The State of Job Descriptions: Trends, Best Practices, & AI-Powered Optimization 

Gem Siocon
Latest posts by Gem Siocon (see all)

Executive Summary & Introduction  

The job market is rapidly changing. Job descriptions are now considered strategic tools in influencing hiring decisions and outcomes, enhancing employer branding, and improving candidate experience. Companies now use data, AI, and inclusive language to create job postings that attract top talent while aligning with business goals. 

This whitepaper explores the latest trends in job descriptions, including the rise of skills-based hiring and the impact of AI and employer branding in refining job descriptions. It examines how companies can optimize job descriptions using artificial intelligence, data analytics, SEO, and competitive benchmarking. In addition, it addresses challenges in job description biases, sustaining candidate engagement, and ensuring compliance with employment laws. By implementing modern job description best practices, organizations can hire better candidates that drive organizational success. 

Trends Shaping Modern Job Descriptions 

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Data-Driven Job Descriptions 

Recruiters today are no longer relying on traditional guesswork to craft job descriptions – they are using hiring data, industry benchmarks, and job market insights to optimize job postings and get better hiring results. According to CIPD, more organizations are collecting workforce planning and resourcing data, with 24% collecting data on their recruitment processes’ ROI, up from 13% in 2022. 

ATS and hiring tools allow recruiters to analyze historical recruitment data, such as click-through rate, application rate, time spent on the career page, and time to fill. These metrics reveal how candidates interact with job descriptions. It will then inform recruiters if the language is unclear or the formatting is ineffective. For example, if a job description including salary information receives many applications, recruiters should do the same for other job postings. 

Measuring Job Descriptions

Measuring job descriptions against industry benchmarks can help improve them. Tools like salary surveys and competitor analysis assist recruiters in determining whether the role’s compensation is competitive enough or whether the employee benefits align with industry standards.  For example, suppose a competitor in the same industry offers higher salaries or additional perks (e.g., hybrid work options). In that case, recruiters can adjust their job descriptions accordingly to stay competitive in attracting top talent.

Crafting data-driven job descriptions should also be guided by real-time insights. Current hiring trends, in-demand skills, and candidate preferences should be considered to ensure job listings resonate with the target candidates. This involves using labor market reports, checking the platform’s analytics to monitor candidate behavior, and staying updated on industry trends. 

While data-driven job descriptions offer significant advantages, overreliance on data does not provide the complete picture of the recruitment process.  Hiring manager needs, company culture, job fit, and team dynamics are the ‘qualitative’ factors that must be considered when writing job posts to hire high-quality candidates. Moreover, data-driven recruitment only measures short-term goals like the volume of applicants but won’t help with long-term objectives like candidate quality. For example, data can give information on the number of applicants, but it won’t advise whether they’re high-quality candidates, which is crucial for employee retention. 

Best Practices 

  • Review recruitment analytics to see how job descriptions perform. Check metrics like application rate and CTRs to see which job posts need optimization to increase applications. 
  • Balance data-driven optimization with a human-centric approach to ensure a positive candidate experience. Recruiters should work with hiring managers and current employees to ensure that JDs reflect qualitative and quantitative insights.
  • Implement strong data privacy measures to comply with relevant data privacy laws. Enforce GDPR-compliant hiring practices and secure candidate data when collecting recruitment analytics.
  • Provide the necessary training and tools to recruiters to effectively implement data-driven recruiting. 

The Rise of Skills-Based Hiring in Job Descriptions

Employers are rethinking the role of degrees in hiring. With more than half of U.S. job postings in 2024 no longer requiring a formal education (Indeed), skills-based hiring is redefining how companies attract and assess talent. Skills-based hiring allows recruiters to bypass educational requirements or years of experience, accessing more diverse candidates with solid skills who can do the job just like their college counterparts. It also sets the right expectations by hiring candidates based on their competencies. Recruiting people because of their competencies ensures their abilities can directly support business goals. Other factors, such as potential, experiences, and soft skills like resilience, adaptability, and willingness to learn, are also important indicators of job success that should be considered. 

From Google to Tesla, leading organizations prioritize hands-on experience over traditional credentials. For example, in 2023, IBM removed degree requirements from over 50% of its job postings. They also launched their SkillsBuild initiative, which offers training programs for candidates with non-traditional backgrounds. As a result, IBM reported a 63% increase in applicants from diverse talent pools.

Competencies vs Credentials

AI-powered tools accelerate this trend by helping companies focus on competencies rather than credentials. It can predict job success by analyzing candidates’ prior work experiences, skill sets, and behavioral traits. For example, instead of a “Bachelor’s Degree in Computer Science,” AI suggests focusing on skills like “Proficiency in React.js and JavaScript” and listing the skills necessary for the role, like ‘JavaScript, HTML5, and CSS3.’ Recruitment software Eightfold AI uses machine learning to match candidates to roles based on their abilities and experiences, ensuring a skills-first approach to hiring.

However, while skills-based hiring has advantages, it is not a one-size-fits-all solution that can be applied to all industries. Educational qualifications are still essential in fields like healthcare and engineering. These industries require high-level expertise and adherence to regulatory and safety standards, which skills-based hiring cannot replace. In these situations, licenses and certifications are good alternatives to traditional four-year courses. 

Best Practices

To implement skills-based hiring effectively, companies should:

  • Conduct a job analysis to identify key competencies.
  • Use technical, behavioral, and job knowledge assessments to measure hard and soft skills.
  • Standardize hiring processes to ensure fairness and consistency. Develop clear criteria for evaluating candidates, establish consistent assessment methods, and ensure hiring managers are trained to assess skills effectively.  

Inclusive and Bias-Free Language in Job Descriptions

Research has shown that job advertisements often influence who applies. Hidden biases in job descriptions can unintentionally discourage certain applicants. A foundational Harvard study found that masculine-coded words (e.g., ‘competitive,’ ‘leader’) make women feel less of a sense of belonging in male-dominated roles, even if they believe they are qualified.  

More recent studies confirm this effect. According to a Glassdoor Diversity Hiring Survey, 76% of job seekers and employees report that a diverse workforce is essential when evaluating companies and job offers, while 32% would not apply for a job at a company lacking diversity.  Lever also reported that 81% of employees check out the company’s vision for DEI before applying, while 71% review job postings to ensure inclusive language is used. These studies show that inclusive job descriptions widen the talent pool and improve the company’s reputation, leading to a better quality of available candidates. 

The markers of inclusive and unbiased job descriptions

Inclusive job descriptions use words and phrases that welcome applicants of all backgrounds, regardless of gender, age, race, ability, or sexual orientation. They are characterized by unbiased language, state clear requirements, and offer employee benefits catering to diverse candidates. Job postings also include diversity and EEO statements.  For example, Lowe’s receiver/stocker job description uses language inclusive such as “Able to stand and sit for prolonged periods” and Ability to hear, listen, and to communicate verbally with others.”  Airbnb offers an extensive benefits package that includes health insurance, disability insurance, and flexible work arrangements, appealing to diverse candidates. Tools like Ongig can help make jobs more inclusive by scanning job descriptions for biased words and suggesting neutral alternatives. 

Although inclusive job descriptions help create equitable and diverse work environments, limitations exist. According to MIT Sloan, tweaking the language of job postings to make them more gender-neutral has little practical effect on the likelihood of men and women applying for jobs and their behavior during recruitment. In other words, altering job descriptions’ language may not help organizations address diversity issues. Unconscious bias influences hiring decisions, performance evaluations, promotions, and workplace culture. Organizations should take a holistic approach by implementing comprehensive training and systemic changes to address unconscious biases.

Best Practices: 

  • Remove exclusionary words and phrases. Remove any technical jargon 
  • Be brief and transparent on requirements and responsibilities 
  • Include a salary range 

Candidate-Centric JDs and Personalization

Today’s job seekers don’t just want jobs. They want to apply for roles that align with their career aspirations. With career advancement and skill development ranking among the top five priorities for candidates (LinkedIn), job descriptions must evolve to meet these expectations. 

A candidate-centric JD prioritizes the applicant’s needs over the company’s demands. It focuses on growth opportunities, work-life balance, and employee benefits that resonate with target candidates. Instead of saying, “You must have X years of experience,” it should state, “You’ll grow in this role by leading projects that impact our market position and competitive advantage.” It is also transparent. It gives a realistic view of what the candidate will do daily so they can visualize their responsibilities and potential.  

A candidate-centric job description attracts and converts the right candidate, resulting in better candidate quality and faster recruitment. It also enhances the candidate experience and employee retention. According to Gallup, strong candidate experiences positively correlate with long-term employee satisfaction. 

The role of personalization

Personalization takes candidate-centric JDs further by tailoring them specifically to various candidate personas. For example, job descriptions for early-career marketing professionals emphasize developing marketing skills, while job posts for junior marketing executives focus on senior leadership opportunities. AI analyzes data from past successful job descriptions to craft new JDs that resonate with target candidates. For example, a recruiter uses AI to create a social media manager job posting customized to his company’s tone and industry standards.

To meet evolving candidate expectations, companies use AI-powered tools to craft candidate-centric and personalized job descriptions. Workable’s AI tool generates fresh, customized job descriptions that recruiters can edit, specifying company details and aligning with their culture. SmartRecruiters synthesizes information from candidate profiles and past job descriptions to create customized job descriptions. 

While candidate-centric job descriptions and personalization offer several benefits, crafting them for different candidate personas requires more time and effort. There’s the risk of excluding qualified candidates who don’t fit the prescribed candidate persona. To prevent candidate exclusion, companies should test multiple versions of job postings, analyze engagement metrics, and gather feedback from diverse hiring teams. 

Best Practices: 

  • Use clear and concise language. Make your job posts sound conversational but still professional.
  • Be transparent about salary and benefits so candidates can decide immediately if they’ll apply. 
  • Highlight company culture and growth opportunities to give a sense of what it’s like to work at your organization and what makes it unique. Provide specific examples like mentorship programs, leadership training, or employee testimonials.

SEO and Discoverability 

With millions of job seekers relying on Google, recruiters must optimize their job descriptions for search engines. Research has shown that 70% of job searches begin on Google, which receives over 150 million monthly job searches. 29.9% of job seekers on Google are looking for open positions, and 27.3% are applying. This information highlights the importance of optimizing job postings for search engines to ensure they appear in relevant search results. 

SEO helps job descriptions get discovered by candidates who are actively searching. For example, Cinemark optimized its career pages, leading to 1,550 indexed job results on Google, improving accessibility for potential applicants. However, SEO has limitations. Overloading job descriptions with keywords (keyword stuffing) can result in penalties and reduce the visibility of job postings in search engines. It also makes the job description harder to read, making it difficult for candidates to engage and apply for the position. And while SEO can increase the number of views on job postings, it doesn’t guarantee that these views come from highly qualified candidates. It may inadvertently attract many candidates who are considered a poor fit for the job. 

Best practices: 

  • Perform keyword research – Use Google Keyword Planner or LinkedIn Talent Insights to find job-related keywords.
  • Optimize job titles. Keep them 50-60 characters, avoiding overly creative or vague titles.
  • Improve readable.  Use bullet points, headers, and structured formatting to make job descriptions scannable.
  • Balance SEO with engagement. Include culture, benefits, and growth opportunities to attract the right candidates, not just more candidates.

Employer Branding

Employer branding is no longer optional. According to LinkedIn, 75% of job seekers consider an employer’s brand before they apply for a job. This development has transformed job descriptions from simple lists of responsibilities into effective marketing strategies to attract top talent. 

Modern job descriptions emphasize company culture, values, career growth opportunities, and DEI initiatives. According to Indeed, 72% of job seekers say it’s extremely important to see details about company culture in a job description. Job descriptions can be more compelling by using images, videos, infographics, and storytelling techniques. Lego and Red Bull communicate their culture and employer brand through employee stories and testimonials. 

However, it’s important to note that a strong employer brand cannot compensate for a poor candidate experience. ERE’s benchmark research shows that only 29% said they would likely refer others based on a positive candidate experience. In comparison, 15% said they’d actively discourage others from applying based on a negative candidate experience. These findings show that brand perception impacts referrals. They also underscore the need to make the application process a genuine and positive interaction beyond employer branding.

Best practices: 

  • Highlight company values and culture with employee testimonials. Bring these stories to life with photos and videos.
  • Use clear and concise language when writing job summaries and responsibilities to set the right expectations. 
  • Provide an easy and seamless application process with clear instructions to improve the candidate experience. 

AI-Powered Job Description Optimization  

How AI is Transforming JD Creation and Review 

With companies struggling to attract top talent, AI is reshaping job descriptions by improving clarity, reducing bias, and boosting engagement. 

According to SHRM’s 2024 Talent Trends AI survey, 65%  of organizations use AI to generate job descriptions. 40%  customize their job postings further to better attract target groups. One respondent even said they used AI to develop new policies for creating job descriptions, job postings, and employee/candidate communication. On why HR uses AI to support recruitment and hiring activities, 88% said it saves them time and/or increases their efficiency. 

AI-powered tools like ChatGPT and Ongig can assist recruiters in quickly generating job descriptions: 

  1. Create job descriptions from scratch. Just input the job title, which will automatically create the responsibilities and qualifications for the position. It can also be prompted to write a company and job overview, compensation and benefit details, and an EEO statement.
  2. Create job descriptions on a large scale for numerous job openings
  3. Standardize formatting through job description templates to maintain uniformity across postings.
  4. Translate job descriptions into different languages when hiring for other regions. 
  5. Rewrite them to be more compliant with employment laws. 

Natural Language Processing

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Natural Language Processing (NLP) tweaks job descriptions based on what the applicant might search for to find the job opening. It analyzes job description structure and tone and rewrites them to make them clearer, more readable, or more engaging.  For example, it can change the style from formal to casual so they appeal to the younger candidates. It also suggests keywords to make them more visible on search engines and job boards. Predictive analysis forecasts how well a job description will perform based on click-through rates, application rates, and time to fill. Then, it adjusts language, structure, and content to make them more attractive to the right candidates, increasing engagement and reducing hiring time. 

While AI offers numerous benefits, it may inadvertently introduce or perpetuate biases if trained on flawed data. It may miss subtle contextual cues vital for attracting the right candidates. These uses raise crucial ethical considerations. Furthermore, AI cannot capture the nuances of the company’s workplace culture, team dynamics, and specific organizational goals, making your job description generic and forgettable. 

Best Practices

To effectively implement AI in job description creation while mitigating ethical risks:

  • Use AI review tools like Ongig to check for biased or exclusionary language. Compare AI-generated JDs with high-performing past job postings to assess effectiveness.
  • Audit AI systems and training data regularly for bias. Ensure AI training data includes diverse candidate pools.
  • Train hiring teams to recognize bias. Create ethical guidelines for AI use when writing job descriptions. 

AI-Powered Bias Detection and Removal 

Biased job descriptions can limit the candidate pool and reduce workplace diversity:

  1. National Bureau of Economic Research study revealed that, on average, applicants with Black names were 10% less likely to receive a callback than applicants with White names.
  2. SeniorLiving.org reported that 52% of older workers said that if they actively looked for new jobs today, their age would negatively impact their job searches.
  3. The US Bureau of Labor Statistics highlighted that unemployment rates were much higher for people with a disability than for those with no disability.

AI has transformed the traditional hiring process. It detects discrimination in job posts that discourage candidates from underrepresented groups from applying.  AI flags gendered language like ‘independent’ or ‘strong’ that is considered ‘masculine’ and replaces more neutral alternatives. A study by Monash University involving 500 tech recruiters revealed that when recruiters had access to both AI-generated scores and anonymized applications, gender bias was not observed, indicating that AI can effectively aid in reducing bias during candidate assessment.

How AI-Powered Tools Help Improve Job Descriptions

AI-powered job description tools like Ongig and Textio scan job descriptions, identifying words and phrases that suggest discrimination against gender, age, race, sexual orientation, elitism, religion, and neurodiversity. For example, it flags ‘digital native’ on the job description and suggests its omission.  AI then scores job descriptions for inclusivity and recommends more inclusive alternatives. It also ensures that job posts comply with relevant employment laws like Equal Employment Opportunity (EEO). 

However, while AI offers solutions to recruitment biases, it also has limitations. If the data used to train AI-enabled recruitment software is biased, it will also generate biased outputs. Resume Builder predicted that even though 7 in 10 companies will use AI in the hiring process in 2025, nearly all companies still believe AI produces biased recommendations: 47% of companies believe it leads to age bias, 44% cite socioeconomic bias, 30% mention gender bias, and 26% point to racial or ethnic bias. 

56% of companies also worry that AI could screen out qualified candidates. Moreover, improperly designed AI systems expose organizations to legal risks under anti-discrimination laws. For best results, implement a hybrid approach allowing HR to use AI tools to expedite the job description writing process. At the same time, human oversight should be applied for review and final approval. 

Best Practices

  • Carefully review all AI-generated job descriptions. Use AI tools to scan and eliminate biased words. Ensure they are accurate, clear, and fit the company’s tone and brand. Incorporate feedback from hiring managers and team members. 
  • Audit AI systems and training data regularly for bias. Check the data sets on which AI models are trained to ensure diversity and fairness.
  • Train hiring teams to recognize bias. Create ethical guidelines for AI use when writing job descriptions, interviewing, and making recruitment decisions. 

AI for Competitive Benchmarking 

Using AI for competitive benchmarking refers to comparing and analyzing job descriptions against industry standards and competitor practices. Recruiters learn the latest information on market trends, skill requirements, and compensation levels to update job descriptions so they become more effective in attracting top talent: 

Skills benchmarking – identifying the skills needed for a particular job within the industry. Cornell University’s Generative AI Impact on Labor Market study underscores the growing demand for Chat-GPT-related skills in job ads. It integrates them into job postings to attract applicants with relevant AI skills. Gloat enables skill benchmarking by comparing employees’ skills against organizational and industry-wide standards.

Salary benchmarking – comparing and aligning compensation levels with current market rates to ensure they are competitive and fair. Payscale uses AI to automatically match jobs to relevant salary market data for precise benchmarking. This ensures that compensation decisions are accurate and updated. 

Market trends benchmarking – uses predictive analytics to predict future salary trends and market demands so companies can adjust their compensation strategies accordingly.  LinkedIn Talent Insights works by understanding how companies compare with competitors across key hiring and workforce trends. Recruiters can access real-time data from 200 countries, over 850 million member profiles, 58 million companies, and 20 million jobs. 

AI Limitations with Job Descriptions

While AI offers significant advantages, it’s not without limitations. AI relies on publicly available data, which may not fully capture competitor data. Organizations won’t know other companies’ hiring strategies, leading to incomplete benchmarking. Another is job title inflation, which distorts comparisons. For example, a ‘Customer Service Manager’ in one company may have similar responsibilities to a ‘Customer Team Lead’ in another organization.

The inconsistencies can make it difficult to compare roles across companies precisely. AI benchmarking may also lead to over-standardization of job descriptions. Overstandardization limits the flexibility and innovation of roles. As a result, job postings are less personalized to the company’s unique culture, resulting in candidates that may be qualified skills-wise but are not considered a good add culture-wise. 

Best practices:

  • Combine AI insights with human intelligence and internal data. Use AI to analyze job responsibilities and required skills rather than mitigate job title inflation. Combining AI and human intelligence ensures that benchmarking is accurate and comprehensive. 
  • Use tools like LinkedIn Talent Insights to access real-time data on hiring trends and competitor strategies to stay updated about industry standards and best practices.
  • Employ predictive analytics to forecast future salary trends and market demands, and companies can adjust compensation strategies proactively. This ensures that salary packages stay competitive and aligned with future market conditions. 
  • Continuously review and update job postings to remain relevant and effective in attracting top talent. Receive feedback from employees and hiring managers. 

AI and Performance Analytics for JDs

With job seekers spending an average of 49.7 to 76.7 seconds reviewing a job description before deciding whether to apply, recruiters must ensure job postings are clear, engaging, and optimized for maximum visibility. Traditionally, job descriptions were written based on intuition and past experiences, but AI-powered analytics now enable data-driven optimizations to improve recruitment performance. By tracking click-through rates (CTR), application rates, engagement metrics, and predictive hiring insights, AI helps organizations refine their job descriptions to attract the right candidates faster: 

1. Click-Through Rate (CTR) Analysis

AI compares the number of views vs. clicks-to-apply to determine how effective a job description is. AI suggests optimizing job titles, descriptions, and formatting to improve visibility if CTR is low. Talention enables recruiters to optimize CTAs by analyzing click and conversion rates. Similarly, CareerBuilder’s AI-powered Google Cloud solution improved CTR by 40% and led to an 18% increased in applications in key job categories (Google Cloud).

2. Application Rate Optimization

AI detects where candidates drop off in the application process. If a job description is too lengthy or complex, AI recommends concise language and better readability to improve application rates. Lever provides real-time analytics to track completion rates and suggest refinements that reduce candidate friction.

3. A/B Testing for Job Description Engagement

AI can run real-time A/B testing to determine which JD versions perform better. For example, one JD may emphasize remote work, while another highlights career growth opportunities. AI then tracks which version generates more applications. Wonderkind helps recruiters optimize job ad campaigns through A/B testing, ensuring job descriptions are data-driven and candidate-focused.

4. Candidate Behavior Insights

AI evaluates how long candidates read job descriptions and whether they engage deeply or bounce off quickly. Appcast tracks drop-off points during the application process and provides recommendations to improve candidate engagement and reduce time-to-apply metrics.

5. Predictive Hiring Analytics

AI identifies which JD formats lead to faster hires and better candidate quality. Short, skills-based job descriptions perform better than long, rigid postings. Eightfold.ai leverages machine learning to predict hiring success based on historical hiring trends and job description performance.

However, despite AI’s sophisticated ability to analyze job descriptions, there are drawbacks. AI needs large datasets to make accurate predictions. So, for niche positions that have limited available data, it won’t be able to predict candidate fit accurately. For example, creative roles such as graphic artists require subjective evaluation of their portfolios. AI might struggle to assess the quality or originality of their creative output, resulting in inaccurate predictions of candidate suitability.

Furthermore, AI recommendations may not account for company-specific needs like cultural fit or specific skill combinations. This could lead to job descriptions not aligning well with organizational requirements, attracting poor-fit candidates. AI also can’t recognize brand identity or tone so AI recommendations won’t reflect company values in job descriptions. 

Best Practices for AI-Driven JD Optimization

  • Use AI-powered dashboards to track JD performance in real-time (CTR, application rates, engagement metrics).
  • Refine job descriptions continuously based on AI-driven insights but incorporate recruiter expertise to maintain authenticity.
  • Ensure AI-generated JDs reflect employer branding by involving hiring managers and marketing teams before finalizing job posts.
  • Audit AI models regularly to detect bias and ensure inclusive hiring practices.

Best Practices for Writing Effective Job Descriptions 

Structuring JDs for Clarity and Engagement 

Use clear and accurate job titles to match candidates’ job searches. If possible, indicate the level of seniority or the specific competency needed for the position. For example, use Senior Marketing Manager – Email Campaigns instead of Digital Marketing Manager. 

Engage applicants by describing the company’s mission, values, and the employer value proposition. Add photos or videos showcasing the company culture, work environment, or employee testimonials (if possible). Explain why the company is a great place to work and why the role is essential. Mention any training, promotions, and other professional development opportunities. These perks help attract candidates who are serious about their careers and want to see a future with an organization. 

List the job responsibilities in a straightforward and bullet-point format.  Focus on what the candidate will do regularly. It would also be helpful to describe the deliverables such as ‘ Submit 25 leads weekly’.  Also, list the essential and desired skills, qualifications, and experience. Describe how the skills and knowledge are relevant to the role’s tasks. 

Include salary range in the job description to set expectations. Specify employee benefits, especially those that go beyond the basics (e.g., health insurance, paid time off, retirement plans), such as professional development budgets, wellness programs, etc, to entice job seekers further to send their applications. 

Set clear expectations for working locations and hours, including typical hours, schedule, and other work information about the work environment. Specify if the work is remote, on-site, or hybrid. 

Writing in a Clear and Inclusive Manner 

Use simple, familiar, and specific job titles so everyone can understand them.  

Write job descriptions in a conversational but professional style. If possible, avoid using jargon that could confuse some candidates. Stick with specific words to avoid misunderstandings. 

Remove exclusionary language that discourages people from underrepresented groups from applying, such as ‘recent graduates’ or ‘digital natives’, in the job description. For example, a phrase like “native English speaker” might make a qualified candidate who speaks English as a second language feel left out. Using something like “fluent in English” is a more inclusive option. Use tools like Ongig that scan job postings for sexist, racist, and other exclusionary words and replace them with more neutral alternatives. 

Be concise when writing job responsibilities and qualifications.  Only include qualifications and skills that are necessary for performing the job. Long lists of requirements might deter applicants with a neurodiversity. For example, someone with autism might not feel qualified to apply if they don’t meet every requirement on the list.

Publish salary information and employee benefits so candidates know upfront if the position fits them. It also helps organizations expedite hiring by filtering out candidates with mismatched salary expectations. 

At the end of job descriptions, always have an EEO statement. 

Leveraging Employer Branding 

When writing job descriptions, connect with the company’s purpose. Highlight the impact of the company’s products and services on its customers and employees. Employees are more motivated to work when they know their jobs contribute to something bigger than themselves. 

Integrate your company’s core values into the very fabric of the description. Instead of listing the values, demonstrate them with real-world examples of how they’re being implemented in the workplace. For instance, if a team’s mission is to encourage DE&I, then promote the HR team to seek to build the culture surrounding that message.

Weave the company values into the job description. Demonstrate the unique benefits a company may offer. For example, if the company values career growth, the job description should include professional development, training, or mentorship opportunities. Companies that value work-life balance offer flexible work arrangements, generous PTO, and wellness programs. 

Tailor messages to the target candidates. Use tone and language that would resonate most effectively with them. 

Engage candidates by adding images and videos to break the text of the job description. Capture company culture by showcasing the office environment, team collaborations, or company events. Post videos of employees sharing their experiences working for the company. 

Ensuring Compliance and Legal Accuracy

Writing legally compliant and accurate job descriptions is critical to avoid misrepresentation, discrimination, and other employment law violations. Misrepresenting job responsibilities can lead to legal issues related to employee expectations and performance management.

Job descriptions should clearly outline the primary job function to ensure it complies with the ADA, which prohibits discrimination against qualified individuals with disabilities. Job functions are the tasks an employee must regularly perform. It is especially important to have the legal team review new job postings, roles that had major revisions, or when there is a possible compliance concern. It’s important to stay current with employment laws and regulations to ensure job descriptions remain compliant. Conduct regular job audits to help identify compliance issues or inaccuracies and immediately address them. 

Future Outlook: The Evolution of Job Descriptions 

According to the World Economic Forum’s The Future of Jobs Report, 22% of current jobs will be affected by 2030, with 170 million new jobs created but 92 million jobs displaced. Jobs involving technology, AI, cybersecurity, and data analytics are accelerating, while clerical and administrative positions are becoming obsolete due to automation. The change is driven by the emergence of AI, climate change, demographic shifts, and the economy. Hence, job descriptions now emphasize flexibility, continuous learning, and the ability to reskill or upskill. 

AI and automation are transforming businesses, with 86% of employers expecting AI to reshape industries by 2030. Tech occupations such as Big Data Specialists, Fintech Engineers, and AI and Machine Learning Specialists are emerging and projected to increase. Job descriptions must be written to highlight the demand for skills in these areas. They should also specify proficiency in tools, languages, and platforms relevant to each role.

Responding to climate change will create high-demand roles like renewable energy engineers and environmental specialists.  Job descriptions for these roles must accurately reflect the responsibilities and required competencies.

Job Descriptions and Remote and Hybrid Work

Remote and hybrid work has also impacted job descriptions. Job ads now must indicate whether the work is in-office, hybrid, or remote. Performance and deliverables are being emphasized. Soft skills like time management, leadership, communication, and adaptability are important, allowing for asynchronous collaboration. 

A significant shift is underway from focusing on traditional qualifications like educational background and job titles to emphasizing skills and relevant work experience. According to  HR Dive, job posts without degree requirements are growing faster in some industries than those requiring degrees. Job descriptions increasingly highlight needed skills and competencies to widen the talent pool and promote inclusivity. 

Current job descriptions must state the salary range for a given role. Willis Tower Watson reported that various new transparency laws generally require in-scope employers to include information on pay scales or ranges in external and internal job advertisements and postings, which will apply to new and existing positions for new hires and internal transfers.

Similarly, the National Law Review said the Salary Transparency Act is pending before the US Congress. If passed, it would amend the Fair Labor Standards Act (FLSA) and make it unlawful for an employer to fail or refuse to disclose the wage or wage range for a position in a job posting, employee opportunity, or upon hire, and at least annually.  Nine states currently have state-wide transparency laws, and more are following suit. 

Job Descriptions and Employee Benefits

In addition to salary, employee benefits are comprehensively disclosed in job postings. Forbes’ survey revealed that 40% of employers believe workers leave their jobs to find employment that offers better benefits. Publishing benefits upfront is a strategy to attract top talent by showcasing the overall value proposition, not just the salary. 

Additionally, most employees prioritize employee well-being, work-life balance, and flexibility. Disclosing benefits related to healthcare, mental health support, flexible work arrangements, and paid time off demonstrates a commitment to employee well-being. The top five benefits employees want from employers are employee-covered healthcare, life insurance, pension and retirement plans, mandatory paid time-off, and mental health assistance. Not only that, but employee benefits have also evolved to cater to the most diverse candidates. Benefits like fertility assistance, gender-affirming care, and weight management medication (if appropriate and prescribed) align with the broader push for inclusive policies that recognize and support the workforce’s diverse needs.

Job Descriptions and Employee Values

Candidates are increasingly seeking employers whose values align with their own. Indeed, it was found that 72% of job seekers say it’s hugely vital to see company details in job postings. And 10% of employers say they had to edit a job description after it was posted because the candidates they were receiving weren’t a good culture add. Most employers evaluate whether a candidate fits the workplace culture during interviews. However, conveying them earlier in a job description can attract the right people and avoid hiring mistakes.  

As such, job descriptions are now more likely to include company culture, values, and mission information. 

Gone are the days when job descriptions were only written once and used repeatedly. HR is now using data analytics to understand which aspects of job descriptions work and which do not. This includes tracking keywords that attract the most candidates and which benefits are most appealing. Analytics also monitor CTRs and application rates. Based on the findings, recruiters update job descriptions to increase the quantity and quality of applicants and reduce hiring costs and time to fill. 

The rapidly changing nature of work requires job descriptions to be more flexible and adaptable. They must be updated more frequently to reflect evolving skill requirements and industry trends.

Quotes about Job Descriptions from HR Pros

AI and Data-Driven Job Descriptions: 

“When GenAI tools like ChatGPT became widely adopted in 2023, they quickly became a go-to for JD creation—helping standardize formatting, flag redundancies, and establish a structured baseline, particularly for new or evolving roles. One of AI’s most immediate benefits was surfacing non-value-adding skills and outdated qualifications that often get recycled across industries. But the downside is that AI doesn’t understand nuance—it predicts patterns—which means the quality of a strong, well-aligned job description requires AI-literate users.”

Cynthia Patterson Founder – PeopleOps 

PeopleOps is an HR consultancy offering comprehensive solutions for small to medium-sized organizations across the US, Canada, LATAM, UK, and EU.

“AI is a powerful tool, but it’s not a one-click fix. What it can do is take the busywork out of job post writing—so talent teams can focus on clarity, messaging, and hiring the right people faster.”

Heather Fenty Director of Sales & Content Marketing – Ongig

Ongig helps organizations write more effective, inclusive, and data-driven job descriptions using AI-powered software and templates that streamline the JD creation process.

Skills-Based Hiring

“A very big challenge of skills-based hiring is breaking the deeply entrenched habit of valuing degrees and years of experience over capability. Hiring managers still often equate qualification with competence and are slow to adapt to a radical change in hiring practices. AI algorithms can analyze a candidate’s capability beyond their CV and help recruiters make more well-informed decisions.“

Lucas Botzen HR Expert & CEO – Rivermate 

Rivermate – We help companies hire remote employees anywhere in the world

Candidate-Centric Job Descriptions & Personalization

“A great job description should feel like an invitation, not a checklist highlighting career growth, company culture, and the impact of the role rather than just listing qualifications.” 

Megan Mooney Managing Partner – Vetted

Vetted – marketing, PR, and creative roles recruitment agency 

Employer Branding in Job Descriptions

“Job descriptions should provide potential new employees with a real sense of what it’s like to work for the company. Using an authentic, personalized tone that shares the company’s mission and showcases real cultural elements—not just corporate buzzwords—makes a job description far more engaging.“

Denise Chaffin CEO and Head of Talent Attraction of Top Source Talent

Top Source Talent · specializes in delivering tailored recruitment solutions that empower businesses and government organizations to thrive. From Staff Augmentation and Recruitment as a Service (RaaS) to Contingent Workforce solutions and Talent Branding, we’re here to connect you with the exceptional talent you need to achieve your goals

AI and Eliminating Bias and Making Job Descriptions More Precise 

“I’ve seen firsthand how job descriptions can unintentionally exclude qualified candidates just because of the way they’re written. AI is already changing that, and I expect it to completely transform how companies create job postings. Instead of relying on vague, outdated templates, AI can analyze successful hires, suggest more inclusive language, and tailor job descriptions to attract the right talent.”

Ed Hones, Attorney At Law, 

Hones Law Employment Lawyers PLLC

Conclusion & Key Takeaways 

Modern job descriptions are more than just a list of duties and responsibilities. They’ve become essential to attracting people and building a strong employer brand. Changes in technology bring this shift, people’s needs and expectations, and the job market and growing commitment to diversity, equity, and inclusion. 

To stay ahead: 

  • Adaptability is important. Companies need to adapt or be left behind. They must learn to adjust job descriptions and hiring strategies to stay competitive. Candidates now prefer organizations that offer flexibility and room for growth.
  • Technology plays a significant role. AI and automation have radically changed how job descriptions are written, analyzed, and optimized to reach and hire top talent. 
  • Human oversight remains essential. While technology has sped up
  •  When creating job descriptions, it is still vital for humans to ensure job posts are fair, accurate, and aligned with the company’s unique culture. 
  • Focus on candidate experience. Regular review and updates of job descriptions are still necessary so they remain relevant and effective. Use data to see what’s working and what’s not and adjust accordingly. 
  • Continuous improvement is key. In the end, job descriptions are just the beginning of attracting candidates. Providing a positive candidate experience is the key to hiring the right people. 

Learning the latest trends and best practices can help organizations craft compelling job descriptions that attract and retain the right people to help build a thriving and diverse workforce. Request a demo of Ongig to learn how we can help!

by in Job Descriptions