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Deterring age discrimination. Count those mature hires ‘in’!

To find out how to interpret bias in recruitment, we also have a great eBook on inclusive hiring.


Once upon a time we were all happily employed and worked in our jobs until we reached the age of 65. Then we retired with a gold watch and lived happily ever after. 

While that’s not quite the way it really happened, the reality is aging workers are faced with a very different story today. While the ability to ‘retire’ seems to move further out of reach, many people are faced with the challenges of needing to work longer.

And perhaps the greatest challenge to that need is age discrimination in hiring.

Ageism – a hiring challenge for our age

A 2020 report conducted by LinkedIn found that nearly half of the baby boomers engaged in their survey believed that their age was the main reason their job applications had been rejected by an employer. 

Earlier, a 2015 survey by the Australian Human Rights Commission found that 27 per cent of older people had recently experienced or witnessed age discrimination in the workplace, most often during the hiring process.

And when they say ‘older’ they’re referring to candidates aged over the age of 50.

When you think that many of those will need to work for a further 20 years, their classification as older workers seems discriminatory in itself.

While ‘ageism’ tends to be more of a problem for older workers – shouldn’t we be calling them more experienced workers? Age discrimination can also affect younger workers.  Employers might discriminate against younger job seekers, for example, because they believe they won’t be committed to the role or will move on to another job quickly.

Learned versus lived

Over the past 20-25 years, the number of post-graduates achieving master’s degrees has almost doubled.

But does a potentially over-qualified ‘green’ hire necessarily trump the experience that an older employee has gained through the university of life and years working in a role?

What ‘qualifications’ have they earned and learned that formal education could never provide?

What is age discrimination in hiring?

A textbook definition of age discrimination from the website of Shine Lawyers is “where a person is treated less favourably than another person of a different age in circumstances that are the same or not materially different. The person may be treated differently due to their actual age, or due to a characteristic that pertains or is imputed to pertain to persons of that age. Further, age discrimination can occur when an employer places conditions, requirements or practices that are not reasonable and have the effect of disadvantaging a person or persons of a certain age.”

While in Australia employment laws are in place to protect employees from all forms of discrimination at all stages of employment –  from recruitment through to redundancy or retirement – age discrimination can creep in at any time. It can happen when decisions are being made about:

  • who gets shortlisted for interviews
  • who gets selected for a role
  • what benefits, terms and conditions are offered with that role
  • who is offered training opportunities 
  • who is considered and chosen for promotion, transfer, retrenchment or dismissal.

There are four main types of age discrimination

1. Direct discrimination in hiring

Direct discrimination is when someone is treated differently or less favourably than another person in the same situation because of their age.

For example:

  • Someone reviewing CVs refuses to even consider any candidate over 45 years of age.
  • A hirer believes older workers are slower and resistant to or incapable of adapting to new technologies.
  • Someone is marked for redundancy because they are the oldest – or youngest – employee.
  • An employer decides an employee is too old to undertake skills training while other, younger employees complete the training.

2. Indirect discrimination in hiring

Indirect discrimination can be less obvious than direct discrimination. It describes the situation where an organisation has a particular policy, job requirements or way of working that would appear to apply to everyone but which puts a person or group of people at a disadvantage because of their age.

For example:

  • An employer has a policy that only people with postgraduate qualifications can be promoted. This could be seen to disadvantage young people who simply haven’t had the time to achieve post-grad qualifications. Or an older worker who didn’t go to university because ‘in those days’  it wasn’t commonplace to do so. 
  • A company requires all employees to meet a physical fitness test, even though that fitness standard is not relevant to the job. While the test might be easy for young people, it could be seen to disadvantage older employees.
  • An employer assumes that older people won’t fit in with the team due to their age

3. Harassment

This is when discrimination crosses a line to become dangerous – for those being discriminated against, of course, but also for the employer that risks potential criminal charges and reputational damage. Harassment happens when employers, managers or colleagues make people feel humiliated, offended or degraded.

For example:

  • An older employee having difficulty learning a new online time management system becomes the subject of ongoing ridicule in staff meetings. This could be held up as age discrimination.
  • An older worker is nicknamed Granny Joan.

4. Victimisation

A step up from harassment, victimisation is when individuals are treated poorly because they have made a formal complaint about age discrimination and the way they have been harassed, overlooked for promotion or otherwise discriminated against. Colleagues or co-workers who have also supported someone in their discrimination complaint may also be victimised by their managers or employers.

What the law says about age discrimination

In a range of global jurisdictions including the US, the EU, UK and in nations across Asia-Pacific such as New Zealand and Australia, discrimination laws are designed to protect all people from age discrimination in many areas of life – getting an education, accessing services, renting a property, accessing and using public facilities… and protecting people from discrimination at work.

The laws cover all sorts of employers and employees across private sector and government, charities and associations and all part-time, full time or casual workers and contractors.

Age discrimination in the workplace can be damaging and costly on so many levels. Here’s what employers need to know and do

Taking positive steps to address age discrimination can help organisations attract, motivate and retain good staff while building your reputation and brand as an equal opportunity employer.

Starting with legal obligations, there are a few key areas that employers and recruiters should address to minimise age discrimination:

  • Know the law and stick to it – Just as there are laws that cover discrimination around sex, race or disability, the Age Discrimination Act (the ADA) says that an employer must take ‘all reasonable steps’ to prevent discrimination from happening at work or in connection with a person’s employment. This is called ‘vicarious liability’. 
  • Develop an anti-age discrimination policy – While any organisation’s employment policy will be shaped by the relevant employment and discrimination laws, it’s essential that the ‘laws of the land’ are enshrined in your own policies and practices. Written policies make it clear for all stakeholders that discrimination and harassment– age-based or otherwise – will not be tolerated in your workplace. These policies should be made familiar to all employees, contractors, recruiters and partners. They may also be part of your employer brand and be explicitly stated in your recruitment advertising.
  • Cultivate diversity – The benefits of diversity in the workplace are well recognised in contemporary business. Having a workforce comprised of employees of different gender, cultural and ethnic backgrounds, experience and education have been shown to positively impact a wide range of business metrics from productivity to sales, innovation to employee satisfaction and tenure. Often overlooked in the assessment of diversity is the value that having employees of every age bring to the organisation.
  • Challenge and change attitudes – Like all forms of discrimination, ageism is often driven by inaccurate stereotyping, misperceptions, myths and unconscious bias. A number of studies have shown that developing intergenerational teams explodes preconceptions and the beliefs around ageing or the abilities of the young. The more younger and older people work together the more their perceptions of each other are moderated and negative attitudes are softened.

Making recruitment practices and process fair for all

Perhaps the most important place to tackle age discrimination head-on is where it potentially begins and ends – in the recruitment process.

Remove age discrimination from candidate screening 

The ultimate goal in overcoming discrimination in the workplace is to build a culture that thrives on diversity and a team that values the benefits diversity brings. 

Sapia helps organisations start where they intend to finish by removing the potential for a wide range of biases – including age discrimination – from top-of-funnel interview screening. 

Our Artificial Intelligence enabled chat interview platform offers blind screening at its best. It solves bias by screening and evaluating candidates with a simple open, transparent interview via an automated text conversation.  Candidates know text and trust text and questions can be tailored to suit the requirements of the role and the organisation’s brand values.

People are more than their CV and their age. Candidates tell us they appreciate the opportunity to tell their story in their own words, in their own time.  In fact, Sapia only conversational interview platform with 99% candidate satisfaction feedback.

Sapia offers blind screening at its best

Unlike other pre-employment assessments, Sapia has no video hookups, visual content or voice data. No CVs and no data extracted from social channels. All of which can be triggers for discrimination and bias – unconscious or otherwise.  

Sapia’s solution is designed to provide every candidate with a great experience that respects and recognises them as the individual they are. It won’t know (or care) whether a candidate is 18 or 58, male or female, tall or short, Asian or Caucasian. What it will know is whether a person is a right fit for your organisation.

Here’s an example of how Ai is a fairer judge, regardless of age

This case study graph demonstrates the effectiveness of Sapia’s platform in removing age bias from the candidate shortlisting process. While Sapia specifically excludes age data from the screening process, the data listed here was extracted from the client’s ATS after the hiring process was complete to check for any bias. This data comes from HIRED people, hence the high YES rate.

The left-hand column shows the number of applicants sorted by age groupings. In this sample, there are ±500 people over 50 – a group that often reports age discrimination.

The middle column shows the percentage of people in each group who were allocated a green for go ‘yes’ recommendation for the role, an amber ‘maybe’ or a red ‘no’.

The predictive model (and corresponding Sapia scores) reveals no age bias in the process  – with an equal percentage of candidates receiving a ‘yes’ recommendation in the over 60s as the under 20s. Without blind screening, and without the removal of age bias, the value and brilliance of the older candidates might otherwise have been easy to overlook or, at worse, wilfully disregarded or ignored.

 

Check your bias, Check your process

While Sapia offers one of the easiest ways to provide a level playing field for all candidates, it’s one part of your overall process that should be reviewed to check for built-in age discrimination and other biases as well. Some other important considerations:

  • review selection criteria – ensure your documented criteria for a role are consistent with the ‘essentials’ of the role, the qualifications and skills actually required, not based on stereotypes or arbitrary traits. Check you’re not making assumptions that it’s a young person’s role.
  • review job listings –  at a minimum, you need to be sure that job descriptions are compliant with employment and discrimination law. Advertising for a “25-30-year-old woman”, for instance, is discriminatory. Twice.
  • add diversity to your candidate sourcing – make a virtue of your inclusive and diverse hiring policies by explicitly mentioning them in your job ads. Consider where your recruitment ads are being seen. There may be better places to connect with candidates that will help support your organisation’s diversity goals.
  • check your hiring processes – review application forms, screening factors,  ATS filters, onboarding and workplace culture, to see that age discrimination (amongst others) isn’t unintentionally embedded in your processes and your collective workplace thinking.

Have you seen the Inclusive e-Book?

It offers a pathway to fairer hiring in 2021 so that you can get diversity and inclusion right while hiring on time and on budget.

In this Inclusivity e-Book, you’ll learn: 

  • How to design an inclusive recruitment path. From discovery to offer and validation of the process.
  • The hidden inclusion challenges that are holding your organisation back.
  • How to tell if Ai technology is ethical.

Download Inclusivity Hiring e-Book Here >

Find out how Sapia can help take age discrimination and other biases out of the equation in screening interviews. 


Blog

How leading retailers are using AI-Native Hiring

Retail leaders have embraced AI to improve supply chains, automate checkout, and enhance customer experience. But what about finding the people who deliver that customer experience?

AI brings incredible possibilities to supercharge how retailers hire, develop, and retain talent.

At Sapia.ai, we helped iconic retailers like Woolworths, Starbucks, Holland & Barrett, and David Jones reimagine hiring from the ground up – replacing resumes, ghosting, and gut feel with structured, ethical AI that delivers performance and fairness at scale.

The Retail Problem: Volume, Turnover, and Ghosting

Retail is high volume. It’s high churn. And it’s high stakes for candidate experience:

  • Candidates ghosted during slow hiring cycles
  • Store managers are overloaded with admin
  • Recruiters are overwhelmed with 100,000+ seasonal applicants
  • Talent is overlooked due to bias or unfair screening processes, not a lack of potential

And yet, most hiring still relies on broken tools: resumes, forms, manual processes, and outdated systems.

Sapia.ai: The AI-Native Hiring Engine Built for Retail

Our platform automates the entire “apply to decide” journey, leveraging AI & automation to streamline the hiring process & bring intelligence into retail hiring. 

Smart Interviewer™: Mobile-first, chat-based, structured interviews for a holistic candidate assessment. 

Live Interview™: AI-driven bulk interview scheduling without calendar chaos.

InterviewAssist™: Instant interview guide generation.

Discover Insights: Embedded analytics to track hiring health in real-time.

Phai: GenAI coach for career and leadership potential.

Unlike resume parsing or generic chatbots, Sapia.ai assesses soft skills, communication, and culture fit using natural language processing and validated psychometrics. It’s ethical AI built in, not bolted on. 

From Application to Interview in Under 24 Hours

Candidates don’t want to wait. They don’t want to be ghosted. And they don’t want resumes to define them.

> 80% of Sapia.ai chat interviews are completed in under 24 hours.

We see consistently high completion across categories: grocery, merchandising, home improvement, and luxury retail.

“It was fast, fair, and I actually got feedback. That never happens.” – Retail Candidate Feedback

Real Impact, Across Every Retail Category

Sapia.ai powers hiring for millions of candidates across diverse retail environments:

Impact of Sapia.ai on Retail Hiring in 2024
Category Hours Saved FTEs Saved  Cost Saved
Grocery 272k 131 $6.5m
General Merchandise 193k 93 $4.6m
Specialty Retail 133k 64 $3.2m
Home Improvements 103k 50 $2.5m
Merchandising 22k 11 $0.5m
Luxury 9k 4 $0.2m

The savings created by intelligent, AI-native automation have unlocked team capacity, impacted retailers’ P&L, and improved store readiness.

Speed That Delivers Real ROI

Every candidate gets interviewed instantly. No waiting. No bias. Just fast, fair, data-backed decisions. This generates real impact for retailers who previously relied on slow, outdated processes to handle thousands of applicants. 

  • Woolworths: 5,000 hours saved in a single week
  • Starbucks: Doubled hiring capacity, 91.8% completion
  • Holland & Barrett: Time to hire cut from 20 to 7 days
  • Woodie’s: 3x more ethnic minorities hired in 3 months

DEI by Design, Not by Mandate

With Sapia.ai:

  • 98% of candidates opt in to demographic questions
  • Zero adverse impact detected across gender, ethnicity, and disability
  • 1.5–3x improvements in diverse hiring rates

DEI Fairness Scores (based on actual hiring data):

Gender: 1.03 (vs customer baseline of 1.01)

Ethnicity: 1.15 (vs customer baseline of 0.74)

Why? Because ethical AI removes what humans can’t unlearn: bias. With a candidate experience that is inclusive by design, retailers can ensure fairness in screening, and measure it in hiring.  

Candidate Experience = Brand Experience

Retail candidates are your customers. And the experience you give them matters. We have built a brand advocacy engine that delights candidates and gives you the data to prove it. 

  • 9.2/10 CSAT across 2.6 M+ retail candidates
  • NPS: 78 (30+ points above industry benchmark)
  • 87% more likely to recommend the company’s products post-interview

Responsible, Explainable AI Built for Retail

Not all AI is created equally. Since 2018, Sapia.ai has been built on a foundation of responsible AI:

  • No use of resumes or scraped data
  • Hosted securely via AWS Bedrock
  • Claude-powered LLM scoring with model cards and explainability
  • Independent audits on bias, privacy, and methodology

“We can’t go back to life before Sapia.ai. We used to spend half the day reading resumes.”

— Talent Lead, Starbucks AU

What’s at Stake: Time, Brand, and Revenue

Every day spent using outdated hiring methods costs retailers:

  • Wasted recruiter hours
  • Lost revenue from unfilled roles
  • Bad churn that drains training budgets
  • Lower customer satisfaction from poor-fit hires.

With Sapia.ai, you get the productivity unlock retail hiring demands, and the intelligence your talent deserves.

Want to see how fast, fair, and human retail hiring can be?

 

Book a demo

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Blog

Reinventing the Competency Framework: A Data-Driven Approach for the AI Era

We can’t hide from reality anymore. Talent needs are shifting overnight, and AI is redefining what it means to work. Traditional talent frameworks are no longer fit for purpose. At Sapia.ai, we believe the future of talent strategy lies in a smarter, fairer, and more adaptive way of defining what great looks like. 

Our AI hiring platform is built on the largest proprietary dataset of interview answers globally – we’re a data company at heart, and we’ve seen the power of data-driven people methodology in transforming how organisations hire and retain good talent.  

So, when it came to building a new Competency Framework that could be leveraged globally for hiring for any role at any scale, of course, we used a ground-up, data-led methodology that bridges the gap between organisational psychology and AI.

Why Rethink Competency Frameworks?

Conventional frameworks are typically crafted through expert interviews and focus groups. While valuable, they tend to be subjective, static, and too slow to keep pace with evolving job demands. As roles become more fluid and technology augments or replaces task-based skills, organisations need a new way to understand the human capabilities that genuinely matter for performance.

We wanted to identify enduring, job-agnostic competencies that reflect what drives success in a modern workplace – capabilities like adaptability, resilience, learning agility, and customer orientation.

(Why competencies and not just skills? Read why here.)

Our Approach: Where AI Meets I/O Psychology

Sapia.ai’s methodology is rooted in the science of human behaviour but powered by cutting-edge AI. We asked two core questions:

  1. Can we make competency discovery agile, scalable, and evidence-based?
  2. Can we use AI to automate the process without losing the rigour of traditional psychology?

The answer to both: yes.

We began with a rich dataset of over 37,000 job descriptions across industries and role types. Using large language models (LLMs) and advanced NLP techniques, we extracted over 200,000 behavioural descriptors. These were distilled down through a four-step process:

  1. Behavioural Descriptor Extraction
  2. Clustering and Labeling
  3. Cluster Analysis by I/O Psychologists
  4. Thematic Categorisation and Definition of Competencies

This resulted in a refined list of 25 human-centric competencies, each with clear behavioural indicators and practical relevance across a wide range of roles.

Built to Scale. Built to Adapt.

Our framework is intelligent, but importantly, it’s adaptive. Organisations can apply this methodology to their own job descriptions to discover custom competencies. This bottom-up, role-data-led approach ensures alignment to real work, not just theoretical models.

And because the framework integrates directly with our AI-powered hiring tools, you get a connected system that brings your talent strategy to life. 

Our framework comes to life in the following tools: 

  • Job Analyser – Starting with a job description, it creates a unique competency profile for each role to build tailored structured interviews in seconds.
  • Structured Chat-based Interviews that assess candidates’ responses according to the competency profile for consistent candidate assessment.
  • Talent Insights Reports from every interview with deep reasoning and explainability for fair and objective hiring decisions.
  • Phai Career Coach for internal mobility and employee growth that considers their competency strengths and career aspirations.

The Future of Talent Acquisition & Development is Competency-First

Skills alone cannot predict success. Competencies do. As AI continues transforming how we work, Sapia.ai’s Competency Framework offers a scalable, scientific, and fair foundation for hiring and developing the talent of tomorrow.

Want to see how it works? Download the full framework.


 

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Blog

It’s Time to Stop Hiring for Skills, and Start Hiring for Competencies

If you’re a CHRO or Head of Recruitment at an enterprise today, chances are you’ve been inundated with messages about the importance of “skills-based hiring.” LinkedIn’s recent Work Change Report (2025) is full of compelling data: a 140% increase in the rate at which professionals are adding new skills to their profiles since 2022, and a projection that by 2030, 70% of the skills used in most jobs today will have changed.

This is essential reading. But there’s a missed opportunity: the singular focus on “skills” fails to acknowledge the real metric that talent leaders need to be using to future-proof their workforce — competencies.

Skills vs Competencies: The Crucial Distinction

  • Skills are task-specific capabilities. Think Python programming, Excel, or even negotiation.

  • Soft skills refer to interpersonal or behavioural qualities like adaptability, communication, and resilience.

But skills on their own — even soft ones — are generic, disjointed, and often disconnected from real-world performance. In contrast:

  • Competencies are clusters of skills, knowledge, behaviours and abilities that are observable, measurable, and context-specific.

Put simply, competencies answer the all-important question: Can this person apply the right skills, in the right way, at the right time, to deliver results in our environment?

Why Competencies Matter More Than Ever

The Work Change Report outlines a future where job titles are fluid, roles evolve quickly, and AI is a constant disruptor. This creates three massive challenges for hiring at scale:

  1. Roles are changing faster than static skill frameworks can keep up

  2. Job candidates may have non-linear, cross-functional backgrounds

  3. The shelf-life of technical skills is shrinking rapidly

Skills alone don’t tell us whether someone can succeed in a role that will look different 12 months from now. But competencies can. Because they measure not just what a person knows, but how they apply it.

Adaptive Talent: The New Competitive Advantage

The LinkedIn report highlights a critical insight: organisations now prioritise agility in entry-level hiring. And there’s a good reason for that. With professionals expected to hold twice as many jobs over their careers compared to 15 years ago, adaptability is not just a nice-to-have. It’s core to success.

But you can’t measure agility with a keyword on a CV. You measure it by looking at competencies like:

  • Learning agility

  • Change resilience

  • Cross-functional collaboration

  • Problem-solving in ambiguous contexts

When you shift the focus away from skills to behavioural competencies that can be defined, observed, and assessed in structured ways, you open yourself up to a much more dynamic and more useful way of managing talent.

Building a Competency-Based Talent Framework

To hire effectively at scale, particularly in a technology-driven world of work, talent leaders must shift their lens:

  1. Define Role-Specific Competencies: Move beyond job descriptions based on qualifications or vague skill sets. Break roles down into measurable competencies that reflect current and emerging performance expectations. This step is crucial for organisations to be able to accurately assess role-fit in the next stages. Sapia.ai does this automatically, taking job descriptions and building role-specific competency models in seconds.

  2. Assess Competencies Fairly and Objectively: Use structured behavioural interviews, ideally at scale. These provide a much more accurate picture of a candidate’s readiness than self-reported skills or credentials. Sapia.ai’s AI powered interviews enable competency assessment, at scale.

  3. Build Pathways for Development and Internal Mobility: A competency framework makes it easier to identify transferable strengths, development gaps, and future-fit potential. It gives employees clarity on how to grow within the business. Using an AI-powered coach can help ensure that talent is being continuously developed against the organisation’s competency framework.

The Future of Work Requires Depth, Not Just Breadth

LinkedIn’s data shows that people are learning more skills more quickly than ever. But the real question for talent leaders like you is: Are those skills being applied in ways that drive value? Are we hiring for task proficiency or performance?

The truth is that the organisations that will thrive in an AI-driven, skills-fluid economy aren’t the ones chasing the next hot skill. They’re the ones designing systems to identify, develop and scale competence.

Keen to Shift to Competencies, but Lacking a Framework? 

Sapia.ai has developed a comprehensive Competency Framework using a data-driven approach. Download the full paper here.


 

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