Author: Buddhi Jayatilleke, Chief Data Scientist, Sapia.ai
While culture is a collective outcome, it isn’t something that just happens automatically. Leaders are responsible for defining the underlying values and must remain intentional about sustaining the desired organizational culture. A key part of culture is who you hire and how you hire them. We hear phrases like “Culture Fit” and “Culture Add” in the hiring process. These are part of “who” you hire and are used to both accept and reject candidates. But “how” you hire reflects your culture and creates the virtuous (or vicious) cycle that amplifies (or derails) an organizational culture.
“If you hire people just because they can do a job, they’ll work for your money. But if you hire people who believe what you believe, they’ll work for you with blood and sweat and tears.” – Simon Sinek
The above quote, attributed to Simon Sinek, makes a great point, but how do you find people “who believe what you believe”? In other words, how do you attract and hire individuals who will thrive in and uplift your culture? The experience through the candidate’s journey plays a key role.
And today we have a new enabler. Artificial Intelligence (AI).
AI certainly can not create culture. Culture is innately a human construct. However, AI as a tool can help sustain, project, and amplify culture through effective engagement with employees and candidates. From job description writing to employee coaching, new generative AI tools, built on ethical principles, can help organizations instill their culture through sourcing to onboarding.
Here I highlight four key steps that leaders should pay attention to for building the right “hiring culture” and how AI can help. Due to my own experience in the selection process, more emphasis is placed there, but all 4 steps are equally important.
The job description is often the first interaction potential employees have with your organization. The language used, the values highlighted, and even the requirements listed can say a lot about your culture. For instance, emphasizing teamwork and collaboration suggests a culture valuing collective success over individual achievements. Using gender-neutral language can help attract a candidate pool that is gender diverse. These indicators give candidates an upfront understanding of what you prioritize and allow them to self-select based on fit.
Companies can enhance this first impression by providing more interactive means to get to know the organization rather than using static career websites filled with a lot of content. While some organizations do a great job in structuring the content and including more engaging content such as videos from existing employees, FAQ’s etc, these approaches fail to address questions a potential applicant might have in a timely manner. In a high-volume recruitment scenario, it is impossible to have human recruiters answer thousands of questions via phone or text chat.
This is where smart chatbots built on top of generative AI like Sapia.ai‘s Phai, a careers site assistant, can help. Phai can ingest all the relevant content on a website (or other sources) and then provide fast personalized responses to candidate queries, 24/. Phai not only enhances the experience but also increases the chances of a candidate completing the application process. Chat with Phai yourself by clicking the blue icon in the bottom right of your browser.
The selection criteria and the selection process are reflections of what the organization values. Prioritizing skills over experience may indicate a culture that values continuous learning and potential. An interview is a common step in the selection process and most of the time it is unstructured and fraught with bias. We can all fall victim to various unconscious biases at this stage (and sometimes practice conscious ones too, unfortunately). As an example, here are 4 common ones that I have noticed in fast-paced growth environments like startups:
One way you can interrupt these human biases is to include an AI assistant in the process. This is where tools like Sapia.ai’s Chat Interview™ can help. Chat Interview™ conducts a chat-based structured interview that is scored by AI. Structured interviews are found to be high in validity and low in bias among the many options available to assess candidates. Hiring managers get access to a detailed report called Talent Insights (Ti) that can challenge some of their biased views and help them make better hiring decisions. For instance, independent research conducted using the Sapia.ai Chat Interview™ found a 36% reduction in the gender gap relative to recruitment without AI. One of the practices the Sapia.ai Chat Interview™ encourages is asking value-based interview questions to gauge alignment with company values. For example “Could you tell me about a time when you went above and beyond to help a team member at work?”.
The onboarding process is a critical stage for instilling organizational culture in new hires. Effective onboarding programs that align new employees with organizational values and expected behaviors can have a lasting impact on their integration and success within the company. As more companies become distributed and rely on remote work, part of company culture can be collaborating effectively over tools like wikis, and messaging apps like Slack and email. This requires making sure a new hire knows how to use these tools well and content norms specific to the company. This also brings to light the importance of “connection” as part of building culture, as in a remote work environment you have to be more intentional in building connections than when working together in an office. You can read more on this in “HR for the world of tomorrow“ where we discuss the changing landscape of work and how smart chat is the new medium for building connections.
How feedback is provided during the hiring process and the onboarding period can also be a cultural indicator. A culture that values growth and development is likely to provide constructive feedback to candidates (whether they are hired or not) and to new employees in an effective manner. This is the philosophy that Sapia.ai Chat Interview™ follows with My Insights, a feedback email every candidate gets after completing the chat interview that includes personality insights and coaching tips. The Sapia.ai Talent Insights report provides similar insights to the hiring managers that help them prepare for onboarding a new hire.
In essence, every aspect of the hiring process – from the job description to the final decision – is a reflection of your organizational culture. By being mindful of this, organizations can ensure they not only attract the right talent but also reinforce the culture they aspire to maintain and develop. AI can be used as a tool to mitigate biases, form a consistent process, and enhance the candidate experience to better reflect the company culture.
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.