How AI changes work
AI & work

How AI changes the way we work

A four-step journey for two roles: decision-makers and operators. From understanding AI correctly, to reorganizing how work runs, choosing tools, then building skills.

CEO · decision-maker Operator
Step 01

Understand AI

Grasp the core concepts
Step 02

Organize the work

Rethink around data
Step 03

Tools

How to use & potential
Step 04

Skills

Build them per role
Step 01For both roles

Understand AI before you use it

Changing how you work starts with changing how you understand. The six concepts below are the foundation for talking about tools and skills without misunderstanding.

LLM

Large language model — an engine that predicts the next word from a huge body of text. The "brain" of nearly every AI tool today.

Human in the loop

People stay in the loop: reviewing, correcting and owning the final call. AI proposes, humans decide.

AI Agent

AI that does not just answer but carries out a chain of actions toward a goal: looking things up, calling tools, producing results.

Automation workflow

Steps wired together automatically — triggers and actions — so a process flows on its own, no manual clicking.

Agentic AI

Proactive, multi-step AI: it plans on its own, picks its own tools and adjusts based on each step’s result.

AI native

Designing work and the organization around AI from day one, instead of bolting AI onto an old process.

Keyword
LLMHuman in the loopAI AgentAutomation workflowAgentic AIAI native
Step 02Focus for CEOs

Reorganize how work runs

Decision-makers don’t use AI to speed up a few scattered tasks — they use it to rethink how the whole machine runs. And everything, in the end, revolves around data.

The core
DATA.

Data is what matters most. Whether AI is useful or useless largely comes down to the data you feed it and how you organize it. Changing how you work with AI is really changing how you work with data — same tools, the one with better data always wins.

AI takes daily load off decision-makers

  • Synthesize information across the organization into one clear picture.
  • Search internal information fast — ask, and the answer is there.
  • Organize the management machine: who does what, where work flows.
  • Calendar & priorities: reminders, scheduling, clearing the way to focus.
  • Make decisions based on data instead of gut feel.

Most of the value sits in internal data

MessagesVoice / recordingsImagesDocumentsEmailSpreadsheets

This is what only your organization has. The closer the data sits to real work, the closer AI’s output gets to reality.

01
Collect

Gather data from every source — conversations, files, images, systems — into one accessible place.

02
Analyze

Clean, label and extract meaning so AI understands it and can find it again when needed.

03
Use

Feed it into decisions, automation and outputs. Data only has value when it gets used.

Keyword
DATAInternal dataCollect → Analyze → Use
★ High priority CEO · decision-maker

CEOs also own competitive strategy

AI is redrawing competitive advantage across entire industries: whoever organizes their data and gets AI into the machine first pulls away from the rest. For decision-makers this is the most important part — and the easiest to overlook.

Competitive advantage with AI → loi_the_canh_tranh_ai.html
Step 03For both roles

Tools today, and their potential

Three groups of tools mapped to the job at hand — search, automation, and reporting — with how to use each and the potential ahead.

01 · Search toolsClaude · Gemini · multi-platform
Q&A, lookups and synthesis right in the chat window. Not locked to one place — works across platforms, and anyone can start.
Potential: plug into internal data to "ask and get answers" on your organization’s own knowledge.
02 · Automation toolsClaude Cowork
Hand over a whole multi-step piece of work for AI to do on its own — research, file processing, running tasks — instead of clicking through every step.
Potential: processes that flow on their own, with people reviewing only at the points that matter.
03 · Reporting & summary toolsClaude coding · needs design
Not an out-of-the-box button — reports and summaries need to be designed first, then built with Claude coding to fit your exact data and needs.
Potential: reports that update themselves, in the right format, re-runnable any time.
Keyword
Multi-platform searchCowork · automationClaude coding · reports
Step 04CEOOperator

Skills to build — role by role

Anyone can reach the tools. The difference is skill — and each role builds a different set.

CEO · decision-maker

Lead the technology

No need to code yourself, but you must understand enough to choose well and move first.
  1. Pick the right technology key member to lead the technical side for the organization.
  2. Or research the technology yourself — deeply enough to understand and decide without being led around.
  3. Coach the team’s AI thinking — spread the right way of thinking, not just which buttons to press.
  4. Experiment with and adopt new things fast; keep what works, drop what doesn’t.
Operator

Raise your own productivity

Use AI to work faster and better exactly where humans create the value.
  1. Apply automation to repetitive work to free up time.
  2. Build reports fast — synthesize, present and report tightly and correctly.
  3. Keep sharpening your core strengths — the part AI can’t replace.
In short

Four steps, two roles, one direction.

Understand AI→Organize the work→Tools→Skills