• Louise Scott-Worrall, Partner |
10 min read


Enterprise learning is evolving at speed. Economic uncertainty, ground-breaking technologies, hybrid working and multi-generational teams are bringing about three fundamental shifts:

  1. The transformative capabilities of generative AI
    How can learning functions support the AI-enabled workforce – and use AI themselves to become more effective and efficient?
  2. The transition to skills-based organizations
    What does the move to skills-based operating models mean for what learning functions must achieve, and how?
  3. The increasing expectations of employees
    How can learning in the flow of work help to meet employee demands – especially those of Gen Z workers?

These forces are leading to huge change in how learning is designed and delivered, which is placing multiple demands on learning leaders. To meet the needs of learners and the business, they must:

  • Support the transformation required to build a skills-based enterprise
  • Deliver learning in the flow of work, and at the point of need
  • Embed learning into the employee experience and value proposition
  • Ensure that learning improves productivity, engagement and performance

Against this challenging backdrop, KPMG and Microsoft hosted our latest Future of Learning roundtable in October 2023.

The event was led by Louise Scott-Worrall, Head of Learning Solutions at KPMG UK. Learning leaders from a wide range of industries explored key trends in workplace skills and learning; the latest technological innovations; and what it all means for them.

The rise of the skills-based organisation

Freneka Mumford, Director of People Consulting at KPMG UK, examined the need for businesses to adopt skills-based operating models in response to far-reaching change. She highlighted three key factors that are driving this:

  • The pace of technological disruption
    Though still a relatively new technology, generative AI’s adoption rate has been astonishing. As a result, almost half (44%) of workers’ skills will be disrupted by this technology over the next five years.
  • The growth of ‘quiet hiring’
    In the face of the global skills shortage, a third (34%) of companies see reskilling and upskilling as crucial to increasing the availability of talent. And that proportion will only increase. As a result, reskilling and upskilling are becoming core business practices.
  • Employees’ needs and expectations
    Half (51%) of Gen Z staff say education hasn’t prepared them for the workplace. Meanwhile, trends like ‘quiet quitting’ and the ‘lazy girl job’ reflect a workforce that’s happy to do just what’s required – all of which causes an engagement challenge.

So how can businesses make the transition? According to Freneka, the answer lies in establishing the four cornerstones of a skills-based organization:

  1. Skills data: Technology alone won’t accelerate learning transformation or enhance outcomes. There’s a foundational requirement: data. To be effective, learning solutions must be fed with complete and accurate data on the skills within the organization.
  2. People processes: Skills must be embedded into HR processes – recruitment and reward being good start-points. Focus your hiring processes on skills, aptitude and attitude, not qualifications. And adapt your reward framework to attract the right skills, rather than just filling vacant roles.
  3. Ways of working: Breaking down traditional, functional silos will make it easier for staff to use their skills and talent to deliver the tasks they’re asked to perform.
  4. The learning experience: If interacting with your learning system and talent marketplace is cumbersome, then employees won’t do it. Providing a compelling offer will mean integrating an experience layer into your tech stack.

Making the skills-based transformation

Implementing the building blocks of a skills-based operation is complex: there’s a lot to plan, design and implement. As Freneka pointed out, it’s a full-blown transformation project, which will require businesses to:

  • Frame the context
    - Set and communicate clear objectives, and a vision for the transition to a skills-based model that will future-proof the organisation.
    - Establish a common language to describe your key skills, and ensure that it’s understood throughout the enterprise.
  • Map the skills landscape
    - Gather the data you need to understand your skills profile and requirements.
    - Identify any gaps – this will form the foundation for your transformation.
    - Map your skills and job architecture, to know who your internal candidates are, and where you need to recruit.
  • Gain and deploy the necessary skills
    - Analyse your skills gaps to direct your investments accordingly, and inform your talent sourcing decisions (build, buy, borrow, bot).
    - Rethink how you will attract hard-to-find abilities – for example, by running special events and challenges designed to attract certain competences and mindsets.
    - Use upskilling and reskilling as an acquisition, engagement and retention tool.
    - Introduce a talent marketplace to guide investments, workforce planning, and talent management.
  • Incentivise the right skills
    - Reframe your reward system to tie compensation to skills, not tenure; and to encourage staff to gain the capabilities the business needs.

As firms look to make this transformation happen, they’re exploring the possibility of formal recognition of the most valued skills. Businesses and learning vendors are looking at how to establish such validation schemes.

Simon Lambert, Chief Learning Officer at Microsoft UK, believes that AI could be a gamechanger in this respect. But in the meantime, it remains a challenge, for two principal reasons. Firstly because “nobody has cracked proficiency yet”, as one attendee put it. And secondly, because once an approach is found, “scaling it will be a real issue,” in the words of another participant.

The role for learning leaders

Learning leaders have a key part to play in supporting the transition to skills-based operations.

Your first priority must be to understand the business strategy – and the skills it will require – before thinking about the learning content you need to deliver.

From there, focus on experience curation, not content creation. When knowledge is easier to access than ever, the learning experience is what really counts.

You’ll also need to democratise access to training through learning marketplaces, which match content to individuals’ current and future needs, and their career aspirations.

All of which will require you to get curious about, and comfortable with, all things technology – particularly AI.

In tackling these imperatives, it’s important to realise that your learning experience platform (LXP) won’t be the answer to everything. To enable the skills-based organisation, LXPs will themselves need a significant overhaul, with a focus on those all-important data inputs. Your learning curriculum, quality and outcomes can’t be transformed simply by adding a layer of technology.

The engagement factor

The post-pandemic era – marked by economic and geopolitical uncertainty – is seeing a shift in the focus of work.

According to Simon, the priority businesses gave to wellbeing and flexibility during lockdowns is fading. It’s giving way to an emphasis on productivity and accountability.

This “productivity vs. engagement tension” is visibly playing out in the workplace,.

Many of us wish to maintain the flexible working patterns we adopted during the pandemic – but at the same time, we value an element of human connection. Meanwhile, organizations have access to increasingly robust metrics on which tasks are best done where.

What’s more, there’s a stark difference in how employees and their employers view their productivity. Some 87% of staff claim they’re productive – yet only 12% of leaders agree.

On the engagement front, meanwhile, the Great Resignation goes on: 40% of employees have left. or are considering leaving, their job since the pandemic.

The reality is that focusing purely on productivity risks stifling innovation and causing burnout. Performance is a product of both engagement and productivity.

With this in mind, Microsoft investigated the link between employee engagement and financial performance over 2022. They found that firms scoring strongly for engagement on staff surveys outperformed those with lower ratings. This gave their share price a resilience when the stock market was falling sharply last year.

Listening to engagement

Microsoft’s study suggests that sustainably improving the bottom-line means enhancing engagement as well as productivity. In Simon’s view, engagement must be built on a number of factors: clarity of mission and goals; connection and community between workers; a positive working environment; and a culture of wellbeing and psychological safety.

Keen to monitor engagement among its own employees, Microsoft has created a ‘thriving score’ to keep tabs on how they’re doing.

This is made up of three components:

  1. Active listening: An annual ‘signals’ event measures how well individuals are thriving. For example, are they doing work that’s meaningful to them, and gives them a since of purpose?
  2. Frequent pulse surveys: A regular outreach to smaller groups asks the same questions each time. Microsoft makes the results available to all staff, so they can see how the culture is moving towards where the company wants it to be.
  3. Passive listening: Microsoft monitors what Simon calls the “ambient signals” as people interact with their workplace technology. Teams generates trillions of data points on who they’re meeting with, how they’re collaborating, the sentiments they’re expressing, and much more.

Learning and skills in the age of AI

Ben Gibbs, Employee Experience Specialist at Microsoft UK, looked at the impact of AI on how learning can deliver the skills an organisation needs.

He described generative AI as a “streamlining collaborator” – which can automate work, generate content, produce insights and spark creativity. It will remove drudgery from many roles, and free people up for higher-value work that needs human skills and judgement.

“We’re in the era of the AI co-pilot,” he told participants.

Inevitably, such a disruptive technology is prompting both fear and enthusiasm. Microsoft research revealed that almost 49% of workers fear for their job security due to the emergence of AI. Yet 70% would gladly use it to reduce their workload.

In Ben’s experience, many customers are asking the same three questions of Microsoft when it comes to AI skills:

  • How can you help us to upskill for AI?
  • Where can I find the next generation of tech talent?
  • How can I do these things fast?

Partly in response to this demand, Microsoft is pioneering a new mapping tool, which combines data from LinkedIn and Viva Skills – a new feature on its Viva employee experience platform.

The tool uses AI to analyse workers’ activities and identify their strongest skills. It then maps this data to LinkedIn’s Skills Graph. This gives users a view of the abilities needed to achieve their organisation’s strategy, and crucially, where to find them.

Challenges for learning leaders

Simon finished the session by exploring two of the biggest challenges currently facing learning leaders – according to research from the Learning Performance Institute:

1. Building a Learning culture

The average life expectancy of a skill, and the average job tenure, are now less than four years.

That makes effective demand planning crucial. You must have the mechanisms to manage your learning curriculum, so that your content evolves in line with business needs. And you must ensure that your learning culture is agile enough to embrace technology like AI – while continuing to use the tools already available.

How can learning leaders make sure this happens – while staying focused on delivering the right outcomes?

For one attendee, it meant having protected learning time built into the weekly schedule for all employees. Another stressed the importance of senior leaders acknowledging their own skills gaps; acquiring the abilities they’re missing; then sharing their learning experience. “That makes everyone feel more comfortable to go out and learn.”

2. Learning in the flow of work

Ben outlined Microsoft’s experience of how the firm created a step-change in the delivery of learning in the flow of work.

Previously, staff learned in a “system of support” (the learning management system) – rather than the “systems of productivity” where they actually work (such as Teams or Office).

This was pulling people out of the flow of work whenever they needed to access training and support.

Microsoft’s answer was to integrate training, resources and performance support into systems of productivity through Viva Learning. That helped accelerate the consumption of training content, while placing it in the right context.

Questions for learning leaders to consider

Artificial intelligence

  • How can the learning function in supporting an AI augmented workforce?
  • How can we improve our confidence and competence with AI?
  • What efficiencies can AI help the learning function to achieve?  
  • Where should we prioritise our AI investments?

Skills-based operations  

  • What do we actually mean by becoming a skills-based organisation?
  • What enablers will we need to put in place?
  • How will this impact what learning needs to achieve – and how we deliver that?

Employee expectations

  • What do our Gen Z employees expect from workplace learning?
  • How can we deliver learning in the flow of work?