Employers

It’s beyond doubt there’s huge potential for AI to deliver results and economic value for businesses, from greater productivity to improved customer experience.

But to build a truly AI-native business – where AI is baked into the DNA of your business, and delivering maximum ROI – multiple elements must work in harmony, or momentum can easily stall.

We recently spoke to 2,000 tech leaders and employees – to get a realistic understanding of AI maturity today and what businesses can do to improve. And it’s clear that barriers to AI adoption are preventing the technology from delivering on its promise.

But what are they? Here’s three common roadblocks and how your business can start to overcome them:

1. Overestimating AI maturity

We found that four in five leaders say implementing AI has led to an increase in revenue generation, while 97% say the benefits have met or exceeded their expectations. Overall, 57% believe they are ahead of the competition in AI maturity.

Today, optimism in AI for businesses is understandably high. However, there are signs this may be an overestimation of progress. And optimism could be masking the realities of what it takes to fully implement and benefit from the technology.

As AI continues to evolve, establishing best practice is an ongoing challenge that’s creating risks and potential missed opportunities for the future.

Strength in areas such as data governance and security are vital hallmarks of AI excellence – and necessary requirements to reach AI maturity. But they are being overlooked by many.

Only a small proportion of leaders report they have established key hallmarks of best practice —for example, just 28% strongly agree they have provided guardrails and governance structures to limit AI risk. And less than half (43%) strongly agree they have ensured responsible use of AI in business practices.

This gap between leaders’ expectations and reality suggests that businesses are struggling to objectively assess their own progress with AI – and identify the further steps needed for full implementation.

Using a more objective framework to benchmark progress, categorise the stages of AI maturity, and create a roadmap for next steps can help businesses to plan more holistically – and realistically. We’ve included 3 actions for leaders in our ROI of AI report to get you started.

2. Difficulty securing investment and demonstrating ROI

Our research found tech leaders are positive about AI delivering financial gains in the long term – in fact, 85% expect to see an increase in revenue generation in 3-5 years.

But if businesses are unable to prove the value of AI today, and if employees lack the skills to access its full potential, then it will become increasingly difficult to unlock further investment – and AI progress will stagnate.

Of all the AI adoption barriers cited by leaders, 63% say the biggest blocker to further investment is the inability to fully use existing AI technology. Paired with more than half (58%) reporting resistance from employees to use AI and a lack of ability to demonstrate or predict tangible results (57%), it’s clear we’re at a standstill.

Value driven by AI needs to be tracked diligently and communicated within businesses. Only then can roadblocks, like resistance from employees or workforce skills, be tackled head-on. Take a look at our recommendations for employers in our ROI of AI report to find out more.

3. Employees still lack access to formal AI training

True AI maturity depends on people as much as technology, and our data shows a lack of workforce skills is slowing AI adoption progress.

Businesses need to build workforce expertise, fast, to combat struggles with implementation and get the most from AI. But training opportunities remain in short supply.

We found that most employees (51%) have received fewer than 5 hours of training on AI, with 25% opting to self-fund training. And many have gained skills by playing with ChatGPT (61%) or learning on the job (59%).

Of the employees we spoke to, 56% of workers that describe their AI skills as ‘expert’ have not received any formal training from their employer.

This gap in formal training may mean workers struggle to assess whether their actions are aligned to company policies or broader best practice – in turn, creating potential risks for the business.

Currently, workers are largely fending for themselves which has a number of ramifications for employees and businesses alike. For the worker it can be difficult to understand their personal skills gaps and learn efficiently with limited timeframes. For the business, informal AI usage from employees increases risk of misuse, and limits ability to measure ROI from new tools.

Learn more about your AI maturity

Assessing AI maturity helps businesses get the most out of emerging tech. From prioritising investment to identifying skills gaps, understanding where your business is on the AI maturity scale is the key to access future growth.

To learn more about AI maturity and next steps, check out our full ROI of AI report.

The challenge

On average, construction employees spend 29% of their time working with data unproductively, according to the Multiverse Skills Intelligence Report. It’s a growing challenge, particularly in a space like construction – where daily workflows are so closely tied to complex, business-critical datasets.

To store, use, and analyse data more effectively, construction companies are taking steps to build their data maturity.

Laing O’Rourke is one example. Since 2021, the team has worked with Multiverse to improve data skills and create data champions across the organisation. At Big Data LDN 2024, we heard how learners have created new efficiencies through data upskilling programmes.

Our panel included Pedro Rente Lourenço, Group Head of Data and Analytics at Laing O’Rourke, in conversation with Louisa Dunwiddie, Enterprise Account Director at Multiverse. We discussed how Laing O’Rourke has enhanced workforce capability and powered a data revolution within its business, laying the foundation for a valuable data strategy.

The upskilling opportunity for construction transformation

The construction industry deals with complex data, from geospatial and survey information to cost estimations and financials. As the scale of projects and data estate grew at Laing O’Rourke, decision-makers realised that data skills were needed outside of a ring-fenced IT department. If not, critical skills gaps could slow productivity.

As Pedro told us, “Data governance cannot be confined to a data team – it needs to spread out across our projects, because every project is almost like its own business.” Multiple teams across Laing O’Rourke stood to benefit from data upskilling programmes.

The Data Academy at Laing O’Rourke

Laing O’Rourke partnered with Multiverse in 2021 to establish their Data Academy. They used the Apprenticeship Levy to fund employee upskilling in data and AI, at no extra commercial cost.

Initially, 87 employees enrolled in courses to improve data skills across the company – transforming how they handle and gain insights from data.

Today, Laing O’Rourke has had nearly 300 members of staff enrol on the programme, driving transformation within the firm.

The results: The impact of the Data Academy

Pedro reflects that initially, Laing O’Rourke simply wanted to see whether the programme would “stick”.

They saw fast success, and now, staff from teams across engineering, quantity surveying, HR and more have learned how to use data more productively.

“It’s created more and more demand, because when staff see the value, they see there is a clear return on investment.”

The Data Academy has shifted Laing O’Rourke’s operating model – bringing data capabilities out of the IT team and closer to other employees who use it every day. It has two main advantages:

1. Measurable efficiencies for dashboard product owners

Employees with newfound data skills have driven new levels of productivity for Laing O’Rourke. Pedro told us how data-literate teams can now generate dashboards, develop systems for automation, and reduce silos across the organisation.

The programme has also helped staff make sense of data and explore new opportunities with technologies like AI. Pedro highlighted how they can “look beyond chatbots” to applications such as risk management and data-driven sustainability initiatives.

But while anecdotal evidence tells a compelling story, Laing O’Rourke’s transformation journey needs to be informed by data. Tools to measure the success of change help the team validate the value of upskilling through a standardised return on investment analysis.

“We are continuously analysing ROI in a standardised way, so when people are going through the cohort and developing new solutions, we can see how much it cost and how much time it saved them,” Pedro explained.

The figures are then validated with line and functional managers to support the business case for upskilling. Ultimately, Laing O’Rourke has found that if more people in the business have data skills, more value can be unlocked.

2. Organisational culture change

To drive the success for the programme, Laing O’Rourke selected members of staff who worked with a lot of data to participate. These were the stakeholders who could influence the most change and increase wider data literacy across the organisation.

They found that once staff were aware of the importance of data quality, they would try to design new ways of working that led to process change. “That’s where we really see increased capabilities,” Pedro reflected, “when staff ask “why is this important? what can I actually do with this?”

This mindset change spread down from leaders, and out through individual branches of the business.

“There’s a butterfly effect when you’re reducing silos and breaking down barriers. When employees can save themselves five hours a week, they can enable their team to each save five hours a week. That’s where we see the culture change and the real transformation.”

Data skills are critical for modern organisations

Since recognising the lack of data maturity in the business, the team at Laing O’Rourke has successfully developed data capabilities and driven business growth.

Embedding data skills throughout the workforce is critical for staying competitive as industries accelerate their transformation efforts.

As Pedro put it, “you can bring as many great technologies in as you want, but if you don’t bring people’s knowledge up and give them skills to work with that data, you’re not going to get the benefit.”

Watch the full session with Pedro Rente Lourenço and Louisa Dunwiddie at Big Data LDN 2024.

Find out more about Multiverse’s data programmes to upskill your staff, achieve greater data literacy and build toward business transformation goals.

Half of business owners believe gaps in key tech and data areas will negatively affect business performance over the next decade, across metrics like profit and customer satisfaction.

But policymakers have plans for change. Labour’s new body Skills England is currently being established to drive economic growth, widen career opportunities, and meet future workforce skills needs.

Here’s what employers need to know.

What is Skills England?

Skills England was one of Labour’s key skills manifesto pledges. It is a new Government agency, sponsored by the Department for Education that aims to unify the skills landscape, assess the UK’s skills gaps and transform the system. It will bring together stakeholders across government and beyond, including businesses, training providers, unions, Combined Authorities and regional organisations to collaborate and inform the design of apprenticeships and other training.

In June 2025, Skills England replaced the Institute for Apprenticeships and Technical Education (IfATE), which was the non-departmental public body that oversaw the UK’s skills system. Skills England will take over IfATE’s responsibilities, and it also has an expanded remit including helping inform policy development.

Skills England is chaired by Former Cisco UK & Ireland CEO and Chairman Phil Smith CBE. The board and members, are responsible for shaping its strategic direction and have been appointed from across the skills system.

Skills England and Apprenticeship Levy reforms

One key responsibility Skills England will hold is to create and maintain a list of training courses eligible for funding through the new Growth and Skills Levy, which is set to replace the Apprenticeship Levy. You can learn more about the Levy reforms in our guide for employers.

What will Skills England do?

Skills England has already started assessing the state of skills in the UK, which will inform future policy on apprenticeships and technical qualifications for businesses. Its first report sets out the challenges limiting growth across three pillars:

• Local-level disparities and immobility
• Mismatched skills
• Future megatrends

One of the main ‘mismatches’ the report flags is between employer needs and digital skills. It calls out that less than half (41%) of the UK’s adult workforce are able to perform all 20 tasks deemed essential digital skills for work. These include everyday workplace skills such as communicating using digital platforms and accessing tax information digitally.

While skills shortages aren’t limited to digital roles, they represent a large gap. According to a Government Employer Skills Survey, vacancies are more likely to be due to skills shortages for digital roles (81%) than across all occupations (63%).

Skills England will use these findings to inform changes to the existing skills system. It plans to bring together different partners to match skills supply to demand and build a more coherent approach to training.

A simpler, more effective system is welcomed – providing businesses with access to essential resources for skill development and filling sector-specific skills gaps.

The Multiverse take

It’s exciting to see the UK Government focus on addressing digital skills gaps in the workforce. We’re looking to working with Skills England and seeing how it will drive positive change.

There's no doubt it will play an integral role in bringing together employers, training providers and the many moving parts of the UK’s skills economy. Collaboration that will help build the workforce the UK needs.

To learn more about Skills England, the Levy, or other ways you can upskill your workforce, get in touch with Multiverse today.

Updated: June 2025

Leaders and workers alike are seeking opportunities to increase productivity, transform the customer experience, and unlock new product capabilities using AI tools.

But if workers aren’t also equipped with basic AI literacy to help them leverage new tech effectively and responsibly, AI may only create more headaches – rather than curing them.

Successful AI adoption is often held back by a lack of workforce skills, and leaders name AI as their most significant skills gap. Despite this, many workers still lack access to AI literacy resources, with the majority of workers (51%) having received under 5 hours of training so far.

In this article, we’ll assess how the AI literacy gap forms, and what employers can do about it.

What is AI literacy? Definition and examples

AI literacy refers to employees’ understanding of AI as a technology and how it can be applied in daily work. This includes understanding what types of AI exist, identifying use cases for AI, and knowing the basics of how to use it safely.

Examples of employee AI literacy can include:

1. Using AI tools – leveraging the likes of Microsoft Co-pilot or ChatGPT in their day-to-day role
2. Spotting use cases for AI – for example, streamlining processes or increasing speed of outputs.
3. Using AI safely and responsibly - protecting sensitive data, understanding ethical considerations, and mitigating risks.
4. Technical skills - to build or develop AI tools, or integrate AI into systems, like data analysis, data engineering, or machine learning.

Why is AI literacy important?

Many employees may well have started their journey to AI literacy– most commonly, they may already be experimenting with generative AI tools like ChatGPT to increase their personal productivity.

But if teams haven’t been equipped with a strong foundation in AI skills, challenges can easily appear.

Taking AI from “toy to tool”

A lack of AI literacy may mean employees struggle to identify use cases for new tech, or select the wrong AI tool for the problem they’re trying to solve.

In this scenario, AI won’t be used to its full potential to deliver real results or solve a genuine business issue. The new technology never fully becomes a tool – it remains a toy.

This can create headaches for teams down the line. Not only can they find themselves with the wrong solution in place, but they’ll also struggle to get the desired value back from any financial or time investment.

Offering AI literacy training can help teams to think critically about how and when to leverage AI, and select the correct solution for their needs.

Mitigating risks

As well as technical skills, employees will require AI literacy training to understand and mitigate the risks associated with the technology.

Leaders and workers cite risk as their top barrier to full AI adoption – yet only a small proportion of leaders strongly agree that their organisation has established best practice in providing governance structures to limit AI risk (28%), and less than half of strongly agree their business is ensuring responsible use of AI in business practices (43%).

Training teams on AI ethics, and how to identify and manage risks around data usage, can help to prevent pitfalls early on.

How build AI literacy across the organisational structure

AI literacy is best considered across the org chart, acknowledging the different types of skills employees may need, depending on their role and seniority.

Team level

A ‘bottom-up’ approach begins with building a strong foundation of AI literacy at a team level – arming teams with the basic know-how to use AI safely and effectively in their day-to-day roles.

At this stage you can also nominate designated AI champions within your teams, responsible for spotting new opportunities for AI use cases, sharing findings, and building your AI Center of Excellence (COE).

To avoid the ‘toys, not tools’ conundrum, those AI champions take an analytical and evaluative mindset to problem-solve through the lens of AI.

Management and leadership level

Business leaders and managers are then involved as they look to place their strategic bets on AI and deliver tangible return on investment from emerging tech.

In addition to developing their individual AI skills, leaders and managers can benefit from additional training in strategic thinking and change management - to help them empower and motivate employees at all levels to adopt AI solutions and use them in a way which aligns with their goals and strategy.

Strengthen AI literacy across your workforce

If you want to unlock potential in your business using AI, it starts with a strong AI literacy foundation.

Discover how to build AI literacy in your organisation with our AI upskilling courses, and equip teams with the essential skills needed to deliver impact from AI.

HCLTech's AI academy aims to upskill its workforce in AI and generative AI (GenAI) to deliver significant business value to clients with AI solutions and boost overall productivity.

The partnership will see select HCLTech employees in the UK embark on a 13-month ‘AI for Business Value’ program, with a focus on business benefits and ethical aspects of AI projects. This initiative aligns with HCLTech’s goal of upskilling 50,000 employees in GenAI by 2025, improving productivity and enhancing client and employee satisfaction.

Upon completion of their training, employees will be better equipped to analyze their AI-integrated performance metrics, fostering a culture of insightful continuous improvement and maximizing individual and team potential.

"This strategic initiative underscores HCLTech's commitment to harnessing AI responsibly to drive business outcomes. By partnering with Multiverse, we are not only equipping our workforce with advanced AI competencies but are also amplifying our capacity for innovation and excellence in service delivery," said Ashish Kumar Gupta, Chief Growth Officer, Europe and Africa, Diversified Industries, HCLTech. "Through this collaboration, we aim to position HCLTech at the forefront of ethical AI deployment, ensuring that our clients benefit from the transformative power of AI while upholding the highest standards of integrity and productivity."

"Capturing the potential gains from AI doesn’t just rely on technology and deploying the right models, it also requires individuals equipped with the right skills to apply it in the real world. HCLTech plays a pivotal role in the global tech arena and their clients depend on its cutting-edge capabilities. By empowering teams with advanced AI skills and instilling confidence, HCLTech and its clients are set to unlock the transformative potential of ethical, precise and productivity-enhancing AI," said Euan Blair, CEO at Multiverse.

Multiverse has trained more than 16,000 apprentices in data and digital skills since 2016.

77% of business leaders say they plan to increase training and development budgets by 2030, according to Multiverse data. As organisations move to adopt new digital workflows and technologies, they have an opportunity to centre employees in their workforce transformation initiatives.

But what steps can HR leaders take to drive workforce transformation efforts, rather than just execute them?

We recently held a panel discussion at our London headquarters, bringing together HR leaders from multiple industries to discuss how we can put our people at the forefront of workforce transformation initiatives.

The panel was composed of Ioana Nicolae, Senior People Specialist at Mastercard, Hayley Crossley, Senior People Specialist at Mastercard, and Paige Rinke, Multiverse’s VP of People and Talent.

We discussed Mastercard’s innovative approach to career development through the ‘Own Your Career’ programme, and the steps HR leaders can take to drive workforce transformation from the ground up.

These are the five key takeaways from our discussion:

Offer on-the-job learning opportunities

Internal movement can be a valuable tool to connect employee skills to the projects that require them. At Mastercard, there is a culture of internal movement – employees are encouraged to explore other roles and areas of the business where their skills may transfer.

Ioana explained: “Internal movement is a great thing – and I think from a personal perspective, it just helps to see how great it is to have different perspectives of the same thing, and there are transferable skills.”

“From every role that you do, you can learn something new, and you can expand your skill set.”

From this idea came Mastercard’s talent marketplace, an internal platform launched in 2022 to match people and skills to projects within the business. Employees upload their CVs, skill sets and desired skills, then AI matches people to jobs that need resourcing.

Hayley told us: “We saw quite a few projects take off, and in that first six months, we had two people actually change their roles because of it and get a role with their new team. It became really apparent quite quickly that this is a great tool to use for people to test their skill set.”

This style of learning helps Mastercard employees to upskill, share knowledge and contribute to workforce transformation on their own terms – participating in the projects that interest them the most.

“As a manager, even if you were to lose a staff member on your team, but Mastercard keeps them, it’s a win.”

Build tailored learning pathways

Every industry has skills gaps. When addressing those shortfalls, learning and development opportunities should be tailored based on what employees need to succeed in their roles and develop in their careers.

Using data from yearly talent reviews and the talent marketplace, Mastercard provides employees with tailored learning opportunities.

For example, Hayley explained that the team’s AI platform can record employees’ owned and desired skills to set up personalised learning pathways through providers like LinkedIn Learning and Harvard Online Courses.

The tool helps employees identify their skills gaps and assess what their next role or project should be to fill those gaps. It helps to build both technical skills and vital soft skills required in day-to-day work, like communication and change management.

Provide smarter mentorship

Mentorship programmes are a common learning and development tool for businesses – but AI adds an additional layer of value. At Mastercard, mentorship opportunities are intelligently matched according to skill set.

It’s not a system where a more experienced manager will simply mentor a less experienced member of the team. Instead, mentorship takes place across multiple departments and levels of maturity. For example, if an employee tells the system they want to build their communication skills, they could be matched to another employee who possesses these – regardless of their level of seniority.

AI-powered mentorship helps support cross-functional learning and builds relationships across departments, levels of seniority and territories – which is critical for a large, dispersed organisation like Mastercard.

Currently, over two-thirds (69%) of business leaders believe that their organisation will need different workforce skills to stay competitive by 2030. Learning through peer expertise could become increasingly valuable as the workforce looks to expand its digital skills and encourage knowledge sharing between multiple generations of the workforce.

Create a culture of employee learning and development

One of the greatest challenges that HR teams contend with is retention. According to CIPD, the average turnover for UK workers – the proportion of staff who move on to a new employer or are not working after a year from hiring – is 34%. It means companies lose talent, and when certain skills are scarce, recruitment can be expensive.

The AI-powered talent marketplace is solving talent retention challenges for Mastercard. The tool helps employees identify, communicate and find opportunities to accelerate their career development, leveraging the resources and budget available to them through initiatives like the Apprenticeship Levy.

A people-first approach to learning and development gives employees autonomy over their career growth, helping them feel supported and more likely to stay with the company. On how Mastercard assesses the value of an opportunity, Hayley said “the one question we ask is, is it going to benefit you in your role?”

Sell workforce transformation projects through your leaders

Equipped with a breadth of workforce data and new AI-powered systems, HR teams are well-positioned to support skills-based workforce transformation. However, business leaders need to be at the forefront of communicating with the organisation and securing buy-in for transformation projects.

When leaders are seen as advocates for learning, and authentically communicate the benefits from the top down, it can help convince decision-makers of the business value of learning and development opportunities.

Ioana highlighted the importance of selling through your leaders. She explained: “If you spend a bit more time with leaders and understand what their challenges are in the business, you have a better idea of how you can match up what they’re missing with what you can add. That’s when they really see the value that HR can bring to the table.”

Since its launch, the talent marketplace has established executive sponsors across the business and engaged staff in transformation initiatives. It has an adoption rate of over 80% within Mastercard, a testament to the success of the project.

Multiverse helps businesses deliver workforce transformation

Upskilling has a central role to play in workforce transformation – and HR professionals are the key facilitators.

Closing the discussion, Paige said, “In the background in HR, we can do the work to help determine skills gaps and what leaders need to be at the forefront of it, but we must make sure that we're really open and honest with the commitment upfront, because it is a commitment, but one that can hopefully be transformational and life-changing.”

The Multiverse team works closely with Mastercard to identify skills gaps and offer upskilling programmes to employees based on their learning and development aspirations.

To learn more about how to align your workforce’s skills with strategic goals, explore Multiverse’s transformation solutions.

The skills needed to thrive in today’s working environment look drastically different to those needed a decade ago.

As technology advances, new innovations like AI have transformed the skills that employees need most, resulting in skills gaps.

It’s a growing problem for business leaders: 48% say their organisation has significant skills gaps across key functional areas of the business. But it’s a solvable one – and organisations can get ahead by identifying, quantifying, and fixing skills gaps in their workforce.

In this article, we’ll unpack what a skills gap is and the different types that exist in the workplace. We’ll also dive into the data – exploring the digital skills gap statistics that demonstrate the scale of the challenge – and how leaders are adapting to meet demand.

Skills gap definition

A skills gap is the difference between the skills that employees possess and the skills that the business requires.

Today, they pose a significant challenge to businesses. According to a recent Multiverse report, 68% of business leaders anticipate gaps in key tech and data areas heading into 2030. Half (49%) believe these skills gaps will have a negative impact on key business performance metrics including profitability, employee retention, and customer satisfaction.

As a result, leaders are reordering their strategic priorities. Currently, they rank learning and development as their fifth largest priority, rising to fourth when looking ahead to 2030.

Read the full report for more insights and learn how to build the future workforce of 2030

Types of skills gaps

Our data suggests that organisations are currently struggling to address skills gaps across several business-critical areas, spanning both technical and soft skills.

Examples of technical skills gaps in the workplace

A technical skills gap is the difference between the technical skills employees have and those the business needs, especially relating to abilities in certain software, technologies, or processes.

Modern organisations are affected by skills gaps encompassing a range of specific technologies and platforms. Key areas where technical skill gaps are most acute include:

Artificial intelligence (AI)

AI skills gaps occur when workforces lack the skills to develop, deploy, or manage AI systems effectively. These include expertise in machine learning, data engineering, and solution design. Currently, leaders name AI as their most significant skills gap (45%).

Data

Data skills gaps occur when organisations lack the necessary skills to organise, store, and govern data effectively. 77% of leaders say data management is the skills gap most likely to persist into 2030.

Many organisations also have skills gaps when it comes to standard workplace productivity software. According to the Multiverse Skills Intelligence Report 2024:

• 57% of employees have basic or no Excel skills.
• 55% have no PowerBI or Tableau skills.
• 86% have no Python skills.

Cybersecurity

Cybersecurity skills gaps exist when organisations lack skills in protecting digital assets, data, or systems from cyber threats. Abilities in areas such as network security and threat detection are crucial to building a strong cyber posture, and business leaders name cybersecurity as their second largest skills gap (35%).

Cloud computing

Cloud computing skills gaps refer to a lack of skills for designing, managing, and optimising cloud-based infrastructures across platforms like AWS and Microsoft Azure. Leaders name cloud computing as their third largest skills gap (28%).

Examples of soft skills gaps in the workplace

Beyond technical abilities, workforces may also have skills gaps across soft skill areas. A soft skill gap is the difference between the non-technical abilities employees have and those the business needs.

A recent Multiverse survey on the power of on-the-job learning revealed that business leaders see soft skills as the largest predictor of potential – with leaders twice as likely to prioritise durable skills (64%) over degree results (27%) when assessing applicants for junior roles.

When asked to name the three most important soft skills their companies will need over the next five to 10 years, leaders cited the following skills gaps:

Critical thinking

Critical thinking skills gaps arise when employees lack the ability to analyse business problems and assess solutions effectively. 37% of business leaders consider it one of the top three most important skills their organisation will require.

Communication

Skills gaps in communication refer to the ability to clearly and effectively convey information, verbally or in writing. As remote and dispersed workforces become more common, 37% of business leaders name communication as a top priority.

Adaptability

Adaptability skills gaps emerge when employees struggle to adjust to new technologies or working processes. 35% of leaders see adaptability as a crucial skill for their future workforce.

Creativity

Creativity skills gaps are present when organisations lack the ability to generate innovative ideas or solve problems in novel ways. 34% of business leaders believe creativity will be critical for success over the next five to 10 years.

Why is it important for businesses to close skills gaps?

Over two-thirds (69%) of business leaders believe that their organisation will need different workforce skills to stay competitive by 2030. But to effectively implement new technologies like AI, workforces need new skills – both technical and soft.

When skills are missing, leaders see risks to business success. Half of leaders believe a lack of AI skills will negatively impact revenue growth (50%), productivity (50%) and profitability (49%).

How to identify and fix skills gaps

To maintain their competitive foothold, organisations can invest both in emerging technologies and the skills needed to implement them. 77% of leaders say they plan to increase training and development budgets by 2030. As a priority, 83% say their organisation is moving quickly to implement AI skills development.

Many choose to develop employee skills through upskilling or reskilling programmes. Upskilling refers to expanding existing skills and knowledge to stay competitive and relevant in the workplace, while reskilling is the process of building brand new skills and knowledge unrelated to your current skill set.

However, even though they recognise they have skills gaps, some businesses struggle to assess where those gaps are. As a result, decisions made to close gaps are often top-down and heavily influenced by guesswork or industry trends.

The Multiverse team can help map your skills gap with speed and precision. Book a consultation to identify your skills gaps today.

The AI for Business Value programme apprenticeship aims to equip team members from business functions across the organisation with advanced, industry-relevant AI and machine learning capabilities. Delivered by the tech-first company Multiverse over a 13-month period, the AI for Business Value programme trains apprentices to identify business value gains that can be achieved through using AI and executing ethical AI projects.

The training is part of The Crown Estate’s ambition to better utilise AI to drive value for the nation. A significant national landowner, The Crown Estate delivers financial value to the Treasury and creates wider environmental, social and economic value for England, Wales and Northern Ireland through its diverse £16bn portfolio that includes urban centres and development opportunities; one of the largest rural holdings in the country; and Windsor Great Park. It also manages the seabed and much of the coastline around the same parts of the UK, playing a major role in the country’s world leading offshore wind sector.

Participants on the AI for Business Value programme will be embedded across the organisation, delivering AI innovation and utilising real-time data in areas ranging from administration and property management through to urban design and marine planning.

The programme will enable teams to identify new opportunities to improve operational and design efficiencies, reduce emissions and carry out optimum planning, among other strategic outcomes, supporting The Crown Estate’s objectives on net-zero, economic growth and productivity and stewarding the UK’s natural environment and biodiversity.

With businesses predicting that almost half (44%) of workers’ core skills will be disrupted by 2027, with AI widely reported to be a key disrupter, the training will also enhance the careers of apprentices who are enrolled, empowering them with the most in-demand skills in the economy today, and allowing them to act as champions for AI within the organisation.

Aruj Haider, Head of Digital Emerging Technology & Innovation, The Crown Estate, said: “AI represents an enormous opportunity for us, that will increase our ability to effectively serve the country and give a huge boost to our efficiency and capability to achieve net zero and grow our productivity. This training will unlock our team’s ability to define the role AI will play in our organisational journey. Just as importantly, it gives our people access to some of the most in-demand skills in the workplace today.

“At The Crown Estate, our AI strategy is geared towards developing the skills, mindsets and behaviours to use AI effectively within our organisation. This apprenticeship is a key marker on that journey, and I really look forward to seeing some of the plans and impacts participants make on this programme over the next 13 months.”

Multiverse is a new tech-first institution that combines work and learning to unlock economic opportunity for everyone. It works with more than 1,500 organisations to close critical skill gaps in the workforce in AI, data and tech, through a new kind of apprenticeship.

Gary Eimerman, Chief Learning Officer, Multiverse said: "The Crown Estate has recognised the potential of AI to upscale innovation and increase efficiencies across its portfolio. The skills development provided is empowering the Crown Estate team members to use emerging technology to achieve their aims; while also enriching their career opportunities.”

According to the World Economic Forum’s latest Future of Jobs report, almost two-thirds of companies globally predict AI will grow in importance, with AI and big data the number one priority for company training strategies with more than 50,000 employees. It’s becoming ever more critical for employers to heed the advent of AI, both to harness the numerous benefits it can yield for their business and to prepare their people for the future of work.

The partnership will deliver AI and data programmes for over 50 professional services staff, as part of a drive from the University to bolster areas including student recruitment and student experience while developing a team of AI and data literate colleagues through at-work upskilling.

Training is funded by the apprenticeship levy and delivered by Multiverse, a tech company that specialises in high-quality training through applied learning. Multiverse has trained more than 16,000 apprentices in data and digital skills since 2016.

Enrolled employees have been assessed on their suitability for five of Multiverse’s programmes, with an assessment carried out for each person based on existing skill level, seniority and role within the university.

Programmes include the 13-month ‘AI for Business Value’ level 4 apprenticeship, which will help learners to identify business value gains that can be achieved through using AI and how to execute AI projects responsibly.

The Data Fellowship (standard or advanced) will upskill employees in data analysis and data science, while the Business Transformation Fellowship will help Keele University to deliver strategic initiatives with an agile mindset and drive change in an evolving digital workplace.

In addition to establishing a culture of AI and data literacy across the university, Keele hopes support its future strategy through the automation of manual processes and the use of newfound skills to identify cost-and-time-saving opportunities.

According to Multiverse’s Skills Intelligence Report, the education sector is most impacted by a lack of data skills, with 38% of employees’ time working with data spent unproductively, compared to the average of 30% across 18 other sectors.

Tom Wilcock, Director of Transformation for Professional Services at Keele University, said: “Keele University is always looking to invest in enriching initiatives that improve our students’ experience. The new partnership with Multiverse will allow us to do just that by upskilling over 50 of our exceptional professional services personnel.”

Multiverse is a tech-first institution that combines work and learning to unlock economic opportunities for everyone. It works with more than 1,500 organisations to close critical skill gaps in the workforce in AI, data and tech, through a new kind of apprenticeship.

Gary Eimerman, Chief Learning Officer at Multiverse said: "Our recent report shows that education is the hardest hit sector when it comes to the data skills gap. Keele University’s investment in AI and data training will close this gap, empowering staff with key skills to deliver the best outcomes for Keele and its students.”

Why? We know this because of the lessons learned from digital transformation.

One of the common reasons digital transformation initiatives fail is a lack of consideration for the "people dimension." Over the last 10 to 15 years businesses have learned and appreciated the importance of bringing people along with new technology.

The same principle applies to AI, and we see many similarities today with those early days of digital transformation. For example, business leaders see a chance for enhanced performance and growth with over two-thirds of leaders believing AI will improve productivity and customer experience (69%).

But challenges come with change management – and lessons from the past should be considered.

Workplace culture – built for its people – is crucial for success with AI, but there’s no switch to turn it on immediately. It needs nurturing, with time, effort and consistency.

In this article, we’re going to explore what a strong workplace AI culture looks like, and some suggested steps on how to establish it.

What is workplace AI culture?

Workplace AI culture is the integration of artificial intelligence technologies into an organisation's operations, processes, and employee interactions. In a strong workplace AI culture, teams will constantly consider how AI can and should be used within the business, shaping the overall work environment and company values.

How to establish a strong AI culture

Building an AI culture requires careful planning, clear communication, and a commitment to responsible practices and continuous improvement.

Every employee needs to understand how AI is relevant to their role, how they can use it effectively, and crucially, how to use it responsibly. And, for leaders, it’s about fostering and nurturing this culture by regularly considering how AI plays into their business strategy.

Here are our five steps to building a successful workplace AI culture:

1. Understand your level of AI readiness

Around seven in ten (69%) of business leaders believe their organisation will need different workforce skills to stay competitive in 2030 – according to Multiverse’s ‘Preparing for the AI revolution’ report.

In the same study we found nearly half of leaders (48%) say their business currently has significant skills gaps in key functional areas. Mapping these gaps to inform your approach can be included in an AI readiness assessment.

By looking at people, processes and technology you can understand areas of focus for establishing your workplace AI culture.

2. Build a network of AI champions in a ‘hub and spoke’ model to enable experimentation

Structure is important to help everyone understand their stake in AI – as well as to track progress on how AI is being used.

It becomes easier for an organisation to show this in practice when using a hub and spoke model. A team of champions around the organisation (the spokes) can channel information back to a strategic AI lead acting as the ‘hub’. The strategic AI lead must have authority and enough proximity to senior leadership to align the business’ strategic goals with the application of AI.

The supporting network of AI champions is effectively the frontline of change management. By placing these subject matter experts in each business function, it’s clear to every team who they need to speak to when they have an AI question. This group can act as the eyes and ears on the ground – spotting opportunities and working with the right people to develop a business case for AI.

3. Set positive expectations with clear AI policies and guardrails

Risk is an ongoing concern for leaders looking at AI – particularly data security.

Only around 21% of businesses have established workplace policies around employee use of Generative AI according to McKinsey. So, being clear about what information can be shared on ChatGPT, for example, helps everyone understand the appropriate use cases for AI and rules of engagement.

As well as marking out the red lines, communicating clear boundaries means the average worker can understand the spaces where they can innovate and experiment with AI – setting a positive culture rather than a restrictive one.

4. Empower continuous learning and AI upskilling

Advancements in AI are happening at a lightning pace – it’s why 83% of businesses are moving quickly to implement workforce skills development on AI.

Building a culture of learning into your AI culture encourages everyone to understand the places they can improve, and access opportunities to grow.

Factoring in time for learning as part of everyday roles means there is space for experimentation.

Clear communication on your plans for AI implementation needs to go alongside any training and support to help employees adapt.

5. Measure impact – and share what you’ve learned

Measurement is important to support the experimentation element of your AI culture. Similarly to those early days of digital transformation, there can still be lots of hypothesising about the impact AI may have as a whole or on individual processes.

Being clear with your employees on the impact you want to achieve, and the metrics you’re focused on improving, arms teams with the information to assess opportunities and make the case for future AI investments.

Take your first step in building a strong workplace AI culture

Book a consultation with our team of experts, who can help you to build a strong workplace AI culture.