Skills Architecture is the key to SBO – and AI is the tech enabler

Talent acquisition specialists are continuously challenged to match candidates with the right skills to positions that feed evolving business needs. Technology and data are the one-two punch that empowers HRs to do so effectively.

Skills Architecture: Building the SBO Foundation

A comprehensive skills architecture helps HR leaders start the process with a clear understanding of what skills are already within their talent pool and where the skills gaps lie so they can target the right candidates more quickly. 

As such, skills architecture acts as the blueprint that defines and structures the skills within an organization, unifying skills language and moving beyond traditional job descriptions to establish an agreed-upon nomenclature. It’s the foundation on which a centralized Skills-Based Organization is built, pulling together skills data across teams to form a larger, more strategically malleable view.

“We’ve always historically said that this system doesn’t talk to this system, and this system doesn’t talk to this system, and the spaghetti plate of systems is what disables us from getting data or from making informed decisions that are embedded and rooted in true data and analytics,” says Sadia Ayaz, VP of Talent Management for Veolia. “Here we are today, capable of doing that. AI can take all of that unstructured data and make sense of it.” 

AI: The SBO Tech Enabler

AI’s machine learning algorithms and expedited data analytics are the technological backbone of a sophisticated skills architecture. This is due to its ability to: 

  • Ingest vast datasets to identify both existing and emerging skills within an organization 
  • Detect patterns and trends, allowing HRs to stay ahead of critical skill gaps or areas that require upskilling
  • Reveal hidden talent within an existing workforce, uncovering internal job candidates for consideration

Beyond talent acquisition, AI-driven technologies also fortify talent management strategies in a Skills Based Organization. Through personalized learning paths and recommendations, AI enables employees to acquire new skills in alignment with organizational goals, while also benefiting from individualized professional development. 

By harnessing the power of AI to construct a detailed and dynamic skills architecture, and engaging AI as the tech enabler for a successful Skills-Based Organization, HRs can hire and retain the right talent to fuel an SBO workforce model. Synergy between skills architecture and AI is the cornerstone of shaping the future of talent acquisition and organizational success.

Learn more about the power of’s Talent Intelligence platform here.

Mastering Hiring Challenges: How AI Levels the Field for Companies of All Sizes

Large enterprises and smaller organizations have similar challenges when it comes to hiring: Finding the right people for best-fit positions quickly, accurately and efficiently.

This at a time when 53% of in-house recruiting pros predict their recruiting budget will decrease or stay flat this year.

Fortunately, the emergence of AI-driven talent intelligence platforms has leveled the playing field, providing companies of every size with powerful tools to attract, hire, and retain top talent with the skills needed for success. 

The AI Advantage

A December 2023 report from Gartner names technology as the No. 1 investment area for HR leaders–for the third year in a row. The reason? HR increasingly relies on technology to meet a growing list of business demands, including fulfilling employee experience needs, enabling talent agility and continuing HR tech transformation.2

AI-driven talent intelligence platforms act as force multipliers, by automating time-consuming tasks, enabling the agility needed for companies to achieve more with fewer talent resources. 

Data insights generated by AI can also empower companies to target their efforts more precisely, ensuring that every investment in talent pays off in the quest for sustainable growth and competitiveness in the marketplace.

AI-driven platforms provide an advantage by: 

  • Analyzing vast amounts of data at lightning speed, providing actionable insights to help HRs make informed hiring decisions
  • Streamlining the sourcing and screening process, reducing time-to-hire and ensuring HRs can compete effectively for top talent
  • Personalizing internal mobility opportunities, using skills data to predict potential career pathing options for employees.

AI-driven automation frees up HR professionals to focus on larger strategic initiatives; and just as importantly, to spend more time on the face-to-face, human-centric aspects of the job. is a Talent Intelligence Platform designed to help enterprises hire, retain, and develop their workforce, intelligently. Leveraging Responsible AI and the industry’s largest skills taxonomy, enterprises unlock talent insights and optimize their workforce effectively to hire the right people, keep them longer and cultivate a successful skills-based organization. fuels Talent Acquisition, Talent Management and Skills Architecture all in one, data-driven solution. To see it in action, request a demo.

SBO moves from theory to practice; AI matures as the tech enabler

As AI-driven HR technology advances, and as Skills-Based Organizations move from strategy to execution, the SBO workforce model is primed to mature in 2024. 

First, the technology.

Generative AI was the tech buzz of 2023, spotlighting its almost unlimited potential to automate tasks and streamline business processes. As such, AI has quickly become vital to the Skills-Based Organization workforce model; specifically in its ability to screen hundreds of resumes at lightning speed and to pull skills information from resumes, job descriptions, and any labor related content.’s Talent Intelligence Platform which was built on the next generation AI from the ground up, offers the Skills Architecture Module as the foundational element for managing the workforce and understanding the current organizational skills state, benchmarking it against the skills required in the industry and recommending which top skills to adopt and enhance, allowing significantly greater agility in acquiring, developing and deploying talent. 

Organizations enamored with the idea of AI for AI’s sake, however, can find themselves with more applications than are needed to address their specific needs, with the additional costs that come with them. In 2024, HR leaders will continue to evolve into more tech savvy professionals, collaborating with their counterparts to first identify problems to solve, and then carefully choose platforms that offer the right solutions to talent acquisition and talent management challenges.

Then, the data.

With the best technological solutions in place, HR leaders are on the right path to solving business problems. Ultimately, though, the goal is reached with data.

“We need to think less about platforms and more about data,” says Dr. Sandra Laughlin, Chief Learning Scientist and Global Head of Talent Enablement & Transformation for EPAM Systems. “As new tools are coming out, new and better data sources are revealed. Generative AI can offer feedback on things that are difficult to observe and coach.” 

To fuel efficient skill-based talent acquisition efforts, for example, AI-driven data insights enable precise candidate matching based on exact skills and attributes required for specific roles. Skills-focused data–and the lack of demographic and other potentially biased data–supports diverse talent pools and an inclusive pipeline.

“The big difference [between the types of AI companies] is that a great AI company is a data company. They get a lot of data, they know what the data means, they spend a lot of time making sense of the data,” says analyst Josh Bersin of The Josh Bersin Company. “They use the data in your company matched against (exterior) data so that the data in your company can be classified and used in a more and more intelligent way.” was honored to be recognized as one of the “built on AI” type of  companies, based on billions of labor market data points, with accurate and automated skills detection and assessment, enabling in-depth skills analysis and forecasts to inform and improve strategic workforce planning efforts, increasing quality of hire when used to match internal and external candidates to open positions, and empowering reskilling and upskilling initiatives to improve learning and career path recommendations.

Learn more about the power of’s Talent Intelligence Platform here.

Webinar: and Citi Global Insights discuss how AI empowers HRs (Part 2 of 2) Co-founder and COO Isabelle Bichler-Eliasaf was recently invited to speak with Rob Garlick and Wenyan Fei from Citi Global Insights for a webinar entitled “Are Talent Intelligent Platforms the Solution to Reskilling and Upskilling?” 

Below is the second of a two-part blog series highlighting excerpts from their conversation. You can also view a recording of the full session here.

Isabelle Bichler Eliasaf, Rob Garlick, Wenyan Fei

You mentioned that represents fifth-generation AI. Can you share with us some unique features enabled by this latest generation of AI and what differentiates your platform versus other providers?

Yes, for sure. It’s really honing in on the skills taxonomies we’re creating; built one of the biggest data assets that exists today. We’re bringing a holistic solution from hire to retire, but the first thing you need to do is start with the skills architecture model. It uses the robustness of skills taxonomies to see details and skills, quickly analyzing all the roles of an organization. We’re providing a complete, dynamic catalog to our customer so they can have all their roles analyzed by skills–technical skills, soft skills, hard skills, and so forth. They have an understanding of the skills that are in demand, emerging skills, those that are declining, etc. This is the first step; really building the foundation in order to add on the next floor which is going to be talent acquisition or talent management and so forth. 

What we found is that a lot of organizations don’t do all that; the problem is that they operate in silos, without a unified skills language. They don’t share the same philosophy and the same strategy across teams. But cross-functional strategy should be shared because they’re going to use the same foundation of skills, the same framework. So what we’re doing at this stage is consolidating and synchronizing all teams in the same language. We’re taking the LMS skills framework and adapting it to the HCM and all the others used in an organization. That’s the first step, and now with that accurate, granular, robust skills data, I can inform talent acquisition; I can quickly create a job description based on the skills that I’ve analyzed for that role. Then I’m able to analyze the skills of your people; I can generate a heat map to understand what skills and organizational capabilities you have, and the skills gaps that represent weaknesses in specific departments. The skills data is also going to serve for learning and development to understand what the top skills are, and what the emerging skills are to fill skills gaps.

You say you’re a technology company built on data. Can you walk us through the kind of data that you ingest and how you train your model? It must be a huge amount to get to the point where you need to be in order to add value to people. Does this just get better and better as you are able to train it?

Exactly. It’s learning constantly. And the more data you collect, the more accurate you get so you can generate those predictions. What we’ve done throughout our first two years of inception is build a database by collecting from job boards, Indeed, all those different job boards, job descriptions, and so forth. Just on LinkedIn, you have 400 million active users that you can learn from; what career pathways they’ve pursued, and what skills they have for their position. We ingest all of this, plus pre-built taxonomies from Europe and Canada, and we continue to increase with market data. You can add even more from sites like Udemy; what are the learning trends, and what topics are in demand? All of this together feeds into one data asset. That is really integrated intelligence because we integrate with HCMs and older systems of record, not replacing them but just making them smarter with data. 

People are fearful about data privacy, algorithmic bias, bias in hiring, etc. How do we tackle this as a society? Is AI part of the solution or part of the problem? How are you guys doing that at in terms of responsible AI?

This is why I’m very passionate about responsible AI; because this is a problem and solution. AI is amazing. It’s like saying you’re not going to use electricity because there are risks. Of course you will, but you need to take some precautions. For us at, GDPR is what we’re embedding so that we’re compliant with the most stringent requirements. We’re also making sure all data we have is used with the consent of candidates; we know this because they chose to put their data online with all the information and informative disclosures involved. 

There’s also new legislation around telling you that you’re going to be assessed by a machine and allowing you to opt out: Local Law 144 here in New York City. I actually submitted public comments on the law along with others and one thing they hadn’t figured out is, if I’m a candidate opting out, am I able to be fully assessed? Am I actually discriminated against because I’m choosing that AI not be used? We had an amazing conference with Commissioner Keith Sonderling of the Equal Employment Opportunity and we were talking about that; his take on it is that the law didn’t change anything that wasn’t already in place. It didn’t do anything new. It’s still saying you shouldn’t discriminate based on gender, ethnicity, age, and all those different parameters–there’s another entity performing that assessment. I agree with him, but I think that the fear of AI makes us more aware and want to limit it. So now we need to balance between innovation and regulation.


Webinar: and Citi Global Insights discuss how AI empowers HRs (Part 1 of 2) Co-founder and COO Isabelle Bichler-Eliasaf was recently invited to speak with Rob Garlick and Wenyan Fei from Citi Global Insights for a webinar entitled “Are Talent Intelligent Platforms the Solution to Reskilling and Upskilling?” 

Below is the first of a two-part blog series highlighting excerpts from their conversation. You can also view a recording of the full session here.

Isabelle Bichler-Eliasaf, Rob Garlick, Wenyan Fei

What is a Talent Intelligence Platform? What is the technology that’s been transformed by AI to make upskilling possible?

Talent intelligence is really one of the biggest successes when it comes to AI for HR use cases. Talent Intelligence Platforms bring together all the relevant internal and external data sources into one useful tool to create a holistic view of a company that empowers decisions about talent or workforce planning. It’s really a merger between people analytics, market insights, market trends and workforce planning. 

If you’re looking at the system of records–HCM or ATS–AI makes them smarter. Why? Because it answers the most critical questions of recruiters: Who should they hire? What are the criteria based on skills, but not just basic skills? What is the experience required? This informs the recruiter as to who they’re looking for. With AI, they can take an omnichannel approach to sourcing candidates from two different pipelines: External sources, plus internal talent that may warrant a fresh look based on skills that are in demand now or that are emerging. HRs are able to hire much more efficiently by broadening the talent pipeline and looking at potential, not just unrelated qualifications and job titles. This is how talent intelligence is informing and empowering those HCM and ATS HR flows.

It’s my understanding that this is the same transformation technology that lies behind the large language models. If you don’t mind, maybe just contrast today’s tech with some of the legacy HR systems that create challenges for companies in terms of being able to extract data. 

What really has enabled us to bring increased efficiencies for retention and faster hiring and so forth are those models, of course, plus there’s been exponential growth–a leapfrog really–in AI This is because there’s much more data to train our models upon. In just the last two years, 90% of the current data was generated; that’s how big the computing power is now. It’s also been cheaper so we’re able to train better and more efficiently.

At the most recent HR tech conference in Las Vegas, analyst Josh Bersin recognized our work and categorized companies in AI into three types of companies. There are companies that are now adding AI into their flows, like adding a chatbot. Then there are companies such as SAP Oracle that have a lot of transactional data about candidates and employees and are now running some models to predict what would be a good fit, or what would be the next course an employee should take. Then there are the new types of companies such as ours that are built from the start on AI. We are the companies using neural networks. is using 1.8 billion data points and counting from all different sources to support HR flows; so it’s not just going to give an understanding of what you have in your company but also the ability to benchmark that against the market.

Webinar Recording: Unlocking the Power of AI in HR

A recent webinar sponsored by Crain’s New York Business and NYU School of Professional Studies explored the advancements in AI in HR, including a discussion on why it’s critical for organizations to venture into this technological realm responsibly.

Moderated by Dr. Anna Tavis, Clinical Professor & Chair of the Human Capital Management Department of NYU’s School of Professional Studies, the conversation featured Co-founder and COO Isabelle Bichler-Eliasaf along with with Sadia Ayaz, VP of Talent Management for Veolia, and Heidi Ramirez Perloff, SVP of Global HR Strategic Initiatives and Delivery Solutions for the Estée Lauder Companies. The full recording is below.




How Generative AI Transforms Talent Intelligence

For businesses competing in today’s fast-paced landscape, leading the market means having the right people with the right skills in the right roles. Generative AI has risen to the top of this conversation as a way to more efficiently and accurately reach that goal. 

But what is Generative AI, and how can it revolutionize talent intelligence? If you’re a CHRO, technical innovation leader, or workforce strategist looking to harness the power of AI for HR, here’s what you need to know.

What is Generative AI?

Generative AI is a subset of artificial intelligence that focuses on creating new, original content, rather than simply analyzing or processing existing data. Using vast datasets to learn patterns, relationships, and styles, generative AI technology is able to generate human-like content, whether it’s text, images, or even music.

Generative AI in Hiring

Finding the right talent has always been a critical challenge for HR professionals. When it comes to sourcing, screening and securing the right candidates with the skills needed for business success, generative AI can assist in multiple ways:

  • Skills Extraction and Matching: By analyzing resumes and job descriptions with unprecedented speed and accuracy, Generative AI solutions can quickly identify candidates who best match the required skills and qualifications for an open role. This means talent acquisition specialists can cut time and cost to hire by zeroing in on the right people to move through the hiring process.
  • Candidate Engagement: Chatbots powered by Generative AI can interact with candidates, answer questions, and schedule interviews, ensuring a seamless and efficient recruitment process while freeing HR leaders up to focus on more interpersonal elements of the hiring process.
  • Diversity and Inclusion: Generative AI can support a fair and inclusive hiring process by focusing solely on qualifications and skills, eliminating demographic and other information that can introduce unintended bias.

Generative AI and Internal Mobility

Fostering internal mobility is essential for employee growth and retention. In fact, it’s been shown that employees with a clear view toward future opportunities are more likely to stay with an organization, making proactive upskilling channels a business imperative. Generative AI can assist by:

  • Skills Mapping: Generative AI can help identify employees’ skills, capabilities and interests in order to more accurately suggest potential career paths within the organization.
  • Learning Recommendations: When opportunities are identified in the form of open roles, gigs or projects, Generative AI can produce relevant upskilling pathways to help them acquire the new skills required to pursue them.
  • Succession Planning: By analyzing employee data around skills, capabilities and aspirations, Generative AI can aid in identifying high-potential employees and preparing them for leadership positions.

Generative AI and Skills-Based Organizations

The traditional job-centric approach to workforce planning is quickly becoming outdated, as more companies shift to a skills-focused model. Generative AI supports this transition through:

  • Skills Gap Analysis: By powering a data-driven skills architecture, Generative AI can analyze the skills already present in a workforce, those needed in the future, and how to bridge the gap between the two with employee upskilling or reskilling recommendations.
  • Skills Tagging: Generative AI can automatically tag skills to employees based on their experiences and achievements, creating a comprehensive, continuously updated skills inventory.
  • Adaptive Training: Personalized training plans can be fueled by Generative AI, ensuring employees are continually developing the skills necessary to excel in their current and future roles.

Considerations for CHROs

While Generative AI holds immense potential to elevate HR functions, there are some critical considerations for CHROs when evaluating AI platforms for their HR technology stack:

  • Data Privacy: Ensure that data privacy regulations are followed rigorously, including the safeguarding of sensitive employee and candidate information.
  • Ethical Use: Develop Responsible AI guidelines to comply with regulations and prevent bias, discrimination, or misuse of technology in hiring decisions.
  • Integration: Ensure the AI system can seamlessly integrate with your existing HR software to maximize its efficiency and avoid the delays of a rip-and-replace solution.
  • Training and Support: Invest in staff training to help HR teams understand and effectively use Generative AI tools as well as welcome user feedback.
  • Continuous Improvement: Keep in mind that AI is not a static, set-it-and-forget-it solution. Technology solutions require regular updates and fine-tuning to remain effective.

By automating processes, reducing biases, and focusing on skills, Generative AI enables HR professionals to make more informed decisions and create a workforce ready for the challenges of the future. As a CHRO or HR leader, embracing Generative AI can lead to a more agile, efficient, and innovative HR function, giving your organization a competitive edge in the talent market. is a Talent Intelligence Platform designed to help enterprises hire, retain, and develop their workforce, intelligently. Leveraging Responsible AI and the industry’s largest skills taxonomy, enterprises unlock talent insights and optimize their workforce effectively to hire the right people, keep them longer and cultivate a successful skills-based organization. fuels Talent Acquisition, Talent Management and Skills Architecture all in one, data-driven solution. To see it in action, request a demo.

AI’s Role in Revolutionizing Talent Acquisition and Retention

This article originally appeared in Forbes.

As corporations grapple with the challenging task of attracting and retaining highly skilled talent in an intensely competitive market, AI-assisted HR tools are creating a new paradigm. Of course, these innovations can create potential ethical issues during the recruitment and internal mobility processes. Here are things that HR leaders must consider when weighing the pros and cons of implementing these technologies.

AI In Talent Acquisition

Traditional recruitment methods, often laborious and time-consuming, require HR leaders to sift through hundreds of résumés for every open position. These processes can potentially cost thousands of dollars if a position remains unfilled, even reaching six figures when considering senior or technical roles. Furthermore, hastily rushing the recruitment process can lead to improper fitting, resulting in higher turnover rates. With AI-powered platforms, HR leaders can streamline their processes by ensuring a more accurate selection of candidates and accelerating the hiring timeline.

Algorithms can process vast amounts of data swiftly, eliminating the painstaking manual review of résumés. By leveraging natural language processing and machine learning, AI-powered tools analyze and use skills extraction to identify the most relevant skills for a given role. These systems go beyond simple keyword matching; they can apply context to infer skills that aren’t explicitly mentioned in résumés. Semantic skills extraction reduces missed opportunities that occur using only keyword search, creating a selection process that’s more comprehensive for recruiters and more fair to candidates.

At a time when enterprises are rapidly transitioning to skills-based models, introducing an AI-powered platform can help HR leaders quickly assess and rank internal and external candidates based on their skills and capabilities. This not only saves time by revealing best-fit candidates faster but also goes even further by enabling role matching.

Finally, recruitment professionals can use AI to enhance the candidate experience with personalized interactions. Tools like chatbots and virtual assistants provide real-time updates on application status and offer tailored job recommendations, reducing candidate effort and time.

AI In Employee Retention

High employee turnover can significantly impact a company’s bottom line. A survey showed that 63% of employees changing jobs cited lack of advancement opportunities as a main factor. In this context, AI can help HR leaders understand their employees’ needs and aspirations better, then use that knowledge to enhance their journey within the organization.

With AI platforms, talent management teams can analyze large volumes of data to gain insights into factors contributing to employee attrition, such as job satisfaction, work-life balance and career growth opportunities. This personalized insight, regardless of workforce size, allows HR professionals to identify and address at-risk employees’ concerns proactively. For example, an employee who’s remained in one position for a long time may have unrealized potential to succeed on another team in the company. A proactive HR leader will capitalize on AI-driven insights to spot that opportunity and present it to the employee, offering a new challenge and possibly keeping them from looking elsewhere.

Performance management and feedback systems receive support from AI technologies that provide objective evaluations of employee performance. This can help HR leaders and people managers provide personalized coaching and development plans, enhancing overall job satisfaction for employees.

Ethical Concerns And Potential Biases

While AI technology offers numerous advantages, it does raise ethical concerns that HR leaders should stay aware of. These systems can unintentionally perpetuate biases and stereotypes present in historical data. In 2018, Amazon came under fire when it was revealed that an AI-based recruitment system discriminated against women when hiring for technical roles. The platform sought top candidates by positions on their résumés, and considering women had held only about 24% of STEM jobs in the U.S., the majority of résumés fed into the system were from men. As a result, the algorithm developed male preference and gradually deprioritized résumés from women.

Clearly, unintended bias like this can have devastating consequences for an enterprise on several fronts beyond skewed workforce growth. The ripples can be felt throughout brand reputation, customer backlash, candidate trust and more.

Such dangers have prompted an increase in regulation around responsible AI, including Local Law 144 in New York City. The new law requires independent audits of what it categorizes as automated employment decision tools (AEDT) used in hiring within, or from within, New York City—an expansive reach, given the city is a global business hub. While it can be argued that AI-driven platforms don’t automate decisions but rather inform humans’ decision-making, the systems present within an organization’s HR tech stack are included in the regulations.

To remain compliant, HR leaders must ensure diverse and representative training data for any AI systems they implement. Additionally, systems should comply with the five pillars of responsible AI: explainability and interpretability; bias mitigation and fairness algorithms; data robustness and granularity; data quality and rights; and accountability through regular audits and monitoring of the AI’s decision-making process.

HR innovators looking to employ responsible AI-based systems will benefit from first researching available platforms and asking potential vendors the important questions: Is your solution transparent? Can you easily explain how its algorithms work? What bias mitigation is in place? What client onboarding experience can we expect and what training is included?

AI Is Here To Stay

Artificial intelligence is undeniably transforming the world of HR, especially in talent acquisition and retention. The benefits of AI, like streamlined recruitment processes and improved employee engagement and satisfaction, are significant for organizations. By employing ethical, responsible AI-driven systems, enterprises can future-proof their workforce and reap immense benefits.

Announcing the Partnership Program

NYC / August 9, 2023 –, a leading AI-driven Talent Intelligence Platform, has announced the launch of an exclusive Partner Program available to consulting and recruiting firms. The company describes its new offering as a way for exclusive partnership with premier firms to bring their prospects and clients into the future of work with an AI-fueled, data-driven understanding of what they need to become a Skills-Based Organization.

The company uses a data driven, Responsible AI-driven operating model using billions of data points to help enterprises achieve a Skills-Based modality. 

“Becoming a Skills-Based Organization is the key to success for today’s enterprise HR leaders, but many don’t know where to start. When they ask a consultant for guidance on transforming to an SBO model they may get information, but not the tools they need to get started,” says Co-founder and COO Isabelle Bichler-Eliasaf. “We provide those tools, along with the expertise to optimize them for success.”

To accomplish this, centralizes data to create an adherent skills strategy to unify and standardize data sets to remove silos within HR functionalities.  This unified data set, paired with the company’s Responsible AI, equips HR’s to move faster and with more agility and efficiency. The platform continuously updates to eliminate future skills gaps within the organization where it is already implemented. 

Consultants in the Partner Program will have access to the talent intelligence platform’s Skills Architecture module to generate a skills-map of an enterprise client’s workforce, including unified skills language and agreed-upon job architecture. With better visibility into their employees’ strengths and skill gaps, HR leaders can spot hidden talent, reveal internal mobility opportunities and deploy talent efficiently during times of rapid change.

“Our platform provides HRs with a comprehensive understanding of their workforce and the right data to align with organizational goals,” says Bichler-Eliasaf. “Once our partner consultants provide their enterprise clients with a comprehensive skills catalog of the core competencies, technical proficiencies, and soft skills needed for each role in their organization, they can begin to strategize an SBO operating model.” is a Talent Intelligence Platform designed to help enterprises hire, retain, and develop their workforce, intelligently. Leveraging Responsible AI and the industry’s largest skills taxonomy, enterprises unlock talent insights and optimize their workforce effectively to hire the right people, keep them longer and cultivate a successful skills-based organization. fuels Talent Acquisition, Talent Management and Skills Architecture all in one, data-driven solution.

What is a Skills-Based Organization?

One of the most significant shifts taking place within the realm of HR and talent management is the transition to a skills-based organization. Rather than focusing solely on job titles and traditional hierarchies, organizations are recognizing the importance of assessing and leveraging employees’ skills and capabilities to better drive success and foster innovation. But what exactly does it mean to transform into a skills-based organization? Why is it seemingly crucial for HR professionals to lead this paradigm shift?

Understanding the Skills-Based Organization

A skills-based organization places skill sets and capabilities at the core of its talent management strategy. Instead of relying on job titles and formal qualifications, enterprises instead shift their focus to identifying, developing, and utilizing the skills their employees possess so as to effectively match individuals to best-fit projects, initiatives, and roles.

What are the benefits of becoming an SBO?

  • Agility and Adaptability. In today’s rapidly changing business environment, enterprises need to be nimble and adaptable. By focusing on skills, companies can quickly respond to market shifts and reconfigure their teams as required. Skills-based organizations have the advantage of assembling cross-functional teams with complementary skill sets, empowering them to tackle new challenges and seize opportunities efficiently.
  • Talent Optimization. Traditional hiring practices often rely on predefined roles, limiting the potential of employees who may possess valuable skills outside their designated functions. A skills-based approach allows organizations to tap into the full potential of their workforce by unlocking hidden talents and engaging individuals to contribute in areas where they excel.
  • Employee Engagement and Growth. Engaged employees are more likely to be motivated, productive, and loyal to their organizations. In a skills-based organization, workers have opportunities to develop and showcase their skills, leading to increased job satisfaction and a sense of fulfillment. By promoting skill development and growth, organizations can foster a culture of continuous learning, which modern professionals highly value.
  • Diversity and Inclusion. Traditional job descriptions can use terminology that inadvertently creates barriers to entry. A skills-based approach promotes inclusivity by focusing on what an individual can do rather than where they come from or what their previous job title might have been. By removing biases associated with traditional hiring practices, enterprises can build diverse and dynamic teams.

In our next post, we’ll go over the key steps involved in transitioning to a Skills-Based Organization. is a Talent Intelligence Platform designed to help enterprises hire, retain, and develop their workforce, intelligently. Leveraging Responsible AI and the industry’s largest skills taxonomy, enterprises unlock talent insights and optimize their workforce effectively to lower attrition, win the war for talent and the great resignation. fuels Talent Acquisition, Talent Management and Skills Architecture, all in one, data-driven solution. To see it in action, request a demo