Vanessa Wainwright

A Different Definition of Evidence

Wainwright's first experience of recruitment was not recruitment as most of the industry practises it. It was training and recruitment together, a model in which candidates spent a week developing their human skills before anyone went near a shortlist. The output was not a stack of CVs. It was a considered, evidenced recommendation: we have spent a week with these people, they are amazing, this is how they scored, you should interview them.

That experience set the standard she has held ever since. Traditional recruiting, as she describes it, evaluates people's experience and tries to match work history to job title, a process that works well for the already advantaged and badly for everyone else. "There's so much rich talent out there that's underrepresented," she says. So she kept pushing the method further, bringing in personality assessments, building role play scenarios, looking for any mechanism that would let a candidate demonstrate capability rather than simply describe it.

The philosophy underneath is straightforward and she states it plainly: it should not come down to the words on paper about what someone has done in the past, because we are all so much more than that. Human potential, in her framing, is not a soft idea to put in a values deck. It is the actual product of the work. Uncapping it is the job.

Three People Who Shaped the Thesis

Asked to name the people who have influenced her, Wainwright chooses three, and each one maps neatly onto a different part of how she thinks.

The first is Rosaleen, who founded Alexander Mann, a fellow Irish female entrepreneur whom Wainwright calls phenomenal for the way she took a recruitment business and scaled and grew it. The lesson there is one of ambition and execution: that a staffing idea, run properly, can become an institution.

The second is John O'Halloran, President of University College Cork, whom she describes as a genuine innovator in early talent. His preoccupation is the one Wainwright shares: making sure the skills being handed to the next generation actually meet the needs of industry, rather than arriving a decade late.

The third is Ursula von der Leyen, President of the European Commission, whose vision in establishing the European Union of Skills Wainwright regards as prescient. Von der Leyen, she argues, saw early that democratising access to jobs and learning would require a far sharper focus on skills, because skills are the common language between people, opportunity and education. Taken together, the three influences describe a career-long argument: build at scale, build for the next generation, and build on a currency everyone can actually read.

The Application Flood and the AI Reflex

On the state of the market, Wainwright is precise rather than alarmist. Recruiters, she notes, are now dealing with a 5 to 10x growth in candidate applications, driven by redundancies, a measure of panic, and the simple fact that it has never been easier to click apply. Candidates have gone mass market out of necessity, and the people absorbing that wave are recruiters who now have to work extraordinarily hard just to process what arrives.

The instinctive response is to point AI at the pile, and that, she cautions, is usually the first place AI gets injected into the process. It is also where the risk concentrates. The models hallucinate. They get things wrong. And they carry bias forward, because they were trained on data that had bias built into it in the first place. The consequence is the one she cares about most: "you miss the diamond in the rough, you miss the real potential people in that pipeline," precisely because a pressured team has handed shortlisting decisions to a system that was never designed to spot potential.

She is equally clear-eyed about the pressure on the people making these calls. Heads of talent acquisition, she observes, are being pushed to deploy AI and agents partly to tick a box, to be able to say the technology is in place, while simultaneously being told not to hire more recruiters and instead to maximise the output of an already stressed workforce. That combination, box-ticking above and burnout below, is not a technology problem. It is a leadership one.

From Jobs to Tasks

The deeper flaw, in Wainwright's analysis, is not that AI is being used but what it is being pointed at. Algorithms running over CVs are still hunting for experience, education and keyword job titles, which means the industry has automated the very approach she set out to replace at the start of her career. Faster bias is still bias.

The correction she argues for is skills, and she frames it as a shift already under way rather than a forecast. As the world of work moves away from jobs and toward tasks, the essential question changes: what are the skills required for the task, and who actually has them? Get that right and the matching problem becomes solvable at scale. Get it wrong and organisations will keep hiring the same profiles from the same places while insisting they have modernised.

It is a fitting place for her thinking to land. The recruiter who once spent a week with candidates so she could tell an employer what they were truly capable of is now making the same case in the language of infrastructure, taxonomies and market design. The scale has changed. The argument has not.