Sunday, October 25, 2026
Sunday, October 25, 2026
Lisa MacMillan:
Depending on who you ask, AI may transform civilisation – or end it.
Mary Shelley was exploring what happens when human invention outruns human judgement more than 200 years ago. From Frankenstein to Brave New World and The Matrix, we have been imagining the consequences of technology getting ahead of us for a very long time.
Today, predictions about AI range from existential catastrophe to extraordinary advances in productivity, medicine and human capability.
I’ll leave the fate of civilisation to people better qualified than me.
My question is something rather closer to home.
Before moving into executive search, I worked as a communications practitioner. I have since spent more than 20 years in executive search and talent advisory across Communications, Corporate Affairs and Marketing.
Experience matters. Track record matters. I make my living assessing both.
That experience keeps bringing me back to one question: what is the job becoming?
The answer is unlikely to lie in a job description written three years ago, the role performed by the person who has just left, or the same list of responsibilities with AI added somewhere near the bottom.
What capabilities will help this person adapt as the role changes over the next three to five years?
AI is already inside the work. It can research, summarise, monitor, translate, analyse information and produce a perfectly respectable first draft. The technology is moving faster than our debate about it.
AI is changing the job faster than recruitment is changing the way it identifies the person.
That question matters because the real story is what happens to a job when the machine can do some of it.
Recent research points in a consistent direction. AI is reshaping workplace skills, increasing demand for higher-order thinking and human capabilities alongside digital and AI literacy. Adaptability, resilience and human agency are becoming more valuable by the day.
The skills required in the most AI-exposed jobs are changing more than twice as fast as those in the least exposed. New tasks in those roles are also 2.5 times more likely to rely on capabilities such as empathy, judgement and creativity.
The most AI-exposed junior roles are seven times more likely than the least-exposed roles to require skills previously associated with senior positions.
The international picture varies widely, and that matters. Different countries, industries and organisations are moving at different speeds. Some employers are already putting greater weight on skills than formal qualifications, while predictions of large-scale job destruction remain far from settled.
Different markets bring different labour pressures and rates of adoption. The direction, however, is difficult to ignore: the skills mix is moving.
We have been here before, though not at this speed. When the internet entered the workplace, few employers predicted roles such as social media manager, digital communications lead, content strategist, online community manager, social listening analyst or influencer relations manager. Existing roles evolved, new ones appeared, and organisations sought people capable of learning as the work changed.
The issue is not simply which tasks AI can automate, but how it changes the shape and value of a job. Job loss may be quieter than the headlines suggest: a vacancy left unfilled, a smaller team, or one person expected to produce what once required several. An entire profession does not need to disappear for AI to alter how many people an organisation employs or what it expects from them.
That is why focusing only on what AI can do misses the recruitment question: how should those capabilities change the qualities we look for in people?
Throughout much of my career, one of the most reassuring questions in recruitment has been: has this person done it before?
Have they managed a global team? Led through a crisis? Worked in this sector? Advised a CEO? Managed transformation? Those questions still matter.
A different set is becoming equally important. How does this person think? How quickly do they learn? What do they do when there is no established playbook? Can they make a judgement when the information is incomplete? Can they influence somebody who disagrees with them? Can they understand context, culture and consequence?
Can they also recognise when a very convincing answer produced by a machine is actually the wrong one?
Critical thinking is becoming more important, not less. When AI can produce a convincing answer in seconds, people still need to question the evidence, test assumptions, notice what is missing and recognise when an answer is wrong. A growth mindset matters too. Carol Dweck’s work distinguishes between seeing ability as fixed and believing it can be developed. In recruitment, that means looking for evidence that somebody has learned from setbacks, responded to feedback, tried new approaches and built capabilities they did not begin with.
Recruitment still relies heavily on evidence from the past. Employers examine where somebody has worked, the roles they have held and what they have delivered, often comparing that history with a job description inherited from the previous postholder.
My own approach has always started with the person: how they think, what motivates them, how they build relationships and what they might be capable of next. Experience provides context, but it should not define somebody’s potential. That distinction becomes even more important when the job itself is changing.
Perhaps recruitment needs to become much better at assessing trajectory as well as history.
The question is what that experience tells us about somebody’s capacity to learn, adapt and operate in unfamiliar circumstances.
Seen this way, people whose careers depart from the traditional template deserve a different look: someone who has crossed sectors or markets, taken an unconventional route, returned after time away, or whose experience only partly mirrors the specification but whose judgement and ability to learn are exceptional.
The same shift exposes a weakness in recruitment systems focused on titles, formal qualifications and keywords: they can miss the less visible skills people actually use at work. Skills-first hiring is, at heart, about understanding what somebody can achieve rather than relying on familiar proxies.
AI is changing both sides of recruitment. Candidates can use it to sharpen CVs and tailor applications, while employers use technology to search and sort them at scale. Neither is inherently a problem, but polish and keyword fit are becoming weaker proxies for capability. Recruiters need to look beyond the finished output and understand how a person interrogates information, explains their reasoning, makes decisions and responds when there is no established answer.
The wider question is whether AI remains a tool that extends human potential or begins making consequential choices that people cannot understand or challenge. Recruitment makes that question immediate: are we using technology to understand people more fully, or allowing it to determine who deserves to be seen?
A CV has never been the whole picture. It records somebody’s career but rarely captures how they think, build trust, exercise judgement or respond when circumstances change. LinkedIn profiles and public activity on platforms such as TikTok and Instagram can influence an employer’s impression before they have even spoken with somebody. That does not necessarily produce better judgement. Digital visibility may reveal expertise, but it can also introduce bias, reward polished self-presentation and expose aspects of somebody’s private life that have no relevance to their ability to do the job. The person behind the evidence still matters most.
Experience still matters. The harder question is how we establish somebody’s capability. As it becomes easier to produce a polished account of a career, recruitment needs better ways to discover how a person thinks, learns, exercises judgement and responds to unfamiliar situations.
Companies need to start before the search.
Before replacing the person who has left, ask what the job is becoming. Which tasks will AI change? Which will remain? Which capabilities will become more important? What will help the person in this role adapt as the work changes?
Then recruit for that role rather than simply the one that existed yesterday. Assess capacity as well as history. Test judgement, adaptability, influence and curiosity alongside technical capability. Look beyond an exact title match when the evidence suggests somebody has the ability to grow into what the role will require.
Look at the whole talent system too. As roles change, learning, internal mobility and succession need to change with them. Give people exposure, mentoring, responsibility and opportunities to make decisions. Recruitment, development and succession should become connected conversations as the nature of work moves underneath all three.
Potential does not belong to one career stage. People starting out and those with decades of experience can both bring curiosity, adaptability and the capacity to grow.
Individuals face a similar challenge. Present your career as more than a chronology of previous jobs. Show what you learned, how you adapted, where you exercised judgement, what problems you solved and what you are capable of doing next.
Learn to use AI and understand what it does extraordinarily well. At the same time, keep building the qualities that may become more valuable because it exists: judgement, curiosity, relationships, influence, context, creativity, ethics and the confidence to challenge an answer that fails to make sense.
The future of work is still being written. That gives organisations an opportunity to look beyond familiar titles and conventional career paths, rethink how they identify capability and recognise potential that traditional recruitment may have missed.
We cannot know precisely what every job will become. We can become much better at finding and developing the people capable of helping to shape it.
[1] International Labour Organization, Changing landscape of skills in the age of AI, 13 August 2026. Source
[2] PwC, 2026 Global AI Jobs Barometer, 15 June 2026. Source
[3] Singapore Ministry of Manpower, Job Vacancies Report 2025, 20 March 2026. Source
[4] OECD, Artificial Intelligence and the Labour Market in Japan, 28 November 2025. Source
[5] The Atlantic, Rogé Karma, Three Ways to Think About AI and Jobs, 11 June 2026. Source
[6] Jobs and Skills Australia, As AI recruitment becomes the norm, Australia risks leaving real talent behind, 17 March 2026. Source
[7] World Economic Forum, What skills do employers want from young people entering the workforce in the age of AI?, updated 18 September 2026. Source
[8] Harvard Business Review IdeaCast, How AI Is Changing Talent, Not Just Tasks: Rethinking Where Human Judgment Matters Most, 17 September 2026. Source
[9] The Atlantic, Annie Lowrey, AI Has Ruined the Job Market, June 2026. Source
[10] The New York Times, Sarah Kessler, Employers Are Buried in A.I.-Generated Résumés, 21 June 2025. Source
[11] SHRM, 2025 Talent Trends. Source
[12] CIPD, Inclusive recruitment: Guide for employers. Source
[13] OECD, Skills in the AI Age, 8 July 2026. Source
[14] World Economic Forum, Future of Jobs Report 2025: Skills Outlook, 7 January 2025. Source
[15] Carol S. Dweck, Mindset: The New Psychology of Success, updated edition, 4 June 2026. Source
[16] Tim Clement-Jones, Living with the Algorithm: Servant or Master? AI Governance and Policy for the Future, March 2024. Source
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