizing.
Consolidating AI tools bought separately by each team
A procedure for finding and consolidating AI tools purchased team by team, from building the list through to migration.
AI tool migration checklist — what to confirm before moving
What to check and in what order when replacing one AI tool with another: data export, parallel running and cancellation.
Running a free trial properly — reaching a decision in two weeks
A procedure for not wasting an AI tool trial: what to measure and what to record so a decision actually emerges.
The first 90 days after adopting AI — what to measure and what to ignore
What to measure in the 90 days after adopting an AI tool, and what to ignore, split into 30, 60 and 90-day windows.
Foreign AI tools and Korean tax invoices — how billing actually works
How tax invoices and VAT work when paying for foreign AI tools, what to confirm before adopting, and the alternatives.
Contracting for foreign AI tools — what to check in the terms
What to check in the terms when contracting for a foreign AI tool, and how standard terms differ from an enterprise agreement.
"Korean support" — four different things called by one name
What Korean support in an AI tool actually means, split into four levels, and how to establish which level you are getting.
Manufacturing and logistics AI — where software meets hardware
What to check when bringing AI into manufacturing and logistics: the difference between software and equipment, and Korean certification requirements.
Choosing finance and accounting AI tools — local requirements come first
How to choose AI tools for finance and accounting, focused on Korean tax and accounting requirements and evidence handling.
Finding AI tools that store data in Korea — how to check, and the options
How to establish where an AI tool stores data, and what the options are when domestic storage is required.
Choosing customer support AI tools — the resolution rate trap
How to choose customer support AI tools: how to read automated resolution rates, and how to verify Korean response quality.
Choosing sales and CRM AI tools — inside the CRM or outside it
How to choose AI tools for sales and CRM: running AI inside your existing CRM versus attaching a separate tool.
Choosing contract and legal AI tools — assisting review is not replacing it
How to choose AI tools for contract review and legal work, focused on Korean contract handling, confidentiality and liability.
What to check before adopting healthcare AI — the regulatory path comes first
What to check when evaluating AI tools in healthcare, focused on the Korean approval pathway and medical data handling.
Choosing education AI tools — learner data is the criterion
How to choose AI tools for education and learning, focused on learner data handling, requirements for minors and Korean-speaker quality.
Choosing commerce AI tools — your platform decides first
How to choose AI tools for ecommerce: how your storefront platform limits the candidates, and what to check first.
Choosing productivity AI tools — start from what you already use
How to choose productivity AI tools for documents, meetings and work management, and why integration matters most.
Choosing video and audio AI tools — start with voice rights
How to choose video and voice generation AI tools, focused on voice and likeness rights, commercial use and Korean quality.
Choosing marketing AI tools — split by the job first
How to choose marketing AI tools across email, ads, content, SEO and video — plus the Korean regulatory items to check.
Choosing HR and recruiting AI tools — regulation before features
How to choose AI tools for HR and recruiting, centred on high-impact AI classification and applicant data handling.
Choosing design and image AI tools — start with the licence
How to choose design and image generation AI tools, focused on commercial use rights and brand consistency.
Choosing data and development AI tools — platforms through APIs
How to choose AI tools for data and development work: platform versus API, and what to check for Korean adoption.
The complete process automation guide — assess, design, build
Process automation in order: choosing the target, design, build and operation — and which work suits automation and which does not.
The complete AX transformation guide — from assessment to rollout
AI transformation in four stages: assessment, prioritisation, pilot and rollout — with the failure point and decision criteria at each stage.
The complete AI tool selection guide — what to decide on
Choosing AI tools across four axes: fit to the work, data terms, total cost and operability — including Korean adoption conditions.
The practical AI marketing guide — tools, workflow, measurement
Where to use AI in marketing work and where not to, plus how to measure whether it helped.
How specification quality changes what development costs
How the precision of a functional specification affects cost and schedule — what to detail, and what to leave to the vendor.
Korean SME AI support programmes — how to find them and how to be ready
Where to find Korean SME AI adoption support programmes and what to prepare in advance. Preparing after the call opens is usually too late.
Thirty free AI tools by function — and where free actually stops
Thirty AI tools with a free tier, organised by function, with the real limits of those free plans and when you have to move to paid.
ChatGPT, Claude and Gemini — choosing on the work, not the benchmark
Comparing the three general assistants by type of work and adoption conditions rather than model version.
Writing requirements a vendor can actually quote against
How to write a requirements document that produces accurate quotes — the six required sections and the omissions that distort pricing.
Writing an internal AI usage policy — a section-by-section guide
What an internal AI usage policy has to contain, organised into data classes, approved tools, prohibited actions and the incident process.
How to read a development quote — what to look at before the total
What to check when comparing development quotes: reading for what is included rather than comparing totals.
Build, buy or outsource — what to decide on
How to decide whether to build an AI capability, buy a tool, or outsource it — using three conditions rather than cost.
What is an AI agent — and how does it differ from a chatbot?
The real difference between AI agents and chatbots, what changes when you deploy one, and which work should not be handed over yet.
A practical guide to rolling out internal document search AI (RAG)
The practical order for deploying AI that answers from your own documents — document readiness, citations, permissions and the usual failure points.
Automating marketing reports — removing the manual work
The order for automating a recurring marketing report: separate collection, aggregation and interpretation, then decide how far to automate.
Seven patterns for replacing repetitive Excel work with AI
Seven patterns for handing monthly Excel work to AI — and which tasks a formula still does better.
The costs that are not on the AI tool price page
What actually makes up the total cost of an AI tool, and where the spend appears that the monthly subscription price does not show.
A security checklist for adopting AI tools in a company
The security items to settle before adopting an AI tool, across contract, data, access and operations — written as questions you can send to the vendor.
Does AI-written content get penalised in search?
Whether AI-written content is penalised in search, and what the actual standard is — separating the genuinely risky patterns from safe use.
Five ways to use AI in B2B lead generation
The five places AI actually produces results in B2B lead generation, and the places it should never touch — written for the Korean sales environment.
AI projects that stall at the pilot: the cause is the data
Why a successful AI pilot fails to spread, and the five things to build into the pilot design up front.
A 30-minute AI workflow for customer personas
A four-step workflow for building customer personas with AI — how to treat them as hypotheses, and how to validate them with interviews.
Automating the weekly report — template and prompt included
The structure and the actual prompt for automating weekly report writing, why the saving is larger here than on meeting notes, and a template you can use as-is.
How to use AI for Naver SEO properly
Naver SEO does not work like Google SEO. The differences we verified directly, and where AI should and should not be used.
Automating repetitive work: where to actually start
Four criteria for choosing an automation candidate, and the characteristics of work you should not pick as a first project. How to judge on difficulty relative to impact.
How we cut meeting-note writing time by 80%
How meeting-note automation was built in stages — the difference between using a summarisation tool and building a pipeline, and where it fails.
Six things companies that fail at AI have in common
The six recurring reasons AI adoption stalls at the pilot, and how to avoid each. These are problems of sequence and ownership, not of tooling.
How to calculate AI adoption ROI with numbers that hold up
How to calculate AI adoption ROI to a standard that survives a business case — hourly labour cost, automation-rate assumptions and break-even, with the actual formulas.
How to run an AX assessment without hiring consultants
A four-step procedure for running an AX assessment in-house before you get a consulting quote, with a clear line showing where external help actually starts to pay.
AI readiness: the twelve things worth checking first
Twelve checks to run before adopting AI, across four axes — work, data, technology and organisation. Scoring low is normal, and the lowest axis is your starting point.
Workflow automation tools compared — Workato vs n8n vs Make: scale decides the tool
Data and AI platforms compared — Databricks vs Snowflake: which one is your organisation?
Meeting AI compared — Fireflies vs Otter vs Fathom vs Notta
Fireflies, Otter, Fathom and Notta compared on Korean transcription, the teams they suit, how they charge, and what to check before adopting them in Korea. Decide whether you want a personal tool or a team knowledge base, then check seat structure and recording-data terms.
AI avatar video compared — a Synthesia vs HeyGen adoption guide
AI avatar video compared. Synthesia standardises multilingual training video; HeyGen is strong on translating and lip-sync dubbing existing footage. Strengths, weaknesses, pricing, Korean-language support and contracting checks, side by side.
AI voice and dubbing compared — ElevenLabs vs Murf vs Supertone
AI voice and dubbing compared. ElevenLabs leads on quality and language coverage, Murf on narration editing, and Korean company Supertone on Korean-language work and real-time voice conversion. Compare pricing, Korean support and commercial-use terms to decide what to test first.
Customer support AI compared — Zendesk AI vs Yellow.ai vs Kore.ai
Zendesk AI, Yellow.ai and Kore.ai compared on strengths, the teams they suit, pricing model and what to check before adopting them in Korea. Decide whether to layer AI onto your existing helpdesk or redesign the customer touchpoint itself, and understand the cost structure to expect.
Document and presentation AI compared — Notion AI or Gamma first?
Document and presentation AI compared. Notion AI makes scattered internal material something you can ask questions of; Gamma removes the time between having an idea and having a draft deck. Work out whether your bottleneck is organising knowledge or producing material, then set the order of adoption.
Marketing creative AI compared — AdCreative.ai vs Canva vs Freepik
Marketing creative AI compared. AdCreative.ai handles ad creative experimentation, Canva company-wide brand consistency, and Freepik the supply of raw material. Compare strengths, limits, Korean text handling, licensing and pricing to decide which to adopt first.
Sales AI compared — how to choose between Agentforce, Apollo.io and Zoho
Sales AI compared. Salesforce Agentforce automates conversations inside the CRM, Apollo.io finds new prospects, and Zoho covers low-cost integrated operations. Compare their very different pricing units and Korean-language support to pick the one that matches your sales bottleneck.
SEO content AI compared — Semrush vs Surfer vs NeuronWriter
Semrush, Surfer and NeuronWriter compared on strengths, the teams they suit, pricing model and what to check before adopting them in Korea. Decide whether to spend on a full SEO suite or an editor for individual articles, and how to handle Korean domestic search.
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