The future of career navigation: AI career coaches will win the B2C job market opportunity

Career navigation has remained largely unchanged for decades, relying on personal networks and static job boards. 

Over the past 25 years, the only real innovation in this space has been the creation of online job boards – first general, then verticalised – which disrupted the classifieds business. This created a lot of value but only touches the surface.

Career navigation impacts almost everyone at multiple stages in their lives, from finding their first job to moving from one job to another. 

It’s a massive market. The global workforce is 3.6B people; even if we assume an arbitrary $10 per year price point, this is a massive $36bn opportunity. Top-down, macro trends have been variously valued at c.$30B (global career and education counselling market), $47B (global online recruitment platform market) and $1.2T (global employment services market).

Now, AI makes it possible to offer personalised career pathways, better job matching, democratised job application support, scalable access to career advice/coaching and tailored skill development to help you get to where you need to be. 

The winner will be the first solution to carry someone through an entire working life.

Read on for:

• Overview of the B2C career navigation market, inc. market map plus an anatomy of existing incumbents and their business models
• Key insights into the top “first movers”
• Specific ideas about what to build and advice on differentiators we look out for as early-stage investors in this space

* * *

Every career moves through the same stages: choosing a direction, finding work, getting hired, getting promoted, switching track. At each one, the stakes are high, the support is thin and any failures compound; a weaker first job carries a wage penalty that can persist for the best part of a decade, and younger workers move through more roles and industries in their first years than any previous generation at the same stage. 

These are structural gaps, and they are widening: by 2030, WEF projects job disruption equivalent to 22% of jobs, with 170 million new roles created and 92 million displaced.

“Bridging the skills gap requires millions of people to commit to build new skills and potentially enter new career paths. That is difficult to achieve. I’m excited about products and services that are creating the infrastructure for that massive shift to happen.”

Christina Sass, founder Andela and Emerge Venture Partner

Here are the macro problems creating this situation, organised by career navigation stage.

Career choice

• Lack of formal preparation: Post high school/university, you are expected to know which career to get into for the rest of your life. In general, most are unprepared and under-supported to make this decision and find the most fulfilling career for them.
• Impact of bad decisions: The first job a person secures can significantly impact their future earnings.

Job Search

• Lack of personalisation: Job boards generally don’t provide personalised information about whether the job is right for you (e.g. specifically for you, based on your past experiences, transferable skills, interests, preferred ways of working)

Application

• Influx of applications: Platforms have made it so easy to apply that you are competing against hundreds or even thousands of others for every role. The chances of even getting a response is near zero.
• Lengthy processes: Especially for blue collar work, where typically you’re paid by the hour, lengthy applications are particularly costly.
• Degree value: More than half of recent graduates are stuck in jobs that don’t require their degrees.
• One-size-fits-all: CVs and cover letters are not everyone’s strong suit.

Interview

• Lack of practise: Legacy interview practise centred around applying for lowest priority jobs first to use as practise runs. This is an extremely inefficient use of both candidate and employer time.
• Inequality: Strong performance in interviews is often a function of privilege (having had opportunities for experiences that enhance conversational/critical thinking/debating ability).

Promotions

• Lack of clarity: Most companies lack career frameworks which results in a severe lack of clarity around how promotions work.
• Who you know: As a result, this means most promotions are achieved through working the system (right relationships, right visibility, etc).
• Churn: This results in disgruntlement and churn – perpetuating labour market issues.
• Bias: Bias in processes means that women and minorities are promoted at slower rates.

Switching career

• High cost: Most individuals cannot afford career coaches.
• Lack of information: Most individuals do not know which courses they should/shouldn’t invest in to successfully execute a career transition.
• Preference for external talent: Companies are missing out on internal talent. Instead of helping employees to switch careers internally, they let people go and then hire new people.
• Reskilling: AI will create more jobs than it displaces, but it will drastically reshape the skills that are required to thrive.

With the advent of AI, creating hyper-scalable solutions to all of these problems is finally possible.

Companies are tackling these problems from different starting points – from application support to career planning and switching – but ultimately, we believe that the winner in this category will bundle all of these use cases into a one-stop-shop for candidates. Let’s see how.

The market opportunity

Below is a market map charting 80 career navigation companies, split by stage of the career navigation process and target user segment.

Let’s look at each segment in turn to understand where the exciting white space is.

Segment A – Career choice

Summary: Companies helping professionals find suitable careers based on skills, interests and experiences.

Problems in this segment: To date, career discovery has been centred on skills and experiences, not passions and interests, leading to suboptimal recommendations which has huge ramifications (influence on future earning potential, churn, motivation, etc.)

Status quo: Incumbents in this space include school/university careers departments, career coaches and career choice surveys sold to schools and universities. These typically lack personalisation, or are too costly and out of reach for most.

How will AI disrupt this segment?

• Personalised recommendations: AI can consume a vast amount of information (skills, education, career history, even YouTube history and social media feeds), structure or index this data at scale, and then use data models to match candidate characteristics to relevant careers and jobs. In theory, solutions could then go layers deeper, helping you position yourself for those future roles. Currently based in Amsterdam and working in strategy at Uber but want to work in a product role in the future? “Here are X,Y, Z specific things YOU can do in your role today to align yourself perfectly” – e.g. find opportunities to manage cross-functional projects in your current remit, reach out to Joe Bloggs also at Uber in Amsterdam who did strategy and moved to product, etc.

Who’s doing this? Companies like MoveUp offer resume-based models that can predict the viability of a given jump from job A to job B based on your resume in comparison to millions of other resumes. It is still basic, and barely scratching the surface of what is possible, but a good early example.

1. Provide your Linkedin URL, and also manually enter any additional information
2. You then input your career goals
3. Using AI, MoveUp then helps you to explore career paths which align with your goals. Dive deep into the details and uncover the career options that offer the most promising prospects.

Segment B – Job Search

Summary: This segment covers companies which direct white collar workers to relevant open roles.

Problems in this segment: Still not enough personalisation going into recommendations for new roles – very much based on recommending like-for-like new opportunities or centred on keyword matching like-for-like skills. Job sites are incentivised to drive application volume; they would rather you apply for 20 jobs than the two perfect ones, so this is not a priority for them to solve.

Status quo: With an estimated 25% market share of the jobseeker market, Linkedin is the massive player here. Here’s how they became the jobseekers’ platform of choice:

How will AI disrupt this segment?

• Enhanced job matching: NLP algorithms can parse and understand both job descriptions and candidate profiles at a nuanced level, ensuring better matches between jobseekers and openings. It no longer relies on keyword matching, but instead infers skills and competencies based on interests and past experience. This will result in users being paired with jobs that fit them, immediately (inc. roles they might not otherwise have thought relevant or suitable for them). As and when new roles become available, these will be pushed to candidates.

Who’s doing this? Veer offer natural text to job recommendations. They are still super early but we are excited by this type of concept.

1. Enter attributes, interests, areas of interest
2. Get live role recommendations

Segment C: Application

Summary: This category covers companies that help candidates create application materials (CVs and cover letters), and then go on to apply to jobs on the users’ behalf. We are excited for a world where personal AI headhunters dominate this category, understanding your skills, experiences and desires inside-out and then proactively scanning for open roles and applying on your behalf.

Problems with this segment:

• Everybody knows that to stand the best chance of landing an interview you should tailor your CV and cover letter to the specific job you are applying to. In practice, this is extremely time consuming.
• Platforms have made it so easy to apply that you are competing against hundreds or even thousands of other candidates for every role. The chance of even getting a response is near zero. There are limited benefits to spending time on an application you will likely never hear back from.

Status quo: Current solutions include various sources providing industry-specific advice on how to get through the application/interview process (e.g. case study books for getting into consulting).

How will AI disrupt this segment?

• Resume and cover letter enhancement: AI helps candidates create optimised resumes and cover letters tailored to specific job descriptions.
• Automated application + tracking: Advanced tools apply for roles on behalf of candidates and help track the progress and success of their applications.
• Referral search: AI-powered referral co-pilots link job hunters up with current employees in target companies who can refer them internally.

Who’s doing this? AIApply offers an automated job application tool that finds relevant roles for you, creates tailored application materials for each role, and then automatically applies on your behalf. See their tool in action here.

Segment D: Interview

Summary: This segment covers companies that help candidates prepare for interviews in low-stakes environments, enabling them to nail such a critical stage in the application process.

Problems with this segment

• Interviews form a pivotal part of most application processes yet are extremely hard to practise for. Traditional practise methods tend to involve applying for the lowest priority job first and getting interview time under your belt.
• Strong performance in interviews is often a function of privilege: the best schools offer more opportunities for 1:1 debate; parents who are around and able offer the opportunity to debate current affairs around the dinner table.

Status quo: Traditionally, interviews have been extremely hard to prepare for well. Options included: paying for a career coach/existing employee offering preparation services (expensive), applying to lower priority jobs first to practise (time consuming and inefficient) or researching questions likely to come up and rehearsing specific answers (useful but doesn’t cover any of the non-verbal side of interviews or prepare you to think on the spot).

How will AI disrupt this segment?

• Interview practise: AI tools offer simulated interview environments where candidates can practise and receive real-time feedback on their performance, including responses and body language (which we know employers use to provide insights into soft skills and cultural fit).

Who’s doing this? Final Round AI offers low stakes interview practise – see our associate Sami demoing the product here!

Segment E: Promotions

Summary: This segment covers companies that help employees to achieve promotions in their jobs.

Problems with this segment

• Most companies lack career frameworks, which results in lack of clarity about how promotions work.
• The promotion process often depends on internal politics and visibility rather than on merit or skill development, leading to frustration and higher turnover.
• Employees, especially in larger organisations, may struggle to identify and pursue the right opportunities that align with their career goals.

Status quo

• Here the status quo is people working with career frameworks within their employer’s HRIS insofar as they exist. A big limitation of these systems is that they focus on jobs within the employer only and they cost a lot to set up and keep up to date, so often don’t exist.

How will AI disrupt this segment?

• Personalised promotion pathways: AI can help users by analysing their career history, skills and performance to create a clear, actionable plan for achieving promotions. This plan can include targeted skill development, recommended projects and strategic networking advice tailored to the individual.
• Goal tracking and feedback: AI can help employees set career advancement goals, track their progress and receive real-time feedback on areas for improvement, helping them stay on track for promotion.

Who’s doing this? Career.io promotion tool.

• Step 1: Users receive a generic 9 step plan for how to achieve your promotion

• Step 2: Each step has templates you can use as part of the process

• Step 3: They also offer a salary review tool where you can input the offer you receive for a new role/promotion

Segment F: Switching career

Summary: This segment covers companies that help individuals to navigate career changes – think of this segment like an AI-powered career coach.

Problems with this segment

• Affordability: Most individuals cannot afford career coaches, nor do they know which courses they should/shouldn’t invest in to successfully execute a career switch.
• Lost opportunities: Companies are missing out on internal talent; instead of helping employees switch careers internally, they let people go and then hire new people.
• Reactive: Many career navigation tools are designed to be used at certain pivotal moments in a worker’s life: leaving school or university graduation, or when ‘it’s time’ to find a new job. Tools haven’t worked proactively to periodically prompt workers to assess whether their career paths are meeting their needs or to notify them that their jobs might be at risk of automation.
• Job tenure decline: A shift towards shorter job tenures highlights a growing trend of frequent job changes, and therefore greater need for career navigation tools and guidance.
• Future market shifts: Labour markets are entering a period of structural churn: the WEF projects 92 million roles displaced and 170 million created by 2030 – equivalent to 22% of all jobs turning over – with the fastest-growing demand in technology, data and AI roles, and 39% of workers’ core skills expected to change over the period.

Status quo: Dominated by traditional career coaches or cohort-based bootcamps to help candidates position themselves for their next role.

How will AI disrupt this segment?

• Personalised career transition plans: AI can be used to create personalised transition plans, beyond simple skill gap analysis. For example, by analysing a user’s performance reviews, understanding their favourite aspects of their current role, their short/medium/long term goals (both career and life/monetary), hyper-personalised recommendations can be made, directing users to the most relevant courses, certifications and skill-building activities to facilitate a successful career switch.
• Career forecasting: AI can be leveraged to analyse vast amounts of data from job postings, industry reports and economic indicators. Then, using predictive modelling, it can forecast future job market conditions by identifying emerging job trends and in-demand skills, helping you make proactive career decisions.

Who’s doing this? Anthropos takes your LinkedIn profile and infers skills, as well as the strength of those skills based on how long you were in the jobs which required them. It gives you a full skills profile. You can then explore skills paths to get ready for different role profiles. There is still a way to go to make this as easy as possible for candidates to make career transitions; most of these offerings (skills match to jobs) are still B2B.

• Step 1: Anthropos ingests your LinkedIn profile

• Step 2: It then takes all of your experiences and maps them to the skills you have.

• Step 3: You can dig into the skills you have and their estimated strengths based on how long you’ve spent working on them.

• Step 4: Anthropos then has skills pathways you can choose to get ready for your career transition.

• Step 5: You can also enter into AI-powered simulations with a career coach to learn more about the role and how your experiences are relevant for the role.

Segment H: Blue collar

Summary: This category covers companies that help blue collar workers reskill, find and apply for roles. In contrast to white collar jobs, where point solutions pop up solving for particular stages in the process, the blue collar space overwhelmingly sees providers offering end-to-end solutions which take blue collar workers all the way through from finding jobs to starting the role. We see this being the case due to the more binary nature of blue collar roles – they are often centred around certification, therefore offering less opportunity for companies to add outsized value when focusing on one specific part of the process.

Problems with this segment:

• Around 1% of enterprise technology spend goes to 80% of the workforce, although the market size for blue collar workers is massive. This underinvestment has left hiring processes fundamentally broken. Often, blue collar roles are filled through personal networks and expensive agencies.
• Blue collar options so far have been less about career-building and more about skill validation and certification, which makes the portability of those certifications vital. This makes it easier for a single company to manage the entire value chain.
• Every application involves filling in large amounts of data and undergoing tests. In these industries, you’re paid by the hour, meaning application processes are particularly costly.

How will AI disrupt this segment? We see all the elements of AI disruption outlined above also playing a role here, in particular:

• Career choice: AI can democratise access to information for individuals wanting to figure out which blue collar career path is best for them based on a variety of factors.
• Job search: AI-powered job boards aggregating fractured live role openings which traditionally get shared via WhatsApp and word of mouth will be a huge unlock for those looking for a role.
• Application: Every application involves filling in large amounts of data and undergoing tests. In blue collar industries, you’re generally paid by the hour, meaning application processes are particularly costly. The AI-powered application tools discussed earlier will be a game changer.
• Switching career: Specific employers (e.g. many of the large supermarket chains) are great at supporting career transitions from shop floor into management roles. We are excited by the opportunity here to centralise these sorts of insights to offer great opportunities to blue collar workers not currently in roles with well-defined career switching paths.
• Entrepreneurial upskilling: Blue collar work is often prime for entrepreneurs who want to set up their own practice. Leveraging AI to curate guidance and materials on how to do this, and successfully, will be a great value-add.

The reason we have separated out blue collar from white collar is that we see existing players operating across the length of the career navigation process, and in many cases, also working in specific niches. Given specialisms and the prevalence of certifications in the blue collar space, we see disproportionate value being created from solutions which are hyper-verticalised.

Who is doing this? Varm has created an e2e ‘solution in a box’ which touches upon the full extent of the blue collar career navigation process. They offer reskilling (to become a trained insulation installer) and then, via their labour marketplace, they can deploy newly qualified employees out onto jobs.

What to build as a founder

The next unicorn in this space will be AI-powered career coaches which touch upon every step of the user journey – from initial career discovery and ideation, pointing users to specific live open roles they would love, to building application materials and applying on their behalf, to coaching them through their interview process with low-stakes training, to ingesting your year-end reviews and career ambitions to get you that next promotion or help you transition your career to the next best step for you and your ambitions.

White collar:

• Currently, the bulk of the value sits in the Job Search segment. It’s obvious why; this is the foundation of the career navigation process. But we do not see massive opportunity for startup disruption here given the size of existing incumbents and the limited ways left to differentiate.
• Looking at the other segments, each presents opportunities for startups but nothing that on its own will incubate the next unicorn. Consumers won’t sign up to annual subscriptions for tools which give them career suggestions only, nor for point solutions to help them get promoted.
• The wedge here is Interview, where willingness to pay is high for interview practise, there are really no affordable alternatives out there and AI is making a massive impact on what’s possible. We are excited by the opportunity to gain a large user base through an interview product and then expand your offering across other segments to increase LTV.

Blue collar:

• We are excited for the transformations AI will bring to the blue collar application process by democratising access to career information, centralising job searches and streamlining application processes – particularly where time and cost are critical factors.

• The wedge here is continued hyper-specific specialisation.

What to watch for as a founder

Lifetime value

• Challenge: Getting users to consistently engage with AI-powered career tools can be difficult; you expect users to stick around for the length of their job search and no more.
• Emerge View: Providing materials support and interview practise is great, but how can you take those insights and create more value for the user? Capturing more of the value chain is crucial. For example, encourage users to think about their long-term career progression, not just their immediate job hunt. This could include personalised career development plans that highlight the skills and experiences needed to reach the next level in their careers, based on the data insights you gather. (If your platform identifies that candidates at the level above your users typically have certain certifications or experience, you can guide your users toward achieving these qualifications.) Another example is incorporating features that help users regularly assess and improve their marketability, such as ongoing skills assessments, personalised learning recommendations and networking opportunities, which can keep them engaged long after they’ve secured a job. This not only boosts user retention but also transforms your platform into a valuable career partner throughout their professional journey, rather than a tool used only during job transitions.

Monetisation

• Challenge: Monetising B2C career navigation tools can be challenging, especially in a space where many users expect free services. Finding the right balance between offering valuable free features and premium paid services is crucial.
• Emerge View: Startups should explore freemium models, where basic features are available for free, but advanced tools and personalised services require a subscription. However, there is a real opportunity in monetising the valuable data and insights you collect from users. Beyond just tracking talent pools, your platform will gather deep insights into what candidates are seeking in roles, common pitfalls in their job applications and areas where they need improvement. These insights can be incredibly valuable to employers looking to improve their hiring processes and tailor their job offerings to attract top talent. By offering data-driven insights to employers, you can create additional revenue streams and provide employers with a clear advantage in the competitive job market. This not only enhances your value proposition but also positions your platform as an essential tool for both jobseekers and employers, creating a more sustainable business model in the long term.

Delivering value for blue collar workers

• Challenge: Blue collar workers often face unique challenges in career navigation, such as limited access to career development resources, local job availability constraints and the need for specific certifications or practical skills. Traditional career tools may not fully address these needs, making it difficult for this demographic to effectively navigate their career paths.
• Emerge View: To effectively serve blue collar workers, career navigation tools must be tailored to their specific needs and realities. One way to tackle this is to be an expert in one area – for example, insulation (Varm) or heat pumps (Montamo). Blue collar is generally qualification-specific; by becoming experts in these niches, platforms can offer highly relevant job opportunities, tailored certification programs and industry-specific career advice.