The Key to Hiring the Best of the Best in a Competitive Job Market

The pool of quality candidates is shrinking in an increasing number of industries as new demands emerge in terms of skills, such as data analytics, AI literacy, and sustainability expertise, among others. In order to beat this talent arms race, organisations should shift beyond vacancy filling and create a strategic, skills-centric and data-empowered recruitment system. 

 

There are five evidence-based principles which can be considered; 

• Live and communicate a great Employer Value Proposition (EVP): Spelt-out EVP is an identifying factor as to why the high-performers are supposed to choose (and remain with) the organisation. Prediction longitudinal studies in Indian IT sector indicates, a believable EVP creates employee engagement in first months after entry, which further predicts direct lower early-exit rates (Saks, 2021). On the other hand, the notion of over-promising or brand washing is a quick hack to lose trust and word-of-mouth within digital forums.
  
  
  Practical tip: Post audit of career-site messages, social-media posts and onboarding practices at once. Test subject experimentally the coincidence between the promise and experience in the first 90 days by means of pulse surveys. 
  
  
• Skills-based recruitment: Specific degree requirements can exclude special competence, and increase time-to-fill. In examining 11 million job adverts in the UK, a recent study reveals a rapid change of professional requirements that place emphasis on practical skills rather than accredited qualifications, specifically those in the areas of AI and sustainability (Bone et al., 2025). These ads that feature skills as first priority expanded the list of potential candidates and were associated with the fact that the vacancy was filled faster. 
  
  Best practice: Collaborate with hiring managers to map the outputs of any given role into competences that can be measured; combine online skills test or work sample tests high in the funnel.
  
  
• Harness AI responsibly to reach and speed: Screening using AI, chatbots and video-analysis tools have the potential to reduce the administrative overheads and provide applicant support 24/7. Applicants find organisational attractiveness when they believe that the tools to be used are fair and transparent (Tursunbayeva et al., 2025). But ill-regulated algorithms also have the threat of reputation: grounded-theory studies show how increased model bias may harm the interests of women and minority job applicants (Soleimani et al., 2025).
  
  
  Hands-on suggestion: Use an explainable-AI policy: keep people in the loop as regards of AI-driven selection processes, publish selection criteria, and audit models on disparate impact after every hiring season.
  
  
• Conceive a frictionless and human candidate experience: Quality of process is nearly as relevant as job itself. An experiment conducted in 2023 demonstrated that feedback given in time and individualised communications boosted applicants re-application or recommendation of the firm even in rejections (McCarthy and Von Hippel, 2021).. Slow (or non-transparent) processes, instead, drive limited talent out to competitors who move more quickly. 
  
  
  Practical tip: Trace the end-to-end experience once in search-to-route; monitor off-ramps; covenant to response-standard SLAs (e.g. acknowledge search in 24 hours, decision in two weeks). 
  
  
• Develop the talent pipeline that is alive around the clock: Reactive advertising would not be able to sustain the boom growth. Rather, successful companies keep in contact with niche groups, college alumni and junior employees, and constantly update databases of abandoned candidates. One multi-industry sample evidence shows that firms with both proactive sourcing and data-based forecasting new positions in critical locations 27 % quicker than counterparts (Stephany et al., 2025).
  
  Tactical takeaway: Combine-content marketing with workforce-planning analytics: provide webinars, hackathons or alumni newsletters that keep prospective hires involved months ahead of an opportunity arising.
  
  

Recruitment of the best of the best does not imply placing an ad and waiting. It needs a balanced system that (i) conveys a true value message, (ii) makes judgment based on skills, (iii) uses to the full and sensibly controls AI, (iv) treats all applicants as future ambassadors and (v) pumps talent, contingent of need. The firms that are capable of using these levers transform the limited expertise into a lasting competitive advantage of human markets in the current turbulent labour market.

 

REFERENCES

Bone, M., González Ehlinger, E. and Stephany, F. (2025) ‘Skills or degree? The rise of skill‑based hiring for AI and green jobs’, Technological Forecasting and Social Change, 214, 124042. Available at: https://doi.org/10.1016/j.techfore.2025.124042 (Accessed: 11 July 2025).

McCarthy, J.M. and Von Hippel, C. (2021) ‘Are job applicants treated fairly? A review of applicant reactions research’, Personnel Psychology, 74(4), pp. 873–910. Available at: https://doi.org/10.1111/peps.12427 (Accessed: 11 July 2025).

Saks, A.M. (2021) ‘Translating employer branding into employee outcomes: An engagement model’, Human Resource Management Review, 31(2), 100779. Available at: https://doi.org/10.1016/j.hrmr.2020.100779 (Accessed: 09 July 2025).

Soleimani, M., Intezari, A., Arrowsmith, J., Pauleen, D.J. and Taskin, N. (2025) ‘Reducing AI bias in recruitment and selection: An integrative grounded approach’, The International Journal of Human Resource Management, advance online publication. Available at: https://doi.org/10.1080/09585192.2025.2480617 (Accessed: 12 July 2025).

Tursunbayeva, A., Fernández, V., Gallardo‑Gallardo, E. and Moschera, L. (2025) ‘Artificial intelligence and digital data in recruitment: Exploring candidates’ perceptions of organisational attractiveness’, European Management Journal, 43(2), pp. 233–245. Available at: https://doi.org/10.1016/j.emj.2025.03.002 (Accessed: 10 July 2025).