Employers

Instead of a level playing field, we’re seeing a widening AI adoption gap that threatens to leave a huge portion of the workforce in the digital dust.

The reality? Most companies are treating AI upskilling like a generic software update. But as the numbers show, a one-size-fits-all approach is a recipe for stagnation.

The Seniority Divide: Who’s Actually Using AI?

The most striking trend in our latest analysis is the massive disparity in daily AI usage based on job level. While 52% of mid-level workers collaborate with AI daily, only 21% of junior employees do. This 30-percentage-point gap presents a pipeline problem: If the next generation of talent isn't learning to work alongside AI today, we’re creating a future skills bottleneck.

The research also found a significant divide between those steering the ship and those doing the specialised, day-to-day tasks. Of middle managers, 48% are using AI regularly, while only 20% of individual contributors do the same. When nearly half of managers are leveraging AI but only a fifth of their direct reports are, the productivity gain of AI stays trapped at the top, rather than fueling the engine of the entire team.

While senior staff and middle management have leaned into the tech, junior employees and individual contributors are being left to figure it out on their own.

The Perception Gap: A 17-Point Reality Check

It’s not just that usage is uneven—it’s that leaders often don’t realise how uneven it is. There is a significant disconnect between what’s happening in the C-suite and what’s happening on the ground: 59% of leaders believe their teams are regularly engaging with AI, but in reality, only 42% of employees are doing so.

This 17-percentage-point perception gap suggests that while leaders are sold on the vision of an AI-powered workforce, they haven't yet provided the practical, job-specific pathways to get there.

The Solution: Training for the Real World

The bottom line is clear: One-size-fits-all upskilling benefits no one. You can't give a data analyst and a marketing coordinator the same prompt guide and expect magic to happen.

That’s why we’ve expanded our portfolio of AI programmes to make sure we can teach anyone, in any job, how to use AI to be more effective at work. To date, we’ve trained 1,220 unique job titles. Today, we’re taking that a step further by introducing:

• AI Solutions Builder: Designed to develop agentic AI experts who design custom tools to boost productivity.
• AI Transformation Architect: To train experts to orchestrate and scale automation across the entire enterprise.

Whether you're looking to empower a junior contributor or train a specialist to overhaul your entire workflow, the training must be as specific as the role itself.

Ready to Close the Gap?

If you’re ready to move past the AI hype and start seeing real-world ROI across your entire organisation, we’re here to help. Learn more about our full offering here.

While installing a new tool is easy, achieving true AI transformation is hard.

At Multiverse, we have committed to making this change a full team effort. As a result, we increased our revenue per employee by 37% last year. Here’s how we approached it:

1. Communicate a clear vision and expectations

Successfully driving AI adoption begins with clear communication about what the transformation means, and what expectations come along with it.

Vision

For us, transformation meant integrating AI into the core of how the business operates and how our employees work. Our vision for transformation is built on three pillars:

• Building the foundations: Unlocking our data safely and responsibly so everyone has access to it and knows how to use it to inform business decisions.
• Enabling our people: Upskilling and instilling an AI-first culture, giving our team the resources and support they need to feel confident using AI in their day-to-day.
• Delivering the change: Transforming each department to deliver outcomes with AI, based on their individual workflows and needs.

Expectations

We communicated expectations by:

• Establishing clear guidelines: Making AI a core part of the organisational performance framework. Our new operating principle, "AI to deliver outcomes," embeds the expectation that AI is an engine for performance at every level and is now a core part of our performance framework.
• Fostering an AI-first mindset: Employees should be encouraged to think, "Can AI do this?" when assigned a task, promoting the use of AI for increased day-to-day productivity.

2. Engage every level of the organisation

While having the full backing and role modeling from the highest leadership is crucial, true ownership must be felt across the board.

An every-level approach to engagement is vital to ensure everyone is part of the change. One effective way to achieve this is by creating different roles within the organisation, outside of the technical team, to foster widespread participation:

• Amplifiers: These are all employees who are supported and enabled to utilise AI in their day-to-day work.
• Builders: A subset of people who sit within departments, go through certification, and gain the skills to build AI solutions for their respective department responsibly.

This structure ensures both roles are recognised as important, with Amplifiers feeding into Builders and Builders supporting Amplifiers, distributing engagement across the company.

3. Support continual learning and skills development

AI adoption requires continuous learning. At Multiverse, we’ve committed to all of our employees that they’ll become the most AI-enabled version of their profession, and we provide the upskilling opportunities to get them there. Support for skills development can be integrated into an organisation in several ways:

• Tailored training: Providing customised enablement for different roles to ensure relevant learning opportunities for everyone.
• Ongoing support: Establishing a helpline for when employees get stuck. At Multiverse, our “AI Genius Bar” is available throughout the week for those seeking a bit of extra guidance.

4. Balance financial and cultural metrics for success

Measuring success must be holistic, tracking both hard metrics and qualitative ones. While impacting company financials is important, it’s also crucial to ensure employees are being taken along the journey. We break our metrics down into:

• Revenue per employee: Focuses on how AI drives top-line delivery, not just operational efficiencies or time saved.
• Employee sentiment: Tracks cultural change by using pulse surveys to see if confidence is increasing as new arrangements are rolled out.

Ultimately, achieving AI transformation is a journey, not a destination, and it requires a holistic strategy that integrates technology with people and culture.

This significant extension allows Multiverse to further its model, enabling more high-impact, debt-free degree pathways.

Multiverse is the UK's only independent training provider with degree-awarding powers, a distinction that confirms the quality of education it provides its apprentices. In the National Student Survey commissioned by the OfS, it has held the highest satisfaction rating within the Digital & Technology Solutions Professional standard for the past two years, currently sitting at 85.6%.

This expansion immediately enables the launch of Multiverse’s newest degree apprenticeship programme, AI Product Engineering (AIPE), which is uniquely designed for the future of the industry, amplifying software engineers' capabilities through AI so they are able to deliver more value, faster. The AIPE programme is focused on training engineers to design end-to-end systems and effectively integrate AI across the Software Development Lifecycle. It teaches engineers how to use AI as a co-engineer to amplify their productivity and deliver better commercial outcomes.

The AIPE programme will be quickly followed by additional degree-level programmes within the Chartered Manager and Project Manager standards.

"This recognition from the OfS reinforces our approach. We are proud to be the UK's only independent provider with this power, and its extension means we can rapidly scale up the creation of vital, high-growth degree pathways," said Euan Blair, Founder & CEO at Multiverse. "By expanding our degree-awarding scope, we can deliver more high-quality, job-relevant qualifications that produce the talent the UK economy desperately needs."

The value of this model is best described by those currently benefiting from it. Louise Gardner, a Multiverse degree apprentice, spoke about the programme’s impact: "Doing a degree apprenticeship has helped me advance my career - after graduating, I was able to step into a secondment in the global corporate responsibility team. But more than that, it provided me with critical insights and skills, which I’ve leveraged to add tangible value to my team by improving how we use data to inform decisions.”

This expansion allows Multiverse to deliver more impactful, degree-level apprenticeships that directly address the skills needs of the UK economy, preparing a new generation of talent for the future of work.

Last year, our commitment to empowering our team’s AI use resulted in a 37% growth in revenue per employee. We believe the most powerful AI tool is not a new piece of software, but a workforce that has been taught how to effectively use it.

Our transformation shows that true AI adoption requires more than just access to technology—it demands an entire behaviour change.

Beyond the tool: It's a mindset shift

Many leaders believe their teams just need to learn a new tool to achieve meaningful results, but true transformation demands more. It involves reimagining entire workflows and understanding where the AI tool fits—or where it completely replaces existing processes. Furthermore, it requires focusing on the essential human skills, like critical thinking, to filter results and identify inaccuracies.

Leading a team through this shift, especially when some are reticent to adopt new tech, is a core element of culture change.

How our Learning team uses AI for impact

Our dedicated Learning team is constantly adapting, recognising that in the world of AI, continuous, real-time learning is paramount.

1. Improving the learner experience

We are focused on using AI to deliver a hyper-personalised, contextualised, and enjoyable learning experience.

• Personalisation at scale: AI allows us to move beyond one-on-one mentoring, which was previously necessary for deep customisation, by using the knowledge of LLMs to personalise and contextualise content for each learner.
• Real-time relevance: The world of AI moves fast, so we created protected learning time for our subject matter experts to stay current. We also use AI agents to scan the entire market, collect information, and bring back reports to highlight where we need to focus our attention, ensuring our content is always up-to-date.
• Innovative tools for apprentices: AI is interwoven into the apprentice experience to make learning easier. Our contextual, AI-powered coach, Atlas, helps learners understand why they are stuck and how to unblock themselves, rather than just giving the answer.
• Tools for creators: We've built internal AI tools that remove the challenge of the "blank page" for our learning designers, helping with initial creation, automation, and consistency.

2. Delivering outcome-driven learning

In the AI era, learning is not for learning’s sake; it is for enabling new individual or company capabilities.

• Measuring impact: The rise of AI and modern data systems means we can now connect learning to concrete, measurable results. We can get a "before and after snapshot" to understand the true impact that learning has on outcomes in a way that was never possible before.
• Outcome focus: This capability makes learning truly outcome-focused. We start with what we’re trying to achieve, and work backwards from there to understand what skills our learners need to develop in order to get there.

The foundation of our success is understanding that human adoption drives technology's value. By shifting our internal culture, we are not just keeping pace with AI—we are actively shaping the future of work, delivering personalised experiences for our learners that deliver true transformation.

At Multiverse, we have seen firsthand that investing in AI isn’t just about the technology—it’s about the people building it. This approach has yielded tangible results: last year, we grew our revenue per employee by 37%, a direct result of our investment in AI technology and the cultural transformation that enabled it.

So, how do you shift an engineering mindset from traditional development to AI-first innovation? Here is how we approach AI transformation within our engineering capability:

Embracing experimentation

The key to unlocking innovation lies in individual empowerment, giving team members the freedom to experiment, trusting them and their domain expertise to get things done.

To truly build with AI, teams must shift their perspective on failure. In our engineering team, we encourage engineers to try, learn, and even fail, knowing they might not succeed on the first attempt.

• Learning at pace: We view experimentation not through the lens of risk aversion, but as an instrument for learning at pace.
• Dedicated time: Innovation doesn't happen if it isn't on the calendar. We utilise "Hack Weeks" and allocate 10-20% of our engineers' time specifically for learning and experimentation.

Balancing Speed with Security

A common hurdle in AI adoption is the fear of security risks. How do you balance the need for speed with the necessity of safety?

Our approach is to create guardrails so that our builders don't have to overthink compliance while they are in the creative flow.

• Programmatic boundaries: Whether it is through role-based access control or context-setting files in coding tools, we ensure engineers know it is safe to experiment within specific environments.
• Removing friction: By making security programmatic, engineers don't stumble over administrative fears; they can roll into their creativity and embrace the technology.

Overcoming the fear of failure

With any new movement, there is a natural human fear of humiliation or failure. To foster a true builder’s mindset, leadership must prioritise psychological safety.

By democratising the technology, we remove the fear that AI is rocket science. When the team sees that failure is just part of the process, they gain the confidence to build the future.

• Leading by example: Leaders need to embrace the technology themselves so they’re able to lead from the front.
• Celebrating the losses, as well as the wins: We openly share our mistakes to show that failure is just part of the process. This builds the confidence needed to try something new.

Innovation in action: AI grading

When you combine psychological safety, clear guardrails, and a culture of experimentation, you get tangible results. A prime example of this approach in action is our AI Grading capability.

An engineer on our team identified that grading homework was a prime opportunity to leverage AI and built a solution from scratch to address it. This tool has transformed how we operate:

• Empowering coaches: It reduces a massive amount of hours for our human coaches, freeing them up for higher-order activities like spending actual face time with learners.
• Faster feedback: Learners now receive faster feedback on their work, motivating them in their drive to improve.

This is the power of a builder mindset: when engineers are empowered to experiment, they build solutions that elevate the entire learning experience.

As we learned, successful AI implementation doesn't start with models—it starts with data. For any organisation aiming to harness the full power of AI, establishing the right data foundations and culture is paramount. AI is only as intelligent as the data it is trained on.

Here are three core pillars for building a robust data foundation and culture ready for the AI transformation:

The agility vs. scalability challenge

One of the biggest data challenges in an AI transformation is finding the right balance between agility and scalability. Since AI is a rapidly evolving technology, moving fast often means experimenting quickly, even if initial methods aren't scalable.

• Embrace agility for experimentation: A successful AI strategy involves enabling experimentation and allowing teams to try new things without immediately requiring a massive, fully developed data pipeline. This might mean starting with simpler, non-scalable methods to quickly prove a concept.
• Scale for sustainability: Once a concept is proven, the key is to transition to scalable solutions. An effective strategy involves doing both—experimenting quickly and building scalable structures—by knowing when to do one and when to do the other.

Building a data-first culture

Formal training is essential for building data literacy. However, training alone is not enough; success hinges on integrating data into the very DNA of the organisation.

• Consistency is key: A strong data culture means data is part of the day-to-day language and ways of working. Key metrics and definitions must be clear and consistently used across all settings, including meetings and documents.
• Empowering the whole organisation: Effective AI implementation requires giving data access to everyone, not just data scientists, and teaching them how to use it. Upskilling the entire organisation ensures the best possible use is made of the data.
• The consumption shift: As companies embrace AI, the way people and machines consume data changes. While dashboards were once common, organisations now increasingly need data formats that machines can easily read, such as APIs. Consistency in definitions is critical for trusting AI to correctly interpret the data and provide answers in natural language.
• Security and Compliance: The foundation of a trustworthy data strategy is ensuring that data is handled securely and responsibly. We demonstrate this commitment to our clients and apprentices, ensuring their sensitive information is handled with the highest level of care. Multiverse has achieved SOC 2 Type 1 certification, a result of third-party audit from the American Institute of Certified Public Accountants, confirming our internal controls exceed the necessary, rigorous standards.

Data as your competitive advantage

The most advanced AI applications are widely available to virtually everyone. What truly differentiates a company and drives value is its proprietary data, and what they build with it.

• Unlock internal value: Well-structured, proprietary data can unlock powerful AI solutions. For example, taking unstructured data, structuring it into a knowledge graph, and sharing it can provide valuable insights for customers.
• Move ahead of the pack: If a company wants to build something truly differentiated and make a real difference, it must connect AI to its unique internal data. The sooner an organisation commits to structuring and leveraging its data, the sooner it will gain a competitive edge.

By focusing on structuring data, fostering a company-wide data culture, and strategically balancing speed and sustainability, any organisation can build the solid foundations necessary to deliver powerful and effective AI transformation.

As other People leaders scramble to compete for a scarce pool of highly skilled external AI talent, we have fundamentally shifted our approach to talent development to focus on building our own AI-ready workforce internally.

The shift: Hiring for AI will, not just skill

We recently launched a new hiring framework that focuses on assessing a candidate’s interest in AI. Why? Because we don't want to miss out on brilliant talent just because they haven't had the opportunity to engage with AI tools in their previous roles.

Our framework assesses candidates’ current level of AI competence through a series of questions and tasks built into our hiring process, matching them to one of four levels of AI maturity. The only group we exclude from hiring are those who demonstrate no will towards learning about AI. Everyone else, we’re confident we can equip with the necessary skills to fully adopt AI.

Bespoke onboarding: Building AI skills

This commitment to developing talent continues the moment a new hire joins. We have committed to our employees that they will become the most AI-powered versions of their profession.

Based on their assessed AI maturity, new hires are placed into a custom onboarding programme, receiving more than 20 hours of training in their first three months.

Demonstrable ROI: Quantifying the impact

Our internal upskilling isn’t just a feel-good initiative: it delivers measurable business impact. Last year, we grew our revenue per employee by 37% through strategic investments in AI and a cultural transformation to enable it.

We track several key outcomes, starting with tool usage. We’ve been able to demonstrate that those who engage with our AI upskilling programmes use our AI tools much more frequently than those who don't: for example, they log 73% more Gemini interactions.

We also look for impact stories, quantifying the results of the training, such as the reduced number of hours spent on certain activities or specific cost savings. Across our departments, we’ve logged more than 220 AI use cases created, representing how our team has reimagined their workflows to be more efficient and effective.

If you are a People leader looking to future-proof your organisation, the answer isn't a complex, expensive external hiring spree. The answer is empowering every member of your team with the skills and confidence to excel in the AI-driven future, right now.

Together, in collaboration with NHS HR, Apprenticeship & Workforce professionals, we've successfully upskilled hundreds of NHS staff members across 100 NHS Trusts. This isn't just a number: it represents a fundamental transformation in how healthcare is delivered, from the frontline to the back office, as staff gain the confidence and expertise to harness the power of technology.

Our partnership was born with the aim of empowering existing NHS staff to drive innovation from within. In a sector with increasing demands and shrinking resources, data and AI present a much needed solution to a growing problem.

“Data more so than ever is a critical commodity in the NHS to support decision making, driving more efficient and effective outcomes for patients. We partnered with Multiverse to upskill our community in data science specialisms, and over the past 18 months, we’ve seen apprentices directly apply their learnings to deliver real results.”

Barbara Begg
Head of Central Commercial Function – Commercial Capability at NHS England

"We identified digital literacy as a key learning need early on, and our partnership with Multiverse supported us in addressing it through high-quality apprenticeships. The Multiverse team has always been responsive and collaborative, making it easy to support learners and keep momentum going.”

Roxanne Moran
Talent, Learning and Development Manager at National Institute for Health and Care Excellence

Apprentices are already putting their new skills to use, building innovative solutions that transform their work.

At Royal Free London NHS Foundation, an administrator migrated patient management processes to a digital system, doubling the daily department case load from 30 to 60 patients and reducing wait times from more than 30 minutes, to only 10.

Meanwhile at Medway Foundation Trust, an endoscopy nurse built a Power BI dashboard to automate the theatre audit processes, reducing delays, minimising errors and enhancing resource allocation.

None of this would have been possible without the hard work of HR, Apprenticeship & Workforce professionals across the NHS, who have supported learners to achieve these incredible results, in partnership with senior executive leadership teams.

"The NHS has the highest potential to benefit from technology of any institution in the UK, and its commitment to upskilling its people with the digital and AI skills needed for the future is a testament to its leadership,” said Euan Blair, Founder and CEO at Multiverse. “We've been consistently inspired by the apprentices and the leadership teams who have championed them—they are the true innovators, driving change to make a tangible difference in patient care and operational efficiency."

“Working with Multiverse has been seamless from our very first conversation. The team is responsive, supportive and willing to adapt to our needs as an organisation. Multiverse has also been very effective at understanding our strategic objectives, ensuring our apprenticeships have maximum impact to improve our processes, and ultimately, the delivery of care.”

Samantha Ibison
Apprenticeship and Employability Lead at Leeds & York NHS Trust

We really have enjoyed working with Multiverse – they’re engaged, responsive, and flexible to the changing (and sometimes conflicting!) needs of a big organisation like ours. The apprenticeships have been really popular and are clearly helping us meet the needs of our workforce. We’re excited to continue our partnership with Multiverse and to see the lasting impact it will have on our staff and the care we provide to patients.”

Susana Lucena-Amaro
Associate Director for Learning & Development and Apprenticeships at Barts Health NHS Trust

By equipping the NHS workforce with the latest digital and AI skills, Multiverse is not only helping individuals grow their careers but also empowering the entire healthcare system to become more efficient, innovative, and resilient.

The staff Multiverse has trained are now the data champions, the digital pioneers and the AI innovators who are helping to make the NHS more ready for the challenges of tomorrow.

That's why we're evolving the Multiverse Platform to ensure no learner is ever alone on their upskilling journey.

Our 24/7 AI coach, Atlas, is more than a learning companion. Now, Atlas actively suggests, challenges, and offers instant feedback, empowering your teams to hone new skills rapidly and apply them in the workplace.

Keep reading to find out how Atlas helps your teams unleash real business value.

Building the right skills, right now

In the age of AI, competitive advantage isn't just about adopting new tech - it's about how fast your teams build the skills to use it.

A recent study on workforce intelligence reveals how skills velocity (the ability to quickly develop new industry and tech skills) will be the secret to unlocking real competitive advantage in the AI age.

That means continuous upskilling will become more vital than ever. Over two thirds of leaders say new workforce skills will be needed to remain competitive by 2030.

But to drive maximum impact, learning can’t be limited to individuals or specific teams. You need the ability to scale skills quickly across your entire workforce.

Atlas serves as a point-of-need solution, adapting to learner needs, industry, and role contexts, ensuring the development of the right skills at the right time.

Powerful collaboration, with true engagement

A paradox is emerging with many AI tools. They’re designed to make work tasks easier - but that risks making teams less skilled by offloading critical thinking.

An MIT study on 'Cognitive Debt' found that using AI assistants for writing tasks led to reduced brain activity, while other academic papers show that 'Cognitive Offloading' - delegating thinking to AI - is directly correlated with a decline in critical thinking skills.

So, how does Atlas avoid this pitfall?

Rather than simply allowing learners to offload cognitive work, Atlas is designed to foster what academics like Siemens and Moldoveanu (2025) call "interactional intelligence".

Practically, this means Atlas uses a Socratic, context-aware method to encourage critical thinking within the context of a learner's role and industry.

This helps your teams build a crucial skill - using AI not as a shortcut, but as a collaborative partner to deepen understanding and solve complex problems. But we don’t stop there. Learners are also actively taught to critically assess AI outputs, and strategically guide it to respond to their needs.

Our data shows this in action. Our learners are using Atlas as a thinking partner, not an answer machine. They’re conducting complex, goal-oriented activities, that demonstrate true engagement:

• Solving technical & practical problems (34%)
• Understanding & learning (27%)
• Creating & delivering projects (20%)
• Admin support (16%)

Three features, designed to create maximum value

To build this deeper engagement, our expert Product Teams - with deep industry expertise in artificial intelligence, educational psychology, and learning science - are enhancing three features that help learners actively engage with Atlas.

Guidance with context

Atlas is built into every page of the Multiverse platform. It knows exactly what learners are working on and tailors its guidance to that moment.

Whether they ask Atlas to help locate key resources, understand their learning schedule or troubleshoot issues, Atlas leverages its role and context-aware capabilities to provide real-time support.

Sometimes AI isn't enough. If a question is too complex or needs a human touch, Atlas will recognise this and connect your learner to the right person - whether that’s one of our expert instructors, or one of our support teams that help to resolve tooling issues, support additional learning needs and learner wellbeing.

Generating high-value project ideas

Atlas is a transformative partner that empowers learners to engage deeply, think critically, and apply their knowledge with immediate impact.

To close the gap between learning and application, Atlas helps learners to brainstorm high-value project ideas in the context of their industry and role. Atlas acts as an invaluable collaborative partner.

It suggests innovative approaches, challenges underlying assumptions, and provides instant feedback on initial concepts.

This iterative dialogue guides learners toward the most impactful opportunities at work, ensuring learners apply their skills on areas that will have the most benefit to them, their team and their organisation.

Helping learners apply their new skills

As learners embark on applying new skills in a workplace project, Atlas functions as a powerful coach.

Atlas challenges learners to deepen their understanding, helping to explain unfamiliar terms in language that resonates to each learner, and helping to break down complex topics into manageable steps.

When a learner is writing a report, Atlas can act as a thinking, writing, and editing partner, helping to outline, develop arguments, spark counter-arguments, and refine in real-time.

Similarly, in coding, Atlas can assist with code generation and debugging, transforming a traditionally individual task into a collaborative one. This interactive approach ensures that skills are not just learned, but truly mastered and applied.

The future of upskilling is here

The Multiverse Platform, powered by Atlas, champions a future where human potential is amplified, not diminished, by AI. We’ll help you build a workforce equipped with future-ready skills - and provide expert guidance to help your teams power productivity and performance.

At Multiverse, we know that line managers play a crucial role in a successful learning journey. But having the right information at your fingertips is key.

That’s why we’ve launched your new Line Manager Dashboard - a tool designed to give you a clearer view of apprentice progress and empower you to be an even more effective mentor.

A central view of apprentice progress

The new dashboard centralises the progress and support insights you need to effortlessly guide your apprentices.

Gain clear visibility to help your team members as they apply their new skills in practice throughout their learning journey.

Key features include:

• Off-the-Job Hours: Quickly see if your apprentice is on track with their required learning hours, ensuring they meet this core programme requirement.
• Session Attendance: View their attendance in recent coaching and delivery sessions, giving you a clear picture of their engagement.
• Project Status: Understand which projects have been started and submitted, helping you stay informed on their progress with programme deliverables.

From data to development

This visibility is designed for one primary purpose: to help you have more meaningful, data-informed conversations.

When you can easily see an apprentice’s engagement and progress, you can:

• Celebrate progress by acknowledging when projects are submitted and work is complete.
• Proactively support: The dashboard provides clear flags to help you easily pinpoint apprentices needing support, allowing you to step in with guidance at the right moment.
• Drive meaningful discussions by asking informed questions about the specific projects they are working on.

Ultimately, the dashboard empowers you to support your apprentices proactively and helps you feel more connected to their learning journey.

Keen to see it in action?

The Line Manager Dashboard is another step in our journey to build a truly exceptional learning platform - helping you unlock the full potential of your teams and deliver measurable impact for your organisation.