Your Job in the AI Era: Staying Relevant

Your Job in the AI Era: Staying Relevant
Personal Development/Career Development
English

Course Details

Artificial intelligence is changing how work gets done—and the impact is not limited to jobs that are directly related to technology.

AI can automate some tasks, accelerate others, and change what organisations expect from professionals. As tools become more capable, the value of simply producing more output can decrease. Judgement, problem framing, communication, domain understanding, accountability, and the ability to work effectively with AI can become more important.

This course examines what those changes mean for your work and your career.

Understand How AI Is Changing Professional Value and Adapt Your Approach

In this course, you will:

  • Understand how AI and automation are changing the way professional work is organised and evaluated

  • Identify the difference between tasks that can be accelerated or automated and work that depends more heavily on human judgement

  • Examine why using AI does not automatically make work better

  • Explore how decision-making, accountability, communication, and professional trust are changing

  • Learn why framing a problem can matter more than simply choosing a better tool

  • Identify professional capabilities that remain valuable as technologies and workflows evolve

  • Apply these ideas to your own role, regardless of industry or job title

What Is Changing About Work?

The important question is not simply whether AI will replace particular jobs.

Most jobs contain a mixture of tasks. Some can be automated or accelerated; others require context, judgement, collaboration, responsibility, or interaction with people. As this balance changes, the expectations attached to professional roles can change as well.

The course looks at these changes from the perspective of the individual professional: how work is performed, how contribution is evaluated, how decisions are made, and what makes someone's contribution difficult to reduce to automated output.

AI Is Not Always the Answer

Using AI can improve speed and productivity, but more output is not necessarily better work.

You will examine situations in which AI can be useful and situations in which relying on it too heavily can create problems. These include situations where the underlying problem has not been properly framed, where the quality of the output cannot be adequately assessed, or where responsibility for an important decision still belongs to a person.

The goal is not to avoid AI. It is to understand where AI creates leverage and where human judgement still matters.

From Tools to Thinking

Technology changes quickly. Professional capabilities often change more slowly.

This course therefore focuses less on particular AI tools and more on durable ways of working: framing problems, questioning assumptions, making decisions, communicating clearly, understanding context, evaluating information, and taking responsibility for outcomes.

These capabilities can remain useful even as individual tools, models, workflows, and job descriptions change.

Apply the Ideas to Your Own Role

The final part of the course brings the ideas together so that you can consider what they mean for your own work.

You will be encouraged to examine the tasks you perform, how much of your work depends on judgement and context, where AI could genuinely improve your workflow, and which capabilities you should continue to strengthen.

This is not a technical AI course, and it does not attempt to predict exactly which jobs will disappear.

Instead, it provides a framework for thinking more clearly about how work is changing, what professional value means in an AI-enabled workplace, and how you can respond deliberately rather than reactively.

By the end of the course, you should have a clearer understanding of how AI may affect your role and a more structured way to think about your professional development as technology continues to evolve.


Course Author

Alex Amoroso, PhD

Senior UX Researcher | Research, Product & Learning Design

Alex Amoroso is a researcher, educator, and course designer with more than 10 years of professional experience in UX and product research, behavioural research, and complex problem-solving, alongside extensive experience in professional and academic education.

Her work focuses on a simple question: what is actually going on, what evidence do we have, and what should we do with it?

Across research, product, and organisational environments, she has worked on complex problems involving user behaviour, digital products, analytics, customer experience, decision-making, and innovation. Her research has included studies with thousands of users across B2B and B2C environments, combining qualitative and quantitative methods to investigate problems, challenge assumptions, interpret evidence, and support better decisions.

Alongside her professional research work, Alex teaches doctoral-level research design and methodologies, supervises and assesses research projects, and has developed approximately 30 online courses across research, UX, product, data, analytics, customer experience, business, and decision-making. Selected courses are also available through Udemy Business.

Her approach to teaching is practical and structured: clarify the subject, organise the thinking, distinguish evidence from assumption, and turn complex information into knowledge that can be applied.

She holds a PhD in Health Anthropology, with research focused on human behaviour, environmental stress, and quantitative data analysis, and has published research in peer-reviewed journals.

Across her courses, she combines:

  • Research-based thinking

  • Practical frameworks and methods

  • Real-world examples and applications

  • Clear explanations of complex subjects

  • Exercises, tools, and techniques that support practical learning

Her goal is simple: to help learners understand complex subjects, think more clearly, and apply what they learn in real professional situations.