Before COVID, the conversations I was having with HR executives were about how Sapia might help them with the volume of candidates they were receiving for job openings. For every job posted there were often over a thousand candidates, and it doesn’t take much of a stretch of the imagination to understand how overwhelmed many big organisations were. Our Ai was seen as the solution to automate dealing with candidate volume in a way that found the best people, but also touched base with everyone who applied as part of their brand building. In a nutshell, before the pandemic, efficiency was the key driver in looking for automated hiring solutions like ours.
Now that we’re emerging from the disruption of COVID, no one is talking to me about needing help with the volume of candidates they receive. In fact, they are asking how we might help them get any candidates in the first place! All around the globe, and across multiple industries, there is a need for candidates. It’s certainly been an abrupt change that has left many scratching their heads, but there is almost no time to wrap your head around it if you want to stay in the game. This is a new war for talent unlike any we’ve seen before, and candidates have the upper hand. It’s created a need for a solution to solve two things: firstly, to identify skills in candidates that traditional ways of hiring failed to identify (I call this cohort “undiscovered talent”) and a strong candidate experience (you are the one being interviewed from the moment they hit “apply”).
I thought it was worth looking at how the “war of talent” has evolved since it was first coined by Steven Hankin at McKinsey & Company in 1997. At that time there was a shift in the way that companies valued their talent, and it became seen as important to attract the best in order to have a successful organisation. It’s hard to think about this now, but at that time the whole idea of cultivating company cultures that aimed to elevate and value employees was new. At this stage though the “war” was largely for executive talent with recruiters focusing on building their brand by poaching star C-Suite talent off competitors, wooing them with big sign-up bonuses and lavish overtures like unexpected gifts and trips.
As tech companies started to become the big players in the market, the focus turned from business acumen to the need for the best digital and technical talent. Recruiting became less about material perks (though many engineers still commanded high salaries) but also about giving talent things they wanted besides just money. Flexibility, free lunches, unlimited holidays and creating cultures that were about “working hard and having fun” were how the war for technical talent was won. This was really a time of culture wars between companies, but also meant that many companies hired only for culture-fit. This resulted in fairly homogenous teams that were largely white male techbros, and eventually many large tech companies were called out on it. Beyond tech, corporates were also waking up to the fact that they had some serious diversity issues that needed to be addressed. This led to a new war. The war for diverse talent.
Pre-COVID, hiring more diversely was a strong focus for companies to find the best talent. We all know that diverse teams result in better business outcomes and anyone who had a “pale, male and stale” executive team was seen as minted in the past. Coupled with Black Lives Matter, which became a global movement to address racial inequality from the C-suite down, finding more diverse talent through reducing bias in hiring, was where the war was being fought. This is not a won battle by the way, and remains a large focus for many companies that we work with and help. Importantly, finding diverse talent is still a key part of this new and emerging next phase of the “war on talent” … the one where workers have the upper hand. The one where candidates are in short supply, and people want jobs that suit them just as much as whether they are seen as just suited to the job.
Recruiters have been forced to look at people differently – and this is not a bad thing. Factors like age, ethnicity, education, gender and even past experience that obscured our understanding of someone’s ability to do a job have all been cancelled as qualifying factors. Soft skills, or human skills, have become the focus on what we need to understand in order to assess someone’s suitability to do a job. Are they a team player? Do they like to problem solve? How aligned are they to our company values? Are they self-aware and in touch with their emotions? Can they put stress aside to achieve outcomes?
“What we recruit for” has significantly shifted for many already, but there is still some catching up to do on the “how we recruit”. To be blunt, CV’s and cover letters begging recruiters to “pick me!” serve no purpose in this new battle. They ask too much of candidates from the outset, serve no valuable purpose in the information they provide, confirm our biases and just create work on the HR manager’s side.
We need to walk in a candidate’s shoes and make sure that our recruiting process puts them first, treats them fairly and without bias, meets them where they are at, and is both friendly and informative. And, HR teams need to do this all while working efficiently and fast. Speed is crucial when talent is in short supply.
Impossible? No, not at all. Recruiters need to understand that Ai platforms like ours exist to solve all these problems. We’re not a “technical” solution, but a human one, in that we can accurately identify soft skills immediately and engage with candidates in a one-on-one way, at scale.
You cannot win this war on talent without chat-driven Ai technology. Technology like ours is the only way you can quickly understand the real human skills that every candidate brings to the table, without dismissing anyone upfront.
I can’t help but think that these issues we’re facing as recruiters and HR managers right now, where workers have the upper hand, while unchartered territory, will only serve our industry for the better. It’s a chance to give everyone a fair go, truly understand them, treat them with the dignity they deserve … and still hire better teams.
Maybe it’s not a battle after all. Maybe it’s a win-win.
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For more on how to improve candidate experience using recruitment automation, we have a great eBook on candidate experience.
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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
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:
- Can we make competency discovery agile, scalable, and evidence-based?
- 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:
- Behavioural Descriptor Extraction
- Clustering and Labeling
- Cluster Analysis by I/O Psychologists
- 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.
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:
- Roles are changing faster than static skill frameworks can keep up
- Job candidates may have non-linear, cross-functional backgrounds
- 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:
- 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.
- 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.
- 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.