(S)killing it: how workforce development and learning will power our AI future

Skills assessment and skills development market map, by Emerge Education.

We’re building our annual list of the top emerging edtech companies in workforce development for 2024 with our Workforce Development board, chaired by Donald H Taylor. As we do, we’re diving into the trends and opportunities for innovation along each step of the workforce development journey, for individuals and for organisations → from job discovery, pre-hire assessment and interviews to onboarding, coaching and mentoring, talent management and reskilling for the future of work.

In this fourth article, we’ll explore two vital and interconnected agendas: skills development and skills assessment.

This is, of course, a massive category with many complex subcategories and so this article offers merely a snapshot 📸 of the current state of play. Please share your thoughts 💭 to enrich and expand the conversation 💬 in the comments, and take a look at our recommendations for deep dives 🧐 into different issues at the end.

The learner journey in workforce development, by Emerge Education.

Read on for:

• Challenges, trends and opportunities, including our predictions for the transformative impact of genAI
• Views from sector experts, plus tips for founders
• A mini-market map of key players and top emerging startups in this space

Keywords: skills, training, learning, workforce development, L&D, upskilling, skills development, skills assessment, performance reviews, performance management, microcredentials

💡 Why it matters

We’ve all read the statistics. Our current labour education pace forecasts an $8.5tn skills gap globally by 2030. Since 2015, skill sets for jobs have changed by around 25%. By 2028, employers estimate that 44% of workers’ skills will be disrupted, while an EdX survey last year found that 49% of the skills that exist in their workforce today ‘won’t be relevant in 2025’. Let’s not even get started on the impact of generative AI.

So, everybody knows this is big. The large majority of companies worldwide (87%) are aware that they either already have skills gaps or expect to within a few years, according to McKinsey, which has reported extensively on the importance of building skills-first organisations. A recent pulse check suggests that employers think this situation is actually getting worse.

C-suite beware: Forbes recently called skills gaps ‘the biggest threat to your future’.

🏈 State of play

• There is strong awareness of this situation across all levels of organisations. Of L&D professionals, 64% said that reskilling the current workforce to fill skills gaps is a priority now. Employees themselves are similarly anxious about the widening skills gap, with 46% of those surveyed in 2021 believing their current skill set would have become irrelevant by this year.
• In this context, it’s no surprise to learn that L&D’s voice is growing. The percentage of learning professionals who say they ‘have a seat at the table’ has grown five points in just two years, to 58%.
• Workers want to reskill: 77% are ready to learn new skills or completely retrain. It’s a shame, therefore, that overall only 34% of workers feel supported by their organisation’s skill development opportunities.
• What’s more, these opportunities are not evenly distributed: 46% of people with postgraduate degrees say their employer gives them opportunities to improve their digital skills, but just 28% of people with secondary education say the same. Graduates are four times more likely to participate in job-related training than those with no qualifications, and only around 1% of enterprise technology spend goes to frontline workers.
• And this is not a one-time thing. According to a recent report, 82% of employees and 62% of HR directors said they believe that workers will need to reskill or upskill at least once a year to maintain a competitive advantage in a global job market.
• So far, tech has focused heavily on identifying skills, and many of these functionalities — creating skills frameworks, career pathing, personalised learning recommendations, etc — aren’t new. What’s different now is the sheer enabling potential of AI: providers are elevating their offerings in ways that weren’t possible (at least with such scale, speed and ease) until recently. We’re also seeing more and more solutions focused on skills verification & analysis — enabling organisations to identify future skill needs, then structure, verify and act on that information.

“When it comes to upskilling and reskilling — or what I prefer to call ‘rightskilling’ — all too often learning professionals confound content consumption with skill building. But people do not build skills just by reading an article or watching a video, for instance. It requires a fulsome learning experience that includes things like opportunities for practice and application, coaching, mentoring and social/cohort learning. This of course is hard to do at scale and pace without spending a fortune, but thankfully the technology is evolving rapidly to make this possible.

Even if organisations have a perfect reskilling strategy, they often fail to communicate to employees WHY they should dedicate their limited time and resources to it. Will it result in a pay rise, a promotion or at least a lateral career move that ensures they will stay relevant and not be made redundant? People also need to understand what skills they should focus on developing. A spray-and-pray, “If you build it they will come” approach simply does not work, and your learning platform will end up becoming a dinosaur’s graveyard where learning goes to die.”

Amanda Nolen, learning and skills strategist, and Emerge VP

• Some more numbers… Organisations are spending $430bn on enterprise software, while spending less than $20bn on tech-enabled workforce development solutions, in a much larger $240bn market dominated by often inadequate in-house training, with many external small-scale face-to-face providers. Deloitte conducted a survey of more than 1,200 professionals and organisations, and found that 63% have embedded skills-related technology in core HR information systems and 49% are using standalone AI-driven skills technologies.
• It is non-controversial that promoting internally can be less costly than hiring new talent, which can cost as much as 6-times more. Josh Bersin lays out the economics: the cost of recruiting a mid-career software engineer (who earns $150,000–200,000 per year) can be $30,000 or more, including recruitment fees, advertising and recruiting technology. This new hire also requires onboarding and has a potential turnover two to three times higher than an internal recruit. By contrast, the cost to train and reskill an internal employee may be $20,000 or less, saving as much as $116,000 per person over three years. While the time to fill the role could be in favour of hiring, the internal hire has a lower likelihood of churn, is likely to perform better sooner and require a lower salary.
• Governments are increasingly acknowledging and promoting the importance of upskilling and reskilling. At least 60 countries worldwide have some kind of training levy, where government mandates employers to allocate money to employee training. This represents a real opportunity for training providers as large sums remain left on the table. Research by the World Economic Forum, BCG and Burning Glass shows that employers alone can reskill 25% of employees and with government support 77% of employees with a positive cost-benefit balance.

🚨 Challenges

“Organisations now face the challenge of hiring and promoting employees based on skills. It’s an indisputable matter of fairness. Many say they want to do it, but very few know how to do it. Some products have emerged to help them, but changing habits takes time. Replace any degree requirements with a list of specific skills you expect from your new hire. Do not filter based on degrees, but on skills.”

Mathieu Nebra, cofounder at OpenClassrooms and Emerge VP

• You can’t improve what you can’t measure. Having a more robust way to better understand existing workforce skills is still the number one ask we hear from L&D and corporate leaders. Yet it’s the foundational block and biggest gap in the workforce development chain. Self-assessment and manager reviews are an important component, but they come with limitations and blind spots. It’s challenging to get a clear view of the skills you have in your talent pool (both your employee workforce and candidate pipeline), as people move roles, learn new things and change their preferences.
• Most skills assessments are one-offs and focused on new talent hiring. Testing today is largely non-granular, irregular and intrusive. Think of performance reviews, poor multiple choice tests or long certification tests you need to study months and years for (eg CFA, ACCA). This space is ripe for disruption by AI.
• Corporations are not built to be great training institutions. While 70% of L&D spend is on in-house solutions, L&D teams don’t have the capacity (there is one L&D FTE per 350 employee FTEs), authority, skills or resources to create meaningful, ongoing learning initiatives over and above one-off training and compliance exercises.
• Proving impact remains the holy grail. Marketers improve products through constantly running A/B tests. C-suite leaders use clear metrics to measure business performance. Workforce development solutions should also empower customers to define the tangible granular outcomes they are hoping to achieve. The cause and effect equation will never be perfect, but the more smart experiments and quick feedback loops companies can run, the faster we can elevate the importance of learning and the influence of L&D leaders. Yet still, few large-scale L&D initiatives advance to the measurement stage — just 4%, according to the 2024 LinkedIn Workplace Learning report. The most common ways that L&D tracks business impact remain performance reviews (36%), employee productivity (34%) and employee retention (31%). Just 30% of L&D professionals measure specific business impacts (deals closed, customer satisfaction) tied to learning, despite the fact that these are the metrics that resonate most with C-suite executives. Closing skills gaps (27%) and new skills per learner (16%) bring up the rear, indicating the difficulty of translating macro labour market imperatives into specific organisational contexts.
• Solutions have focused on core HR infrastructure and content, driven by administrative and regulatory needs, creating barriers to entry for smaller players. For decades the main solutions in the space have focused on automating and simplifying HR core functions. Huge players like SAP, Oracle and Workday have become the core engines and guardians of HR data, while players like Skillsoft and Cornerstone have owned the content and learning management infrastructure. While neither player has successfully pursued workforce development, as guardians of data they have created barriers to entry for smaller players, focused on more niche use cases, that could benefit from data integrations — skills mapping foremost among them.

🔥 Trends

• We are living in a skills economy. Organisations invest in training for three reasons: compliance, short-term performance support and long-term capability development. While these remain the drivers for investing in skills and knowledge, they are no longer the only drivers behind workforce development. As we move to a world of ‘skills-based everything’, more and more companies are using data about people (their actual and potential skills) and work (the skills actually needed to carry out a role) to make sure they can fill — and predict — skills gaps more effectively. This data relies on a common language of skills: holistic ‘skills intelligence’ to match talent to tasks effectively and efficiently.

“One of the most important priorities on every CLO’s talent agenda today is ‘future-skilling’ the workforce. We are developing people for jobs that don’t exist yet, and it’s essential to build talent that can grow with and within our organisations.”

Tamar Elkeles, Emerge VP

• Improving ease and robustness of skills measurement. There is a lot of potential to make skills assessment more robust to help managers not only understand employee starting points, but also how their skills are improving in real-time. This could be done using granular and authoritative open-source skills taxonomies and higher order micro-credentials informed by employers. They could also be backed by external sources of authority (such as universities, accreditation and examination bodies).
• Non-invasive automated assessment and evaluation. After Google and social networks, our employer is probably the organisation that knows us best, given the amount of time we spend with it and the information we give and receive. We are seeing powerful integrations with workflow tools such as Slack and Microsoft Teams that prompt ‘micro-assessments’ in the flow of work.
• Human feedback on the go. We shouldn’t have to wait until year-end review or ineffective 360 degree feedback sessions to speak to our manager and understand how we are doing. While automatic data-driven feedback has incredible potential, humans will always play a role in employee development. Alongside real-time AI powered feedback, solutions should make it easy to seek and give feedback in the flow of work.
• Platforms made explicitly for roles and competencies. Just as Pluralsight is the go-to place for developers (and commands a price premium), focused learning providers can become destinations for other specific roles and competencies. This could, for example, be tech sales, as one of the hardest to fill roles with a huge skills gap, or management skills, where US companies alone spend $15bn on training (more here from our friends at Transcend Network).
• Empowering employees to learn from one another. For specific questions and situations colleagues will often be the best teacher and source of insights and motivation, being much closer to the problem than expensive external parties. There is an impact and business case for unlocking internal skills, advice, learning content and knowledge creation from the ground up, especially in larger companies.

“As companies increasingly need to demonstrate their broader impact on the world, there will be a focus on regenerative leadership which goes beyond mere sustainability. An organisation’s success will be measured on an ability to lead and innovate in ways that regenerate and rejuvenate both the environment and society. They must ensure their business practices not only generate economic value but also foster a sustainable and thriving planet, as well as being a catalyst for change across entire industries and communities.

As a result, an importance needs to be placed on developing skills that enable people to build an understanding of the complex dynamics of modern challenges, and the leadership ability to guide organisations towards innovative, ethical and environmentally sound practices. This requires teaching a holistic view of business that recognises the interdependencies between various systems — economic, ecological and social.”

Jamie Brooker, founder at We Are Human & Kahoot!, and Emerge VP

🌍 Key players

Skills development and assessment is a huge category. Rather than aim for a comprehensiveness which is neither possible nor useful, we have chosen here to focus on the structure of the market, along with some indicative examples.

Skills assessment and skills development market map, by Emerge Education.

Each category has, for us, a core set of questions:

• UNDERSTAND & PLAN: Is the solution underpinned by data-driven insights into current and future skills needs, helping companies understand their current skills landscape — and how to get from A to B?
• TRAIN AND APPLY: Is the solution improving the relevance and applicability of the content (tailored learning providers), while increasing employee engagement and unlocking employee potential (applied collaborative platforms)?
• EVALUATE & MEASURE: Is the solution helping define and measure employee skills with greater accuracy and ease?
• MANAGE & PROMOTE: Is the solution helping individuals progress through their careers more effectively with their current employer, while supporting managers to better develop their staff?

We might think of each of box as itself operating on a set of spectrums: from synchronous (live + community) to asynchronous (on demand); from peer learning to expert led; from ‘hard’ or technical skills to ‘soft’ or human skills.

Our next piece will dig into the natural next step of this configuration: reskilling, talent management and career pathway navigators.

🔭 Who is getting ahead?

Employees now have one place to keep updated with learning, as Beekeeper links to the LMS/LXP. Leonardo Hotels can push learning via in-app campaigns groups, such as regular Learning Bites to ensure skills and knowledge are maintained, and Workflows help team members access the right information at the right time, along with access to shift schedules, payslips, onboarding, training, tasks, safety checklists, announcements and more. Self-generated content and peer learning drives users, because of the app’s ease of use and immediacy. Read the full case study here.

AstraZeneca’s operating model for learning is federated. Learning and talent development consultants, who are embedded in and report to the business, take responsibility for root cause analyses, learning interventions and impact measurement. L&D builds the technology ecosystem, ensuring practitioners have access to the right datasets and analytics tools, and shares best practice with a committee of learning leaders. This enables AstraZeneca to map wider organisational capabilities as well as respond swiftly to specific business needs as they arise on a case by case basis. Rather than lead with learning as the solution, it gets closer to the work to lead with understanding performance gaps.

AstraZeneca is increasingly thinking about learning through the lens of a skills-based talent management approach, which unpicks and redesigns an organisation in fundamental ways:

🔮 Predictions

• Assessment solutions of today are bespoke, hiring focused, subjective and big test-driven → Assessment solutions of tomorrow will be more objective, flexible and business outcome aligned. There is massive demand for scalable solutions that empower employers to understand how existing employees are objectively progressing in their upskilling and reskilling efforts and thus delivering against business outcomes. Although self-assessment and internal credentialing can be useful solutions, they lack objectivity which limits confidence for staffing decisions. Well established existing tests can be inflexible, while any assessment that does not tie results to intermediate and end business outcomes is of limited value. AI will be the gamechanger here.
• Today’s solutions define and untangle skills, while offering skill-informed content and learning pathways → Tomorrow’s solutions will show relationships between skills and roles, while providing facilitated role-aligned career pathways and transitions. Skills tech offerings are beginning to be more easily organised into skills tech ecosystems, as providers appear increasingly committed to technical integrations and data sharing. Yet it is still not crystal clear how roles relate to one another, how content X relates to content Y, nor how (or even if) content and learning pathways facilitate role progression. To demonstrate greater impact and experience greater uptake, skills taxonomies will have to show how role demands are changing and relate to one another. Training solutions will use this information to move people from A to B. This means solving problems for employees who want to move from role A (e.g. database administrator) to role B (e.g. data analyst), and for employers who have employees in group A (e.g. product designers) that need to shift to group B (e.g. product managers).
• Today employees have access to all of the content in the world → Tomorrow employers will have access to learning made for them. Large generalist content providers and AI recommendation engines mitigate problems around access and engagement. Specialised providers, however, can build advantages by fully tailoring their learning environments. The learning solutions of the future will use LLMs to train on company-specific processes and protocols which makes them feel like they are made specifically for your industry, your profession and even your company
• Learning of today is more practical and flexible → Learning of tomorrow will be more applied, immersive and inclusive. The next generation of workforce development providers will further move from learning through examples to learning by doing real tasks or simulations. While learning through exercises is a good starting point, learning from real experience and mistakes is even more motivating and powerful.

🎯 Opportunities for startups

GenAI engines of opportunity in workforce development, by Emerge Education.

In this category, we see particular opportunities for AI-driven solutions that offer:

• Expert-led functional training → Problem: Most corporate training is delivered in physical training centres by professional trainers who haven’t been on the ground in years. Solution: Deliver training online and using real world practitioners who are leaders in their roles. Additionally, create peer communities that help each other grow.
• Learning networks and communities → Problem: Masterminds one of the most valuable ways to learn, yet not really scalable. Solution: Tech that enables masterminds/other communities to form and support each other.
• Flight simulator for interpersonal skills → Problem: Practising skills in a high-stakes environment is not the best way to learn because you cannot afford to fail, so in practice it doesn’t happen. Solution: generative AI unlocks flight simulator training for complex interpersonal situations — interactive learning experiences that create safe environments in which to train for high stakes situations or interpersonal skills. This is especially exciting as this moves from chat, to voice, to XR.
• Teaching employees how to use software to enable them to be more productive → Problem: Most SaaS tools are only used in limited way by majority of their users. Solution: Includes teaching AI, no-code skills and how to use sophisticated software.
• Learning materials co-pilots → Problem: Content creation is expensive and takes a lot of time, yet is critical. It’s basically in the job description of L&D professionals. Solution: Until now, machine learning techniques were used to recommend the right pieces of pre-fabricated content to learners. Today, we are starting to use generative AI to create the right piece of content for the learner from scratch based on their needs, radically reducing the cost and improving the effectiveness of learning materials creation.
• Expert marketplaces → Problem: Hard to find answers to day to day hard business problems, in all niches. Solution: Access to niche, specific knowledge and insights from experts that you couldn’t easily or reliably find online or through ChatGPT.
• AI-powered enterprise knowledge search → Problem: Enterprises have a huge amount of internal knowledge that is hard to tap into and find. Solution: Easier ways to discover and apply information in enterprises that could either be horizontal (tech edge, e.g. multimedia) or vertical (eg finance industry, sales focused).
• AI-powered second brain → Problem: We constantly come across new information and struggle to retain it. Solution: Better capturing and processing of things you read/come across and helping you apply it in your day-to-day. One big feature of this would be AI-powered automated tagging of the things you capture.
• Frontline worker management → Problem: Frontline workers are underserved. Systems to manage them are focused on ERP, not shopfloor. Solution: Shopfloor level management systems that are used by frontline workers 24/7 to track tasks, competencies, development, safety compliance and more, leading to greater productivity, transparency and development opportunities.
• Business and sales call recordings AND Track all of our written work output and provide feedback → Problem: So much rich data is now captured on our performance yet we only get feedback based on what our managers see and one every couple of months during performance reviews. Solution: Tracks all of your calls and gives you automated feedback against a series of performance dimensions.
• Company-specific LLM for skill assessment → Problem: Tribal knowledge in companies is not systematically collected and organised to power hiring and development. Solution: Connecting all of a company’s performance, goal management and career development data to train a company-specific LLM that can power other applications/use cases like hiring, performance coaching/feedback and career progression.
• Entrepreneurial upskilling → Problem: There is a long tail of entrepreneurs and business owners (often outside tech) that have little to no support with how to run their business. Solution: Resources, programmes and guidance for this demographic.

💎 Tips for founders

🔗 Read on

• How to build a unicorn in workforce development
• How are organisations using generative AI for workforce development?
• Our deep dive reports into the future of workforce development and moving L&D to systemic and strategic impact
• Our focus on frontline workers — read overview and market analysis here, and full report here
• Part 1 in this series → How startups can drive innovation in recruitment, career navigation and pre-hire skills assessment
• Part 2 in this series → Edtech for employee engagement: how startups can support onboarding, retention and a strong learning culture
• Part 3 in this series → Can technology and AI support coaching and mentoring at scale?

Read more news, views and research from the only fund backed by the world’s leading education entrepreneurs, in Emerge Edtech Insights.

📣 Call to action

We are now building our list of the top emerging edtech companies in WD in 2024.

👇 If you have seen an exciting company in this space, please tell us in the comments 👇

Our list analyses 100s of companies operating worldwide, using public and private data — it is crowdsourced, and voted on by our Workforce Development edtech action group, led by Donald H. Taylor.

Please share companies you think we should consider in comments 👇and join us on 2 July to discover who has made the final list!

🙏 Thanks

At Emerge, we are on the look-out for companies (existing and new) that will shape the future of workforce development over the coming decade.

If you are a founder building a business addressing any of these challenges in L&D, we want to hear from you. Our mission is to invest in and support these entrepreneurs right from the early stage.

If you are looking for your first cheque funding do apply to us here: https://lnkd.in/eWi_9J5U . We look at everything as we believe in democratising access to funding (just as much as we believe in democratising access to education and skills).

Emerge is a community-powered seed fund home to practical guidance for founders building the future of learning and work. Since 2014, we have invested in more than 80 companies in the space, including Colossyan, FutureFit AI and Skills Trust.

Emerge Education welcomes inquiries from new investors and founders. For more information, visit emerge.education or email hello@emerge.education, and sign up for our newsletter here.

Thank you for reading… I would hugely appreciate some claps 👏 and shares 🙌 so that others can find it!

Nic