Did anyone notice the Linked-In post by ‘SCOMO’ on the weekend, dressed in a cardi, holding a plate of home-baked samosas? A leaf out of the NZ PM’s playbook. Trust is fast becoming or is already the organisational trait that is critical for now.
It’s the lack of trust that limited work from home until now.
It’s trust in leadership that makes your workers give lots of discretionary effort.
For big-name consumer brands, your customers are both the people in the store buying your products and the people who want to work for you. When you only have so many jobs to go around, when your candidates are an extension of your consumer reach, you can still give them dignity, you can do even better and give them a hand up, just by changing how you recruit.
How many consumer brands are doing the maths on the cost to build a trusted consumer brand via traditional marketing (traditional brand advertising + social) in a crowded market and the cost of acquiring consumer trust if you think of your candidates as your consumers?
For any relationship, trust starts early. That means trust starts to grow (or diminish) from your very first interactions with your future employee – from your application process through to how you conduct your interviews.
In our current reality of having to work from home and to interview remotely, building trust can be even more of a challenge.
With technology now in the market that ensures every single applicant receives fast automated personalised learning from their interview, there is no excuse for black-box recruiting.
Historically, recruitment is laden with ambiguity and secrecy.
Requiring a live conversation with an org psych if you ever wanted to know your results from sitting your 3-hour psychometric test
Receiving the ubiquitous reject email or call – you don’t meet the requirements of the role, or worse, ‘you are not a good culture fit’
The known unknown- that it could be weeks or even months until you know whether you get the job
Even a few years ago, we wouldn’t question the black box of recruitment, the lack of a reply, and certainly, we wouldn’t expect to receive feedback from an interview. Or to be asked to give feedback
Any company can introduce a feedback request into their recruitment, but giving feedback requires real smarts if you don’t want to kill trust.
And that feedback needs to be meaningful, relatable useful and ideally immediate. A feature enabled only by AI and only by smart human AI.
Today you can access smart AI to give every applicant that learning opportunity. And why wouldn’t you make that a priority in a world of growing unemployment and more disappointed candidates?
Plus, for a consumer brand, their candidate pool is usually also their consumer base and the bigger the brand, the more rejections they give out. In some cases, they are rejecting candidates in 6 figures. Which makes the candidate experience vital for the business even more than for your EVP.
No matter how many candidates apply and how many you bring through to your recruiting process, enhance trust by giving every one of them automated personalised feedback.
Barb or Buddhi? Who do you think has a greater likelihood of getting the interview? I don’t like my name much, but I don’t believe it’s ever been a factor in my career opportunities. Unlike Buddhi, my co-founder. When I interviewed Buddhi for the role, he said he had experienced the ‘name’ discrimination himself.
An NYT article reminded us that simply having a ‘white name’ presents a distinct advantage in getting a job – call-backs for that group being 50 per cent higher. We have already written about the fact that no amount of bias training will make us less bias.
We worry intensely about the amplification of lies and prejudices from the technology that fuels Facebook. Yet do we hold the mirror up to ourselves and check our tendency to hire in our image? How many times have you told a candidate they didn’t get the job because they were not the right “culture fit”?
The truth is that we humans are inscrutable in a way that algorithms are not. This means we are often not accountable for our biases. And bias training has been proven not to be an effective guard against biased hiring.
Enhance trust with your applicants by committing to blind screening, at least at the top of the funnel. While it’s tempting in a world of ‘zoom everywhere’, video interviews are the opposite of blind screening.
Similarly relying on AI that uses deep learning models to find the best match, also don’t endear themselves to building trust with your applicant pool. They make explainability a real challenge for the recruiters.
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:
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.
DEI by Design, Not by Mandate
With Sapia.ai:
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.
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:
“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:
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?
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.
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.)
Sapia.ai’s methodology is rooted in the science of human behaviour but powered by cutting-edge AI. We asked two core questions:
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:
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.
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:
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.
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.
But skills on their own — even soft ones — are generic, disjointed, and often disconnected from real-world performance. In contrast:
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?
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:
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.
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:
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.
To hire effectively at scale, particularly in a technology-driven world of work, talent leaders must shift their lens:
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.
Sapia.ai has developed a comprehensive Competency Framework using a data-driven approach. Download the full paper here.