1. Flourish takes a non-traditional approach to recruitment. What inspired you to challenge the norms around experience and qualifications, especially in STEM fields?
Challenging conventional recruitment norms, particularly around experience and qualifications in STEM fields, was born out of my immense frustration with the structural inefficiencies. Time and again, I saw exceptional individuals sidelined because they didn’t conform to an outdated, narrow definition of what “qualified” looks like.
I wanted to create a space where we focus on real potential, not just CVs. It’s about identifying people who have the drive, resilience, and ability to succeed; however, they’ve not been given the chance. For me, it’s also deeply important that we support these individuals holistically, not just through technical training, but with coaching, mentoring, and wellbeing support so they can truly grow and thrive in high-performance environments.
2. You’re focused on getting more women into STEM. What are the biggest systemic barriers you’ve observed, and how is Flourish helping to break them down?
One of the most significant systemic barriers I’ve observed in getting more women into STEM is the deeply embedded bias. From an early age, girls are steered away from STEM subjects. This is compounded by a lack of visible role models, limited access to relevant opportunities, and outdated recruitment practices that favour linear, degree-based career paths over diverse, skills-based ones.
The result is a “one-size-fits-men” model of hiring and workplace design, one that doesn’t reflect the reality of women’s lives or the breadth of their capabilities. For instance, many women are deterred from pursuing tech roles simply because they don’t have a STEM degree, despite possessing all the necessary aptitude. At the same time, workplace environments often lack the inclusive infrastructure needed to retain and support women long-term.
3. How do you convince employers to take a chance on candidates who don’t tick the traditional boxes but have real potential?
Convincing employers to take a chance on candidates who don’t fit the traditional mould starts with shifting the narrative around what they require. Instead of “Does this person tick every box on paper?” we encourage them to ask, “Does this person have the mindset, capability, and drive to grow in this role and add long-term value to the business?”
We use skills-based assessments, behavioural insights, and structured profiling to provide a clear, evidence-backed picture of a candidate’s strengths, beyond what a CV can show. This gives hiring managers the confidence to make informed decisions, even if the candidate doesn’t tick every traditional box.
We also take time to understand what each employer truly needs, not just in terms of technical requirements, but in terms of team culture, values, and long-term goals. Then, we match them with candidates who align on those deeper levels.
4. We’re seeing AI being used in everything from CV screening to avatar-led interviews. What are the pros and cons of this technology in recruitment today?
AI improves efficiency by narrowing down candidate pools, reducing time-to-hire and costs, especially during large-scale recruitment campaigns. Tools such as coding assessments, vocal and body-language analysis, and customisable pre-employment tests allow employers to evaluate job-specific competencies and behavioural traits at scale. AI can also improve objectivity by standardising the process and removing demographic information, which helps reduce the unconscious bias that often influences human decision-making. Another major advancement is in predictive analytics. AI systems can forecast a candidate’s future performance and likelihood of retention, helping employers make smarter long-term hiring decisions.
When technology replaces too much of the human interaction, such as during avatar-led interviews or automated assessments, it can erode trust and disengage applicants. People want to feel seen, heard, and respected, especially in high-stakes career decisions. There are also serious ethical and technical risks. If AI tools are not trained on diverse and representative datasets, they can replicate or even worsen existing biases. AI should not replace gut instinct, empathy, or emotional intelligence.
5. You’ve mentioned trends around AI use in UK hiring. Can you share what you’re seeing and where things might be headed in the next 12–24 months?
There has been a shift in focus away from academic credentials and toward proven capabilities using AI-driven skills testing. Particularly in tech and digital roles, real-time coding assessments and scenario-based testing will become standard practice. Stricter guidelines are on the horizon, which will enable AI systems to justify hiring recommendations.
6. What are the risks of bias in AI-powered recruitment systems, and how can companies ensure their tools remain inclusive and ED&I-compliant?
Companies must audit and validate AI systems regularly, ensuring they are trained on diverse and representative datasets. Businesses should embed human oversight at key stages of the recruitment process to ensure candidates are treated with fairness and empathy. It’s not just about technical accuracy; it’s about candidate trust, experience, and dignity.
When implemented responsibly, AI can reduce bias, for example, by anonymising demographic data, but it must be continuously monitored to avoid unintentionally introducing new disparities.
7. How do you personally define ‘potential’ when evaluating a candidate, and how should businesses shift their mindset when hiring for skills in STEM?
I often find that candidates with the most ‘potential’ are those who’ve had to problem-solve their way into new environments, who show grit and emotional intelligence, and who are actively seeking growth, even if they don’t have the “right” academic background.
In STEM, especially, where technology moves faster than any degree syllabus can keep up with, we must stop equating talent with titles or qualifications. Businesses need to shift their mindset from hiring for pedigree to hiring for capability and mindset. That means diversifying questions, such as “Tell me about a time you taught yourself something new.”
8. What advice would you give to women looking to pivot into a STEM career, especially those without a formal background in tech or science?
What you do need is curiosity, commitment to learning, and the confidence to start where you are. Thanks to the rise of AI and digital learning platforms, there are more accessible entry points than ever before. Whether it’s short digital skills courses, online coding bootcamps, or employer-led training programmes, the pathways into tech are becoming increasingly skills-based, not credentials-based.
I also encourage women to seek out mentorship and community. Connecting with other women in tech can be incredibly empowering and can help you build both technical skills and confidence.
9. Looking ahead, how do you see the recruitment sector evolving and what role will Flourish play in shaping a more diverse and accessible future for UK tech?
Organisations will increasingly move away from degree-based filtering and start valuing potential, trainability, and mindset, especially in fast-moving sectors like tech. We’ll see AI-driven and skills-based hiring processes become mainstream, enabling companies to tap into wider and more diverse talent pools.
At the same time, candidate experience will become a key differentiator, with firms demonstrating ongoing care, development, and inclusivity will stand out.
