AI · 2.5 HOURS
Applying AI in Daily Work
Applying AI in Daily Work shows professionals who have tried an AI tool, but not yet kept using it, how to bring it into three pieces of work they already own. You finish with a weekly plan that sets out each task, its check and a review day, so the habit lasts beyond the course.
About this course
Many people who try an AI tool at work stop using it within a few weeks, usually because the first task they chose was the wrong kind of work rather than because the tool was poor. Building a lasting habit means choosing recurring work you already own and can judge, and knowing what to ask the tool to do with it.
The course teaches three moves you can make with a tool, which are drafting, summarising, and preparing a decision, together with the check that belongs to each and the reasons some work should start without the tool at all. You finish with a signed weekly loop that places the tool inside three pieces of your own work, each with a day, a move, and a check, one deliberate exception, and a fixed review.
What you will take away
- You will be able to test a task against four criteria, which are that it repeats, you own it, you can judge the output, and its inputs are safe to share, before you build the tool into it.
- You will be able to write a draft request that names the reader, gives the facts, sets a limit on what must not be added, and states the shape of the answer.
- You will be able to check an AI summary sentence by sentence against the notes it came from, and catch a suggestion turned into a decision or an owner who was never named.
- You will be able to ask a tool to compare options against your own criteria, mark gaps as not stated, and leave the final choice with you.
- You will leave with a signed weekly loop covering three tasks you own, one piece of work that starts without the tool and why, and a weekly review.
Who this course is for
- Project coordinators and administrators who write the same status updates, meeting notes, and summaries every week and want the tool to take the first pass.
- Operations, finance, and sales support staff who have access to an AI tool at work, have tried it a few times, and have not yet made it part of how they work.
- Team leaders and office managers who compare quotes, options, and dates and want help seeing a decision clearly while keeping the choice themselves.
- Professionals in client services who want a clear, written view of which work belongs with the tool and which should stay with them.
What you will do
Each lesson teaches one part of the method, works through a realistic example, and ends with a check on a case you have not seen. The course closes with an assessment and then the piece of work you sign.
- 5lessons with a worked example and a check
- 7scenario questions in the course assessment
- Signedthe weekly loop, with a record anyone can verify
- 2.5 hoursat your own pace, with progress saved
- 01
Lesson
Pick the work
This lesson explains why the choice of first task decides whether the habit lasts, and sets out four criteria a good first task must meet. You mark each task from a finance analyst's week as a good first task or not a first task, testing every criterion rather than stopping at the first.
- Why the first task decides whether the habit holds
- Four criteria for a first task
- What picking the work is not
- The usual mistake
You mark 4 statements from a realistic case and receive an explanation for each one.
- 02
Lesson
Draft
This lesson teaches the four things a draft request needs, which are the reader, the facts, a limit on what must not be added, and the shape, so that you receive a draft to edit rather than rewrite. You repair a weak request and then choose the stronger of two requests.
- What drafting with a tool means
- The four things a draft request needs
- What drafting is not
- The usual mistake
You compare two versions of the same piece of work, choose the stronger one, and see the reasoning behind the answer.
- 03
Lesson
Summarise
This lesson shows the three ways an AI summary quietly changes its source, such as turning a suggestion into a decision or adding an owner nobody named. You mark each sentence of a summary of a supplier call as in the notes or not in the notes.
- What a good summary keeps
- How a summary changes its source
- The check: in the notes or not
- What summarising is not
You mark 3 statements from a realistic case and receive an explanation for each one.
- 04
Lesson
Decide
This lesson teaches you to ask a tool to set options against your own criteria, write 'not stated' where the evidence is silent, and refrain from recommending, so the decision stays with you. You edit a request comparing suppliers and then choose the request that keeps the decision with the manager.
- Preparing a decision, not making it
- The request that keeps the choice with you
- Why the tool should not break the tie
- The usual mistake
You compare two versions of the same piece of work, choose the stronger one, and see the reasoning behind the answer.
- 05
Lesson
When not to start with the tool
This lesson sets out four reasons some work should start without the tool, including personal data, judgements about people, and work that needs your own first thinking. You mark each piece of work in a realistic list as start with the tool or start without it.
- Where work should begin
- Four reasons to start without the tool
- What this lesson is not
- The usual mistake
You mark 4 statements from a realistic case and receive an explanation for each one.
- 06
Course assessment
Course assessment
This lesson recaps the choice of work, the three moves, and where work should start, then takes one rota email through the whole method. You answer seven scenario questions set in situations you have not seen before, and you need six correct answers to pass.
- Choosing the work
- The three moves
- Where work starts, and how the habit holds
You judge 7 new workplace situations, with feedback on every option, and need 6 correct to pass.
- 07
Final work and signed record
A weekly loop
This lesson explains why a habit needs a fixed place in the week and how to write a check that names something you can actually see in the output. You write your own weekly loop with three tasks, one exception, and a review, and sign it for your record.
- Why a habit needs a place in the week
- The three parts of each task
- The exception and the review
- The usual mistakes
You write the weekly loop for your own work, part by part, and sign it as your record.
GOOD WORK.THE WEEKLY LOOP, SIGNED.
WHAT CHANGES
What the course changes for you and your organisation.
- 01
A habit that outlasts the course
Because the loop fixes each task to a day, a move, and a check, the tool becomes part of ordinary weekly work rather than an occasional experiment. The weekly review gives you a set moment to notice when a task has slipped and to adjust it.
- 02
Time saved on work you can judge
The course directs the tool towards recurring work where you already know what a good version looks like, so its output can be checked in minutes. Time saved on work you can judge stays saved, because errors are caught before they reach a colleague or client.
- 03
Decisions and judgements stay yours
You learn to use the tool to lay out options and gaps without letting it choose, and to keep judgements about people and sensitive material off the tool. Managers can see from the loop exactly where the tool is used and where it deliberately is not.
- 04
From trial to steady habit
DSIT research published in 2026 found that 56% of UK businesses using AI report higher employee productivity since adopting it. That benefit depends on staff using the tool regularly on real work, with a check on each task, rather than trying it once and stopping.
ROLES THIS SKILL SHOWS UP IN
Roles where these skills are already valued and paid for.
These figures are published salary bands and wage premiums, not a guarantee that finishing this course moves you to the top of the range. They are here so you can see what the market is already paying for the work you will practise.
AI Prompt Engineer
£62,750 to £115,000, midpoint £92,500
Robert Half's 2026 UK guide. London midpoint is £125,750.
Artificial Intelligence Engineer
Midpoint £65,750
The neighbouring engineering role in the same Robert Half guide, for people who take the brief into a built system.
Machine Learning Engineer
Midpoint £75,000
Same guide. The brief you write here is the instruction that role then tests.
AI enablement or operations lead
Premium on the role you already hold
PwC found specialist AI skills carried a 34.2% wage premium in 2025. Many of those postings sit inside operations, customer, and people teams rather than a lab.
Customer communications or account work
The same seat, with a skill the posting now names
The course artefact is a prompt card a colleague can run. That is the work those teams are hiring people to supervise.
Learning, knowledge, or product operations
Listed against the AI-skilled premium
These roles now ask for someone who can brief a model, check the output, and leave a reusable instruction. That is the check this course marks.
QUESTIONS
Questions about Applying AI in Daily Work
- What is Applying AI in Daily Work about?
- Many people who try an AI tool at work stop using it within a few weeks, usually because the first task they chose was the wrong kind of work rather than because the tool was poor. Building a lasting habit means choosing recurring work you already own and can judge, and knowing what to ask the tool to do with it. The course teaches three moves you can make with a tool, which are drafting, summarising, and preparing a decision, together with the check that belongs to each and the reasons some work should start without the tool at all. You finish with a signed weekly loop that places the tool inside three pieces of your own work, each with a day, a move, and a check, one deliberate exception, and a fixed review.
- Who is Applying AI in Daily Work for?
- Project coordinators and administrators who write the same status updates, meeting notes, and summaries every week and want the tool to take the first pass. Operations, finance, and sales support staff who have access to an AI tool at work, have tried it a few times, and have not yet made it part of how they work. Team leaders and office managers who compare quotes, options, and dates and want help seeing a decision clearly while keeping the choice themselves. Professionals in client services who want a clear, written view of which work belongs with the tool and which should stay with them. No specialist background is assumed, and every term is explained before it is used.
- What will I be able to do after Applying AI in Daily Work?
- You will be able to test a task against four criteria, which are that it repeats, you own it, you can judge the output, and its inputs are safe to share, before you build the tool into it. You will be able to write a draft request that names the reader, gives the facts, sets a limit on what must not be added, and states the shape of the answer. You will be able to check an AI summary sentence by sentence against the notes it came from, and catch a suggestion turned into a decision or an owner who was never named. You will be able to ask a tool to compare options against your own criteria, mark gaps as not stated, and leave the final choice with you. You will leave with a signed weekly loop covering three tasks you own, one piece of work that starts without the tool and why, and a weekly review.
- How long does the course take, and how is it taught?
- The course takes about 2.5 hours and is studied online at your own pace. It has 5 lessons, each with a worked example, a practice exercise, and a check on a new case, followed by a course assessment of 7 scenario questions in which you need 6 correct to pass. Your progress is saved to your account.
- Do I get a certificate?
- Yes. When you pass, you sign a record that names you, the course, and the weekly loop. Anyone you share it with can verify it online and download it as a PDF. The record confirms what you completed and does not claim compliance with any regulation.
- How much does it cost, and when can I start?
- The course costs £99, paid once by card through Stripe. Access begins as soon as payment is confirmed, and you can save a sign-in to return to the course from any device.
- Can my organisation train a whole team?
- Yes. Individuals can buy any self-paced course online, and organisations can book trainer-led courses for teams, in person or online, through the Experrt Academy.
More ai courses are listed on the self-paced ai courses for professionals page.
THERE IS A NEXT CHAPTER.
Start today, and finish with
the weekly loop your organisation can use.
Checkout takes an email address and a card, and access begins as soon as payment is confirmed. When you finish, you sign a record that names you and the weekly loop, which anyone you choose can verify online. The record confirms what you completed and does not claim compliance with any regulation.