The Multiverse blog

South Gloucestershire Council is doubling down on efforts to leverage technology and drive efficiencies by training more of its team members in AI and data skills. Following a successful pilot programme, delivered by Multiverse, the council has extended the training, bringing the total number of learners to 60 in efforts to continue improving local services for South Gloucestershire residents.

The Transformation Academy builds on initial training to equip more of its people with the skills to enhance organisational performance, modernise processes and secure cost savings, extending the scope of training to feature AI programmes. Digital skills gained from these courses have already seen team members secure thousands of pounds worth of savings across the council, and hours of time through increased efficiencies.

Multiverse’s Skills Intelligence Report found that nearly 30% of local government employees’ time working with data is spent unproductively. This skills initiative marks South Gloucestershire Council’s efforts to empower its employees with the training they need to drive greater efficiency and impact, in turn benefiting local residents.

The new academy will see staff enrolled from all three of the major areas of the Council, such as the ‘People’ Directorate, including Housing, Children and Adult’s Care, Education and Public Health, as well as Resources and Business Change and the 'Place' Directorate, which includes Planning, Place Shaping, Operations and Streetcare. This demonstrates the broad-reaching efforts to upskill the organisation’s data and AI capabilities, which will ensure decision making is evidence-based and existing manual processes are streamlined.

Key to the new cohort’s training will be the inclusion of AI programmes, such as the Level 4 AI for Business Value and Level 3 AI Powered Productivity. These programmes will introduce AI fundamentals and boost engagement with tools like Microsoft 365 Copilot and Gemini, building on the success of previous training.

Programmes also include ‘Data Insights for Business Decisions,’ which equips teams with the technical skills and knowledge to confidently navigate the data landscape, and the 13-month ‘Data Fellowship’, which is a Level 4 apprenticeship upskilling data-literate staff into high-performing analysts and data science professionals.

Nigel Riglar, Executive Director of Place at South Gloucestershire Council said: “This training is already helping us make better decisions, cut costs, and modernise how we work. By adding AI skills, we’ll go even further in delivering the best service for our residents.”

Gary Eimerman, Chief Learning Officer at Multiverse said: “Our research shows that many councils struggle with a data skills gap. Through this Data & Business Academy, South Gloucestershire Council will give its team members boosted confidence in data, ultimately enabling them to deliver better service outcomes for local residents.”

We are the upskilling platform for AI adoption, and that begins right here, with our own team. If you're looking to not just participate in the AI revolution but to lead it, you've found your home.

Why AI at Multiverse is different: Your opportunity to drive impact

We're taking a fundamentally different approach to AI. We don't just talk about AI, we embed it into our very DNA. Our commitment to upskilling for AI adoption isn't just for our customers; it's a core part of how we build our own world-class team.

We understand that AI skills are in high demand, and they come at a premium. But we also recognise that when a technology is advancing as fast as AI, a willingness to continually learn is just as crucial as existing skill. Without constant upskilling, even those who are advanced in AI today stand to fall behind.

Our unique approach to hiring and onboarding ensures we bring in not only individuals who are already proficient in AI, but also those who possess the curiosity and drive to explore its possibilities.

How we're investing in your AI journey: Consequential growth from day one

We're evolving our hiring and onboarding to ensure that every new Multiverser is set up for success in an AI-driven world. Here’s how our unique approach will benefit you, delivering tangible, measured outcomes for your career:

Smarter hiring: Recognising your true AI potential

Our enhanced interview process goes beyond basic checkboxes. We've integrated AI acumen into our core competency framework, assessing your proficiency with a nuanced, tiered approach:

• Foundational Skills & Explorative Mindset: You're keen to learn and ready to engage with Generative AI tools. Your "will" to embrace AI is what matters most here.
• Deeper Expertise & Frequent Use: You consistently use AI tools in your work and demonstrate a solid understanding. Here, we're looking for both your "skill and will."
• High Proficiency & Leadership: You're not just using AI; you're leading the way, pushing boundaries, and inspiring others. We see you as an AI leader.

This tailored assessment, incorporated into our interview questions and tasks, means we understand your starting point and can better support your growth, aligning with our commitment to driving impact through learning.

Bespoke onboarding: Accelerating your AI capability with impact

Forget generic training. Once you join Multiverse, your AI journey is personalised based on your assessed skill level, ensuring you get the most relevant and impactful development from day one:

• Pathway 1: If you're coming in with a strong "will" and foundational AI understanding, we'll fast-track your learning. Within your first three months, you'll complete four essential "Everyday AI" modules and dive into our intensive "AI Skills Accelerator" programme. This pathway is designed to rapidly upskill you, transforming your curiosity into concrete capability and demonstrating our belief that learning should drive impact.
• Pathway 2: For those with deeper expertise and a track record of high proficiency, you'll directly engage with the "AI Skills Accelerator" in your third month. This timing ensures you have the foundational business context to apply your advanced AI skills for maximum impact, making you an immediate driver of innovation.

This isn't just about training; it's about cultivating a workforce that is truly AI-proficient and future-ready, embodying our mission to empower the workforce with AI. We're committing to helping you become the most AI-enabled professional in your field, unlocking new levels of productivity and innovation.

Join us: Shape the future of work with multiverse

If you're ready to be part of an organisation that genuinely invests in your growth and empowers you to lead in the AI era, Multiverse is the place for you. We're not just hiring for today: we're hiring for the future, and we invite you to build that future with us.

If all those responsibilities make you feel overwhelmed, you’re not alone. Nine out of ten UK employees say they’ve experienced high or extreme pressure in the last year.

You probably can’t cut your to-do list in half — at least, not if you want to advance your career. But you can get more done with less stress with these time management tips.

Spotting the signs of poor time management

Sometimes, it’s hard to recognise that your time management skills are lacking. Sure, you might be crossing things off your list and meeting most of your deadlines. But that doesn’t necessarily mean you’re being productive — or finding a healthy work-life balance.

You probably need help managing your time if:

• You’re always scrambling to hit deadlines at the last minute.
• Most days, you add more to your agenda than you finish.
• Important tasks at home keep getting overlooked, until you realise you haven’t vacuumed in weeks.
• You constantly stay late at the office or spend half your Saturday working to get everything done.
• Sometimes, you don’t even know what to start working on.
• You rarely have time to upskill, so you feel like you’re falling behind your colleagues.

Look out for sneaky time wasters, too. You might spend hours reading emails or trudging to boring meetings. Or maybe you’re multitasking all the time, like typing out a memo while you nod along in a Zoom meeting. These nonproductive activities may make it seem like you’re doing a lot, but they’re actually making you less efficient.

8 ways to take back control of your schedule

You can’t pick and choose all your tasks, but you can control how you handle them. Get ahead with these simple time management strategies.

1. Set clear goals and priorities

Creating goals is the foundation of effective time management. They help you prioritise tasks and say no to things that won’t help you move your career forward.

Use the SMART framework to set professional and personal goals that are:

• Specific - Imagine what you want to achieve in detail.
• Measurable - Make sure you can easily track your progress.
• Achievable - Pick something you can realistically accomplish with your current resources.
• Relevant - Your objectives should fit your long-term career plan.
• Time-based - Set deadlines and milestones.

Let’s say you’re a Software Developer with a mile-long debugging backlog. You could aim to clear out half of it in two months by fixing at least five bug reports a week.

Once you’ve got your big goals, don’t just stick them at the top of your to-do list. That’s too intimidating. Instead, break them down into bite-sized tasks that you can chip away at. Want to clear out hundreds of unread emails in your inbox? Schedule two blocks a day to answer and delete messages, and set time limits so you don’t get lost reading months-old emails.

As you work on your goals, the Eisenhower Matrix can help you spot high-priority activities. It sorts tasks into four quadrants:

For example, reading random e-newsletters goes in the “delete it” category, so use the unsubscribe button liberally. A time-sensitive client email, on the other hand, needs an immediate response.

2. Build a realistic weekly schedule

A digital calendar can significantly improve time management at work and in your personal life. Choose a mobile-friendly platform like Google Calendar so it’s always accessible.

Before you open your calendar, write down all your upcoming tasks and sort them by priority, like this:

• High: Client presentation on Friday, report due Monday morning
• Moderate: Daily standup meetings, study sessions for learning data analysis skills, walking the dog every evening
• Low: Checking email, putting away laundry

Estimate how much time you’ll need for each item, and be honest with yourself. If that detailed report usually takes four hours, don’t say you can do it in three, or you’ll just feel stressed.

Use this list to start mapping out your weekly schedule. Create colour-coded time blocks for similar tasks — like meetings and presentation prep time — so you can see what’s coming up at a glance. Schedule at least a few hours a week for deep focus, too, so you can work on creative tasks without interruption.

And don’t forget to pencil in plenty of breaks and buffer time. Sure, you could rush to six back-to-back meetings, but you’ll probably feel too drained to work on anything else. Regular breaks reduce stress and improve your overall well-being.

3. Tackle challenging tasks first

You’ve got limited energy, no matter how much coffee you chug. Start your day by “eating the frog” — a.k.a starting with the hardest or most urgent tasks on your list. This helps you build momentum and frees up time later for routine tasks.

The Pomodoro technique can help you maintain focus for those big tasks. It breaks work into 25-minute intervals, followed by five-minute breaks. After you complete four pomodoros, take a longer 30-minute break. This strategy lets you accomplish tasks faster without burning out.

Whenever possible, avoid packing your schedule with too many difficult tasks. Quality over quantity is key to protecting your mental health and productivity.

4. Minimise distractions

While most time management tips focus on doing more, you should also cut down on tasks that sap your attention. Social media and texting are two of the biggest culprits. Turn off notifications during focus time and use app blockers to stop yourself from scrolling on TikTok for “just five minutes.”

A tidy workspace can also help you concentrate. Get rid of clutter, such as random bobbleheads and knick-knacks, and create quiet zones free from unnecessary tech.

5. Use the right tools

Many professionals use time management tools to stay organised. Here are just a few options:

• Toggl Track to record your time and see where it’s going
• Digital calendar apps to schedule tasks and set reminders
• Forest to encourage you to put your phone away and focus
• Todoist to track and manage tasks

Experiment with a few programmes to see what works best, but don’t feel like they’re mandatory. If old-fashioned sticky notes and written calendars boost your productivity, stick with that.

6. Organise notes and tasks in one place

Nothing wastes time like searching for a scrap of paper on a messy desk — or worse, trying to remember something that your boss told you three weeks ago.

Save time by jotting everything down in a digital note-taking app like Notion or Google Keep. Keeping everything together decreases stress by making sure you always have clear, up-to-date information.

7. Avoid procrastination with small wins

Nothing kills motivation like slogging through an ocean of tasks. Give yourself something to celebrate by setting micro-goals. A major white paper might take days to complete, but treat yourself to a fancy coffee after drafting each section. Little victories will help you stay motivated and recognise your progress.

Don’t let perfectionism paralyse you, either. Just start, and tell yourself you can always fix it later.

The two-minute rule also stops little tasks from piling up. If something takes less than a couple of minutes, do it right away, even when you don’t feel like it.

8. Review and adjust your system

Mastering time management won’t happen overnight, especially if you’re a chronic procrastinator or easily distracted.

Start small by choosing just two or three of these practical strategies to increase productivity. At the end of each week, spend 10 minutes reviewing your progress and analysing how you’re spending time.

Not making progress? Try new time management apps or switch up how you prioritise tasks. You could even use AI to automate basic tasks like sending appointment reminders to clients.

Above all, flexibility is key. Your personal life may get busy, or you might decide to focus more on upskilling. Adapting your time management system will keep everything moving smoothly.

Apply these skills in your Multiverse journey

Time management skills can benefit all professionals, but they’re especially critical for apprentices. Techniques like time blocking and the Pomodoro method will help you balance work, training, and projects.

Multiverse’s free Project Management and Transformative Leadership apprenticeships allow you to apply and build these valuable skills. You’ll learn how to delegate tasks and identify areas for improvement in your organisation. These hands-on programmes also help you future-proof your career with in-demand AI and leadership skills.

Complete our quick application to learn more about how a Multiverse apprenticeship can improve your time management.

As companies invest millions into artificial intelligence, reports from sources such as MIT are beginning to suggest that over-reliance on generative AI can reduce critical thinking. This resulting human skills deficit could itself threaten the effective adoption of AI if not properly addressed, according to findings published today by learning scientists at upskilling platform Multiverse.

The researchers found that creativity, analytical reasoning and systems thinking are among the 13 human skillsets required for the workforce to successfully adopt AI. These sit alongside technical skills such as prompt engineering, AI model evaluation and AI process modelling, and hold the keys to effectively bringing together people and technology to drive value.

The findings were uncovered through qualitative and observational research with AI power-users, alongside expertise derived from upskilling thousands of workers in the use of the technology. The resulting skills framework will support workers and organisations looking to improve their AI maturity – their ability to deliver meaningful impact with AI.

Accenture predicts that AI could contribute £736 billion to UK GDP by 2038, but also notes that leading companies are nearly twice as likely to prioritise ‘soft skills’. A substantial gap between AI’s potential and the human skills required to use it effectively could therefore represent a major risk to UK productivity and growth.

“Leaders are spending millions on AI tools, but their investment focus isn't going to succeed. They think it's a technology problem when it's really a human and technology problem. Without a deliberate focus on capabilities like analytical reasoning and creativity, as well as culture and behaviours, AI projects will never deliver up to their potential," said Gary Eimerman, Chief Learning Officer at Multiverse. "This framework provides a new model for talent development in the age of AI, which must include human skills as well as technical skills in order to drive tangible business results.”

Focusing on the requirements for effective collaboration between humans and AI, 13 human skills have been identified as critical to support technical AI adoption. These form part of Multiverse’s broader skills taxonomy, a hierarchical system mapping the skills required for success in the digital era.

The most essential human skills identified for meaningful AI adoption are:

Cognitive skills: Mental abilities used for learning, reasoning, problem-solving, and decision-making.

1. Analytical reasoning: Breaking down complex information for AI to more effectively deliver its instructions; recognising tasks that AI is not suitable for.
2. Creativity: Pushing the boundaries of AI use and experimenting with new approaches to drive innovation.
3. Systems thinking: Identifying patterns in AI performance to predict how AI will respond to a task.

Responsible AI skills: Applying ethical principles to ensure the responsible use of AI, considering its impact on individuals and society.

1. AI ethics: Spotting bias and recognising how it affects AI outcomes; using AI outputs in an ethically sound way to inform business recommendations.
2. Cultural sensitivity: Identifying when AI outputs lack sufficient geographic or cultural awareness.

Self-management skills: Recognising thoughts, values, feelings, and behaviours, and how they impact the ability to achieve objectives when using AI.

1. Curiosity: Examining the broader context and requirements of a task to augment AI outputs.
2. Self-regulated learning: Reflecting on the success of a chosen AI approach; partnering with AI to self-assess its outputs.
3. Detail orientation: Fact checking AI for hallucinations and errors; using one’s own domain expertise to ensure accuracy.
4. Adaptability: Iterating and refining one’s approach to interacting with AI based on the quality of outputs.
5. Determination: Patience and willingness to continue trialling new approaches with AI, even during unsuccessful AI interactions.

Communication skills: Strong interpersonal skills which support the optimisation of AI outputs.

1. Empathy: Treating AI as an extension of one’s own mind and thoughts; anthropomorphising AI to create more thoughtful, receptive, and intentional dialogue.
2. Tailoring communication: Discerning whether AI output has the desired tone for a particular audience or situation, and refining prompts if it is not.
3. Exchanging feedback: Using AI to proactively seek feedback on work.

These key skillsets, alongside the broader skills taxonomy, underpin the proprietary skills assessment tools embedded in the Multiverse platform. These tools help organisations better understand the current capabilities of their staff ahead of embarking on upskilling initiatives.

“We need to start looking beyond technical skills and think about the human skills that the workforce must hone to get the best out of AI,” said Imogen Stanley, Senior Learning Scientist at Multiverse, who led the development of the skills taxonomy. “What we found during our first principles research phase was that skills like ethical oversight, output verification, and creative experimentation are the real differentiators of power AI users. By developing these specific skills, employees can move from being passive users of AI to active drivers of innovation and value.”

Multiverse is the upskilling platform for AI and tech adoption, which delivers personalised, on-the-job learning. Multiverse has trained more than 20,000 apprentices in AI, data and digital skills since 2016.

Over 1,500 companies work with Multiverse to deliver impactful learning that’s transforming the workforce at scale. Programmes are targeted at people of any age or career stage.

The need for AI durable skills research

Recent research by Gerlich (2025) found a significant negative correlation between frequent AI tool usage and critical thinking abilities. This was particularly evident in younger participants, who showed higher dependence on AI tools and scored lower on critical thinking assessments compared to older participants. The study attributes this decline to ‘cognitive offloading’, the delegation of thinking tasks to machines, which appears to undermine our capacity for independent analysis.

However, Multiverse recognises that as the world of work evolves, so too will our conceptualisation of intelligence and the skills required for effective AI interaction. Beyond just critical thinking, there exists a whole new set of durable skills that individuals must master to harness AI’s potential.

Our research approach

Our research aimed to investigate the specific durable (soft) and cognitive skills that enable successful AI adoption and integration in the workplace.

We had 3 research questions:

1. What specific durable and cognitive skills are essential for successful and effective AI use in the workplace, and why?
2. How is task performance using AI affected when the relevant durable and cognitive skills are not present?
3. Do durable and cognitive skills for successful AI use vary between experience with AI levels?

We used the following definitions of durable and cognitive skills:

Durable (soft) skills refer to personal attributes and social abilities like communication, adaptability, and ethical awareness that enable effective human interaction and collaboration, representing uniquely human competencies that cannot be algorithmically replaced (Amann & Stachowicz-Stanusch, 2020; Kumar, 2023).

Cognitive skills refer to the mental abilities and processes fundamental to acquiring knowledge and understanding, including analysing, applying, creating, and reasoning, which are essential for learning, decision-making, and critical evaluation of AI outputs (Zhai et al., 2024; Gerlich, 2025).

To ensure the authentic representation of these human skills, we employed a Grounded Theory approach. This is a data led, iterative process that builds theoretical frameworks directly from data, rather than testing pre-existing hypotheses. This allowed us to observe human behaviour in an AI environment, extract and pinpoint core skills from this raw data.

We conducted this observational research using Think Aloud Protocol Analysis (TAP; Ericsson & Simon, 1993), a research method which gathers verbal reports as data. The participants, 20 of Multiverse’s AI users ranging from beginner to expert level, verbalised their thoughts and decisions as they carried out daily tasks using AI. This was paired with follow-up interviews to understand participants’ perceptions of the way they interacted with AI.

Our findings

After collecting our initial data, we conducted thematic analysis which highlighted a set of 13 skills with examples of how each skill optimises AI use in the workplace.

These address research question 1, ‘what specific durable and cognitive skills are essential for successful and effective AI use in the workplace, and why?’, and research question 2, ‘how is task performance using AI affected when the relevant durable and cognitive skills are not present?’

Below, you can see an example skill that was evidenced in our research, ‘Tailoring Communication’. As alluded to above, this example shows how grounded theory research was used to identify specific skills. We analysed the raw data and grouped themes together, undergoing a process of iteration and refinement which eventually led to our final skillset of 13.

1. Tailoring communication: Discerning whether AI output has the desired tone for a particular audience or situation, and refining prompts if it is not.

This skill was observed as participants reviewed AI outputs to ensure a match with their desired tone, to sound like the human user, or to be appropriate for a particular audience. In the TAP analysis, a participant talked about understanding their environment in relation to AI’s outputs:

"The key here is marrying the output of your AI tool to the human world that you live in at work, which is like generally what is the expectation and the culture surrounding what your output should be."

Participant 9
Intermediate/Advanced AI user

Another participant reflected on the key soft and cognitive skills they employed in their AI interactions:

"I like to think about how I would explain this process to a normal person who isn’t a robot. And then that explanation becomes my prompt."

Participant 16
Expert AI user

We also captured evidence addressing research question 2, as participants reflected on the consequences of not tailoring their communication when using AI:

"The consequence would have been additional questions or confusion created by not being very clear and speaking in a voice that was appropriate for the audience that you're working with."

Participant 7
Expert AI user

Whilst this participant candidly explains:

"If I would solely trust and let Chat-GPT guide me in my communications I would truly fail."

Participant 1
Intermediate AI user

A note on critical thinking...

Interestingly, the evidence we captured for cognitive skills when using AI echoes established research demonstrating that when people anticipate future access to information, they exhibit lower rates of information recall but enhanced recall for information location and access methods (Sparrow, Liu & Wegner, 2011). This suggests that memory storage is being relocated rather than diminished, prompting us to reconsider which cognitive abilities are most valuable when working alongside AI systems. Our research supports this phenomenon, suggesting that the challenge lies not in cognitive decline as Gerlich’s research concluded, but in determining which skills to prioritise in an AI-augmented work environment.

Addressing research question 1, the full set of our 13 critical skills for AI adoption is listed below, along with their groupings:

Cognitive skills - Mental abilities used for learning, reasoning, problem-solving, and decision-making.

1. Analytical reasoning: Breaking down complex information for AI to more effectively deliver its instructions; recognising tasks that AI is or is not suitable for.

2. Creativity: Pushing the boundaries of AI use and experimenting with new approaches to drive innovation.

3. Systems thinking: Identifying patterns in AI performance to predict how AI will respond to a task.

Responsible AI use skills - Applying ethical principles to ensure the responsible use of AI, considering its impact on individuals and society.

4. AI ethics: Spotting bias and recognising how it affects AI outcomes; using AI outputs in an ethically sound way to inform business recommendations.

5. Cultural sensitivity: Identifying when AI outputs lack sufficient geographic or cultural awareness.

Self-management skills - Recognising our thoughts, values, feelings, and behaviours, and how they impact our ability to achieve our objectives when using AI.

6. Curiosity: Examining the broader context and requirements of a task to augment AI outputs.

7. Self-regulated learning: Reflecting on the success of a chosen AI approach; partnering with AI to self-assess its outputs.

8. Detail orientation: Fact checking AI for hallucinations and errors; using one’s own domain expertise to ensure accuracy.

9. Adaptability: Iterating and refining one’s approach to interacting with AI based on the quality of outputs.

10. Determination: Patience and willingness to continue trialling new approaches with AI, even during unsuccessful AI interactions.

AI communication skills - Strong interpersonal skills which support the optimisation of AI outputs.

11. Empathetic interaction: Treating AI as an extension of one’s own mind and thoughts; anthropomorphising AI to create more thoughtful, receptive, and intentional dialogue.

12. Tailoring communication: Discerning whether AI output has the desired tone for a particular audience or situation, and refining prompts if it is not.

13. Exchanging feedback: Using AI to proactively seek feedback on work.

Finally, addressing research question 3, our research also revealed that participants at four different AI experience levels exhibited distinct characteristics.

• Basic users tended to focus on task completion with simple prompts and limited evaluation.
• Intermediate users balanced quality and efficiency with growing AI awareness.
• Advanced users optimised AI for strategic tasks, used more complex prompts, and exhibited metacognition i.e. reflected on their own strengths and limitations in the AI interaction.
• Expert users integrated AI into sophisticated workflows, whilst maintaining extensive knowledge of AI’s constraints.
  

Interestingly, we found that female participants consistently underestimated their AI competency in self-assessments, requiring upward adjustments to a higher experience rating based on observed performance - highlighting important implications for how AI confidence is perceived across demographics.

What’s the impact of these findings?

In addition to answering our research questions, we have addressed a critical gap in the literature by conducting bottom up, grounded theory based research. Almost every piece of research or articles written about durable (soft) skills relies on pre-existing definitions of durable and cognitive skills. Our inductive research, on the other hand, observes how these skills naturally emerge and manifest in real workplace contexts - allowing us to discover authentic skill categories which reflect how humans behave in relation to AI.

Multiverse has already recognised the importance of these soft skills and successfully mapped them onto our existing learning programmes. For example, in our AI for Business Value programme, the technical requirement to ‘model business processes using relevant techniques, standards, notation and software tools’, directly connects with the durable skill of ‘Creative Thinking: being confident enough in one’s own AI abilities to push the boundaries of AI use’, demonstrating how durable skills are essential for mastering technical skills.

Additionally, being able to identify these skills allows us to progress towards being able to assess them and measure them, helping employee’s develop deeper and more sustainable AI capabilities beyond more basic AI awareness and technical skills.

And for leaders?

There are several key takeaways for leaders from this research:

Make strategic AI investments: Rather than pursuing blanket AI adoption that can reach billions in expenditure, leaders should evaluate tools based on their specific use cases and longevity, and whether they will unlock your company’s potential or hinder progress. Consider reframing your company’s skill development priorities towards transferrable soft and cognitive skills which in turn enhance any technical competency.

Crucially, focus on investing in learning as much as the tools themselves - creating the time, space and resources for deep and lasting AI adoption is as critical an investment as purchasing the technologies.

Map existing training: If your organisation has existing AI that requires technical training but you aren’t seeing progress in AI adoption, consider mapping that training against our newly identified durable skills. This approach may increase adoption and learning of your already-invested AI technologies. Leaders can also identify where relevant AI durable skills naturally align with technical competencies and integrate them, rather than treating them as separate initiatives.

Normalise cognitive offloading: Help your teams understand that relying on AI for certain tasks isn’t cognitive laziness, but strategic resource allocation that exercises an entirely new set of cognitive capabilities. Leaders can model and encourage when it is appropriate to use AI, while still valuing uniquely human contributions.

References:

• Amann, W., & Stachowicz-Stanusch, A. (2020). Soft skills and their role in employability. Management International Review, 60(4), 485-510.
• BBC. (2025). Government redirects apprenticeship funding towards foundational skills. BBC News.
• Clevry. (2025). Hiring Intelligence Report 2025: Soft skills as top hiring priorities. Clevry Research.
• Ericsson, K. A., & Simon, H. A. (1993). Protocol analysis: Verbal reports as data (Rev. ed.). MIT Press.
• Gerlich, R. N. (2025). AI overreliance and critical thinking decline: Evidence from workplace studies. Journal of Cognitive Technology, 12(3), 45-62.
• Global Skills Agenda. (2025). Core skills for the future workforce: Resilience, creativity, and analytical thinking. World Economic Forum.
• Goldman Sachs Research. (2023). The potentially large effects of artificial intelligence on economic growth. Goldman Sachs Economics Research.
• Kumar, S. (2023). Soft skills in the age of AI: Redefining human value in automated workplaces. Human Resource Management Review, 33(2), 178-195.
• Leça, B. P., & de Souza Santos, M. (2025). Cognitive skills development in AI-enhanced learning environments. Educational Technology Research, 41(1), 23-38.
• Nadeem, A. (2024). The irreplaceable human: Soft skills as competitive advantage in AI integration. Business Strategy Review, 35(4), 112-128.
• Sparrow, B., Liu, J., & Wegner, D. M. (2011). Google effects on memory: Cognitive consequences of having information at our fingertips. Science, 333(6043), 776-778.
• University of Oxford. (2025). AI skills wage premium study: Technical competencies in the modern workplace. Oxford Internet Institute.
• World Economic Forum. (2025). Future of Jobs Report 2025: Skills disruption and workforce transformation. WEF Publications.
• Zhai, X., Chu, X., Chai, C. S., Jong, M. S. Y., Istenic, A., Spector, M., ... & Li, Y. (2024). A review of artificial intelligence (AI) in education from 2000 to 2020. Educational Technology Research and Development, 72(1), 1-45.

The Royal Institution of Chartered Surveyors (RICS) has partnered with Multiverse to launch a Transformation Academy for staff. A suite of tailored data and AI courses will enable teams to harness data and insights to improve decision-making, enhance operational efficiency, and drive a culture of innovation to improve service for its members.

The academy will provide upskilling opportunities that will support RICS’ mission to modernise its workforce and elevate built and natural environment industry standards. With a focus on both foundational and advanced AI and data skills, the training will enable staff to implement new ways of working and optimise processes.

This will in turn enhance the experiences provided to members from faster, more responsive support to more relevant insights and services. It will also enable RICS to streamline internal reporting and processes, and make smarter, data-informed decisions that strengthen its role as a trusted voice in the built and natural environment.

According to Multiverse’s Skills Intelligence Report 2025, the construction industry loses 26 days of productivity every year, with 33.9% of employees’ time working in data spent ineffectively. RICS is enhancing its workforce capabilities by enrolling teams across three specialised cohorts, each aligned to deliver hands-on experience to ensure AI and data training can be applied to role-specific day-to-day activities.

The Data Cohort will focus on building a strong foundation through the Level 3 Data Insights, Level 4 Data Fellowship, and Level 5 Applied Data Engineering courses. Practical tools like Microsoft PowerBI will be introduced to apply insights in real time.

The Transformation and Project Management Cohort will take the Level 4 Business Transformation and AI for Business Value courses. Meanwhile, the AI Cohort will learn how to apply AI-driven tools to deliver measurable improvements via Multiverse’s Level 3 AI-Powered Productivity and Level 4 AI for Business Value.

Robyn Mckenna, Chief Product Development Officer at RICS, said: “At RICS, we’re committed to equipping our people with the skills and tools they need to thrive in a rapidly evolving landscape. The launch of the Transformation Academy in partnership with Multiverse is a critical step in embedding data and AI capability across our organisation. It will not only improve how we operate internally but also how we serve our members; with faster insights, smarter decision-making, and a stronger foundation for innovation. This is about future-proofing both our workforce and the profession we support.”

Gary Eimerman, Chief Learning Officer at Multiverse, said: "RICS is a world-renowned organisation with a 150-year foundation of supporting a sustainable and insight-led chartered surveyor community. The launch of our training programme underlines this commitment, supporting teams with the digital tools and skills they need to make data-driven decisions, enhance client service and streamline manual processes.”

Multiverse is the upskilling platform for AI and tech adoption, which delivers personalised, on-the-job learning. Multiverse has trained more than 20,000 apprentices in AI, data and digital skills since 2016.

Over 1,500 companies work with Multiverse to deliver a new kind of learning that’s transforming the workforce at scale. Programmes are targeted at people of any age or career stage.

Project management itself is all about bringing people and resources together to get complex tasks done efficiently. Today, businesses are using AI to simplify everything from setting budgets to troubleshooting equipment shortages. Learning how to work with these tools can help you lead projects more successfully and open up new career pathways as employers look for tech-savvy Project Managers.

What is project management?

Project management focuses on planning tasks and leading teams to reach shared goals. It requires strong communication skills, problem-solving abilities, and other soft skills.

Even relatively simple projects often involve many steps, including:

• Creating a realistic project budget and timeline
• Managing resources, such as construction equipment or financial software
• Delegating tasks to specific team members based on their strengths and availability
• Assessing risks and planning how to avoid them
• Documenting project progress at every step

Project Managers handle these nitty-gritty details so their teams can focus on more specialised tasks. For example, a tech firm might bring in a dedicated Project Manager to plan a mobile app project, while Software Developers concentrate on the actual programming. This division of labour keeps projects moving forward smoothly, without distractions or too many people making decisions.

Organisations in all industries rely on Project Managers to plan and oversee initiatives. In the UK, these professionals contribute an estimated £186.8 billion to the economy. They help companies make strategic decisions — such as how much to invest in a marketing campaign — and use resources efficiently.

The five phases of the project management process

Project management professionals work on a wide range of initiatives, even within the same industry. One person might manage the construction of a multi-million-pound hospital, while another oversees software development for medical professionals.

While these undertakings can have very different scopes, they typically follow the same project life cycle. Here are the five stages:

1. Initiation

You probably wouldn’t backpack across Europe without a map and a budget — that’s a fast-track to disaster, or at least a stressful trip. Managing projects requires the same kind of thoughtful pre-planning.

During this phase, professionals set project objectives and map out the big-picture steps to achieve them. They also evaluate the project’s feasibility. For instance, a client may want to revamp their entire onboarding process but only have the budget for a new handbook. Figuring out these limitations early helps prevent disappointment and overspending later on.

Initiation also involves:

• Weighing the potential project’s pros and cons
• Identifying project team members
• Defining the project scope
• Establishing the project deliverables or outcomes

Project Managers often organise all this information in a project charter. This document helps stakeholders understand exactly what’s involved in the undertaking and the estimated project costs. That way, they can make an educated decision about whether to move forward — or go back to the drawing board.

1. Planning

In the planning phase, Project Managers develop a detailed roadmap for the initiative. This outline should include:

• A scope statement that defines exactly what the project will involve (and what it won’t)
• A step-by-step plan for completing the project
• A realistic timeline with milestones and deadlines
• A detailed budget that factors in every cost, from labour to office supplies
• A breakdown of which project team members will handle each task
• A communication plan, such as weekly meetings or email updates
• A risk management plan that addresses potential hazards (supply chain shortages, cyber attacks, etc.)

Planning is one of the most time-consuming steps in the project management process, but it’s well worth it. It helps build a strong foundation for the project and prevents serious issues down the line.

For instance, you might realise that a project requires a custom piece of equipment that takes months to order. By spotting this early, you can adjust your schedule and avoid frustrating delays.

Planning also prevents the all-too-common problem of scope creep. Clients often ask for more deliverables, or overachieving team members may take on extra tasks without thinking twice. With a strong plan, you can set boundaries and deliver (only) what you promised.

1. Execution

Once you’ve finished your plan, you’re ready to put your project team to work. This is the core part of the initiative, where everyone comes together to start creating the deliverables.

Every complex project involves a healthy amount of delegation. Consider your project team members’ strengths and interests when assigning tasks. An aspiring leader, for instance, might be eager to plan client meetings. Meanwhile, a Business Analyst may focus on gathering and analysing financial data.

As a Project Manager, you should communicate frequently with all your stakeholders. This might involve a daily standup with the project team, regular status updates, and quarterly reports. By keeping everyone in the loop, you’ll reduce confusion and costly errors.

Tracking is key, too. Obviously, you don’t want to micromanage your project team — that’s bad for morale. But checking their progress and setting smaller milestones will help ensure that everyone stays on track. That way, you can offer support as needed.

4. Monitoring and control

Controlling a project may sound harsh, but you’re not turning into Big Brother. This phase simply involves tracking a project’s progress and addressing any roadblocks as a team.

Start by setting key performance indicators (KPIs) to measure project success. If you’re managing a social media campaign, you might track these metrics:

• Engagement rate (comments, likes, etc.)
• Follower count
• Number of impressions

On the other hand, a software development project might focus on cycle time and code quality.

This kind of project monitoring will help you understand your performance and adjust your plan if necessary. For example, consistently poor code quality might mean that it’s time to bring in a more experienced Software Developer.

You should also closely monitor the budget throughout your project. An extra resource here, a little overtime there — these costs can add up quickly. Track all expenses carefully to keep your spending in check.

And don’t forget about the timeline. Even the most experienced Project Managers can’t avoid every delay, such as a natural disaster or a flu outbreak in the office. Be flexible and ready to shuffle around resources or deadlines to keep making progress.

5. Closure

The project isn’t over when you finish your last deliverable. You still need to hand everything over to the client and reflect on what you learned.

Share your project documentation with your client and other stakeholders. This paperwork helps them understand how to manage it moving forward. You may also need to provide hands-on training to set them up for success. Nursing staff, for instance, might need a workshop to learn how to use a new healthcare database.

Evaluate the project's success, too. Here are a few questions to consider:

• Overall, which parts of this project went well?
• How could I improve future projects?
• What obstacles did the team face, and how did we overcome them?
• Were there any unnecessary steps or resources?

Schedule a debriefing meeting to discuss these topics with your team and talk about your insights. This step will help you celebrate a successful completion and make your next project plan even better.

Types of project management

There’s no one-size-fits-all project management methodology. It depends on your goals, the industry you’re in, and your team’s strengths. Here are four popular frameworks.

Waterfall

When a river flows down a waterfall, it moves in one direction. Sure, the water might splash up a bit when it hits the bottom, but it never turns around and flies back to the top.

The Waterfall methodology works the same way. The project moves through each phase — from initiation to closure — one step at a time, without ever reversing or repeating phases.

This one-way approach requires a lot of upfront planning to get everything right the first time. But when done well, Waterfall can significantly boost efficiency and productivity. Plus, team members may feel more satisfied when they’re not constantly redoing their work.

Of course, it’s not easy to change a waterfall’s direction. This sequential method works best for simple and predictable projects that don’t require much flexibility.

Agile

Agile project management uses an iterative approach to help teams constantly improve their work. Instead of waiting for feedback at the end, they work on tasks in small bursts, get input, and make adjustments as needed.

Software Developers created the Agile method to keep up with their clients' rapidly changing demands. It’s a much more flexible approach than the waterfall method, allowing teams to make changes on the fly.

Consider Agile project management when you need to adapt quickly. It’s a great fit for marketing campaigns, product development, and other collaborative initiatives with lots of moving parts.

Lean

Lean project management is a subset of Agile that focuses on conserving resources and improving efficiency. It follows the “just-in-time” principle by delivering only the work that’s needed, when it’s needed. Teams also focus on project tasks that have the most impact instead of getting bogged down in minor details.

Manufacturers originally developed the Lean methodology, but it’s also popular in construction and healthcare. Use this approach when you want to save money without sacrificing value.

Hybrid

Sometimes, no project management framework meets all your needs. The hybrid approach lets you combine principles from different methods to fit your specific project.

This flexible strategy is an excellent option for more complex projects. For example, a hospital might blend Agile’s iterative approach with Lean’s cost-saving measures to create a new waiting room system.

Project team management

Because every industry needs Project Managers, upskilling in this area can prepare you for new roles and responsibilities. Here are a few essential skills to develop:

• Communication: The best Project Managers can clearly explain their expectations and goals to their teams. They also make complex information accessible for clients and stakeholders.
• Leadership: Strong managers can rally their teams behind shared goals and help them perform at their best.
• Problem-solving: Every project involves unexpected challenges, so the ability to stay calm and troubleshoot is key.
• Risk management: Project Managers should know how to assess risks and take steps to prevent them.

Industry-specific knowledge is essential, too. A Project Manager for a website may not need to know every detail of Python, but they should understand enough to help troubleshoot bugs.

Leaders should also follow effective project management practices, including:

• Clearly define each team member’s role from the beginning.
• Celebrate small wins — such as completing a tricky feature — to boost morale and build positive momentum.
• Encourage team members to share ideas and feedback freely.
• Use collaboration tools like Trello (for task management) and Slack (for communication).
• Step in early to resolve conflicts and help members compromise.

Tools and technologies in project management

Many professionals rely on traditional project management tools. Here are a few favorites:

• Asana: A task management platform that lets teams assign responsibilities and track progress together.
• Gantt charts: Visual diagrams that use horizontal bars to represent the duration and deadline for each task.
• Microsoft Project: A project management software that allows users to create project plans and schedules.

While these resources are still popular, artificial intelligence tools can help Project Managers work even more efficiently. For example, Notion AI can generate project plans and other content, while Monday.com uses AI to automatically delegate tasks and monitor progress.

How AI is transforming project management

Artificial intelligence isn’t just another tech fad. It can help you manage change and lead projects more effectively, especially when you’re juggling dozens of tasks. Here are a few ways this technology can support project management:

• Automating project scheduling and resource management: Tools like Motion use AI to prioritise tasks and create accurate schedules. They can also help you schedule team members at the right time.
• Intelligent risk forecasting: Predictive models use historical project data, economic trends, and other information to anticipate potential risks.
• Natural language summarisation of meetings: Turn your meeting recordings into summaries and to-do lists with notetaking tools, such as Fireflies and Otter.ai.
• Predictive analytics for budgets and timelines: AI can help you set realistic budgets and deadlines, reducing unexpected surprises.
• AI assistants for real-time status reports: Tools like ClickUp use data analytics to measure progress and generate status reports. They can help you quickly spot bottlenecks or underperforming employees.
• Interpret code: Use AI coding tools like Denigma to quickly understand programming languages — no more racking your brain to remember JavaScript functions.

The role of the project management office (PMO)

A project management office is a team that sets quality standards and policies for projects. It helps Project Managers maintain consistency, even when working on drastically different initiatives. For example, a PMO may require construction and HR projects to follow the same core practices.

AI dashboards allow PMOs to track every project in a centralised place. This makes it easier to spot scope creep or teams that aren’t following company policies, so PMOs can take action quickly.

Career paths in project management

In 2024, Indeed ranked Project Manager as the top job in the UK. These professionals are in demand in many industries, including:

• Construction
• Information technology
• Business transformation
• Healthcare
• Finance

Many job titles fall under the umbrella of project management. For example, Operation Delivery Leads earn an average base pay of £60,000 and manage projects across different teams. Meanwhile, a Programme Manager focuses on big-picture strategizing for multiple projects, with an average salary of £61,000.

Training paths in project management

The Project Management Institute offers numerous certifications and training programmes that teach essential skills. One popular option is the Project Management Professional (PMP) certification, which demonstrates expertise in different project management techniques.

A Multiverse apprenticeship is another excellent way to prepare for a project management career. It teaches the latest project management methods and software, including Jira and AI tools. You’ll also gain hands-on experience by planning and executing real projects in your current role.

By the end of the 15-month apprenticeship, you’ll have a portfolio that showcases your skills and mastery of different project management types. The best part? Multiverse programmes are completely free for apprentices.

Master AI-powered project management with Multiverse

Successful project management isn’t just about checking off to-do lists and meeting deadlines. It’s an art that helps teams thrive and businesses meet their strategic goals.

Learn how to lead change with Multiverse’s Project Management apprenticeship. This free programme teaches essential project management approaches that you can use to guide initiatives from start to finish. Plus, our AI modules allow you to learn prompt engineering, data analytics, and other in-demand skills.

Ready to kickstart your project management journey? Fill out our quick application today.

Learning how to use Microsoft Copilot effectively can help you stay competitive in a rapidly evolving digital workplace. With more companies embedding AI into their workflows, mastering Copilot’s features can streamline your work and save time. Users say it helps them complete routine tasks up to 29% faster.

What is Microsoft Copilot?

In 2023, Microsoft replaced its non-AI virtual assistant Cortana with Copilot. This new tool, the company announced, “uses AI to turn your words into a powerful productivity tool,” helping users “work smarter and faster.”

Like ChatGPT, Microsoft Copilot is powered by large language models (LLMs) — including OpenAI’s GPT-4o and Microsoft’s Prometheus framework — that interpret and respond to user inputs.. For example, you could ask Copilot to help you brainstorm content ideas — “suggest 20 Instagram posts to announce a new product” — or draft a memo.

Copilot uses a freemium structure, allowing users to access basic features at no cost. The free version is a good choice if you only want to use the Copilot app, which functions much like ChatGPT. It can generate a limited number of images, search the web, and answer questions.

For the full experience, you’ll need to upgrade to Microsoft Copilot Pro. This paid plan costs £19 per month and integrates Copilot agents with Microsoft 365 apps. It also gives you early access to the latest AI features, including multilingual speech recognition and sentiment analysis tools.

How Microsoft Copilot works

Microsoft 365 Copilot may seem like an enigma, especially if you’re not a tech professional. But this platform is relatively straightforward.

The software was built on two large language models:

• OpenAI’s ChatGPT-4o: This omni-channel model can produce audio, images, and text. This multimodal capability, OpenAI explains, “enables the model to engage in more natural and intuitive interactions with users.”
• Microsoft Prometheus: It combines GPT with Bing’s search index, allowing it to draw on real-time data and cite sources.

Copilot stands out from other AI tools because it combines these LLMs with the user’s own proprietary data. It does this through Microsoft Graph, an application programming interface (API). This platform collects data from all your Microsoft 365 apps, including Calendar, Outlook, and Teams.

When you interact with Copilot, it draws on this information to create tailored responses. For example, it could summarise emails or a dense white paper that would take hours to read. Or it might suggest a meeting agenda based on your messages in Teams.

This AI assistant also integrates directly with other Microsoft products, expanding their capabilities. These embedded Copilot features are so intuitive that you may not even realise that you’re using AI to improve your work.

Key features and use cases

Microsoft Copilot is an incredibly versatile AI tool with applications in practically every industry. Here are a few ways you can use this software to boost productivity.

Word

Even relatively short documents often take hours to write and revise. Copilot can speed up this process by generating a first draft based on a prompt or an existing document. For example, you might input, “Write a blog post about the benefits of drinking tea. Use the information in /teanotes as your reference.”

You can also use Copilot to summarise key points from meeting notes or complex documents. Rather than slogging through a 40-page transcript, you’ll get the gist in seconds.

Excel

Microsoft Excel has been a foundational data analytics tool for decades. But the Multiverse Skills Intelligence Report 2024 found that 57% of employees have no Excel skills or only basic knowledge.

Copilot can help upskillers analyse data sets in Excel and spot trends, such as best-selling products. It can also suggest formulas based on conversational prompts. Instead of racking your brain for the VLOOKUP function, for instance, you can just ask Copilot to “find Kelly Smith’s phone number.”

PowerPoint

Copilot’s generative AI software lets you turn simple outlines into full-fledged slide decks. That means you don’t have to spend hours obsessively rearranging slide layouts or fine-tuning headings.

Plus, you can instantly add your company’s branding or even translate the whole presentation to another language. It all adds up to significant time savings, especially if you’re not a graphic designer.

Outlook

UK office workers spend over 11 billion hours a year on email, scheduling, and other repetitive tasks. Lighten your to-do list by asking Copilot to draft emails and summarise your colleagues’ messages. It can also help you schedule meetings, focus time, and other events.

Teams

Microsoft Teams users receive an average of 153 messages per day. While that constant communication helps keep everyone in the loop, it can also be incredibly distracting. You may just be getting in the zone when you hear that signature “ping.”

With Copilot, you can quickly summarise your chats and conversations instead of reading every message. It can also suggest action items — “email Brad to reschedule the webinar” — and transcribe meetings. That way, you can focus on more important tasks outside of Microsoft Teams.

Copilot Chat and Pages

Copilot Chat is a free AI chatbot that works across all Microsoft apps. Its search-like interface lets you look up information on the internet without needing to open a separate browser.

It also integrates with Copilot Pages, an interactive and collaborative canvas. For example, you could ask the AI assistant to list nearby competitors, then create a page to share with your coworkers. These Copilot features simplify collaboration by keeping everything in one centralised workspace.

GitHub Copilot

Programmers can use GitHub Copilot to generate code suggestions, helping them build applications much faster. This AI coding tool also supports users by catching and fixing mistakes, drastically reducing debugging time.

A GitHub experiment found that developers who used Copilot finished a JavaScript web server 55% faster than those who didn’t use the tool. Additionally, 96% of surveyed developers reported that Copilot helps them complete repetitive tasks faster.

How to access Microsoft Copilot

Because Copilot is so deeply enmeshed with other Microsoft technologies, it has multiple access points, including:

• Taskbar integration: Windows 11 lets you pin Copilot to your taskbar for easy access. Some newer laptops also come with a Copilot button on the keyboard that you can tap to open the app.
• Bing chat: The search engine includes a Copilot tab in the top menu, which you can click to launch the app.
• Toolbar buttons: Microsoft 365 apps feature Copilot buttons in the ribbon menus.
• Teams and Outlook add-ins: When you launch these platforms, you’ll see the Copilot icon in the upper-right corners.
• Microsoft’s Edge browser: Open this browser to view the built-in Copilot sidebar. It can create images, give you custom daily news briefings, and more.

You can also access Copilot on your smartphone by downloading the mobile app.

Advanced Tools: Vision, Voice, & Labs

Once you’ve mastered Microsoft 365 Copilot’s basic features, it’s time to level up with more sophisticated tools. These platforms can help you future-proof your career by boosting your efficiency and helping you acquire new skills.

Copilot Vision

Microsoft has revamped the way people search with Copilot Vision. It’s exclusively available with Microsoft’s Edge browser and acts as a personalised AI companion.

The premise is simple. Copilot scans all the web pages that you browse, almost like an invisible friend looking over your shoulder. It then analyses and contextualises this information to provide insights you might not get on your own.

Say, for instance, you’re planning a business trip to Madrid and want to design the perfect itinerary. You can describe your interests to Copilot Vision: “I want to take my clients to dinner at authentic Spanish restaurants and schedule a walking tour.” As you explore websites, Vision will highlight relevant information and activities, accelerating the research process.

Copilot Voice

Sometimes, you don’t have the time (or patience) to type out prompts. With Copilot, you can use voice commands to ask for information or perform tasks. For example, you might say, “Can you add a meeting with my assistant to my calendar for noon tomorrow?”

Copilot Voice also offers multilingual interactions in over 40 languages. It’s perfect for studying for exams or practising your conversational skills before an international trip.

Copilot Labs

Microsoft is constantly experimenting with new Copilot features. Commercial customers can sign into Copilot Labs to get early access to these projects. It’s a fun way to see what’s in the works and play with more advanced tools.

One available product is Copilot Actions, which automates web tasks based on user prompts. For example, you could ask it to book a hotel or order flowers for your spouse. You can also use Copilot Podcasts to create a custom podcast, or chat with an adorable visual avatar with Copilot Appearance.

Some of these tools might not directly improve productivity, but they give you the opportunity to learn about cutting-edge AI applications. And who knows? That AI-generated podcast or a conversation with Copilot Appearance might spark new ideas.

Benefits for productivity

Like any new technology, Microsoft Copilot has a bit of a learning curve. But once you get the hang of its features, it can have a huge impact on your productivity. Here are four advantages of using this AI tool.

Save time

Every professional has a laundry list of time-consuming (and often quite tedious) tasks. Microsoft Copilot can automate many of these activities, including:

• Summarising documents, from emails to hours-long webinar transcripts
• Generating emails, articles, proposals, and other content
• Researching information
• Prioritising emails based on urgency or deadlines
• Editing content, such as reports and intricate Python code

By automating these tasks, Copilot frees up your schedule for activities that require a human touch.

Develop stronger collaborations

Using AI to improve human relationships may seem paradoxical, but it can be extremely effective. For example, you could use Copilot to write meeting summaries and track tasks. That way, you can keep your team on the same page and make sure everything gets done on time.

Streamline data analysis

According to Multiverse’s The ROI of AI report, 52% of tech leaders believe their organisation lacks essential data skills. Professionals can help fill this gap by combining Copilot with Microsoft BI to “chat” with data sets.

A Business Analyst, for instance, could prompt Copilot to find trends in sales data and generate data visualisations. These applications are much faster than building dashboards and designing charts from scratch.

Improve project management

When it comes to managing complex projects, Microsoft Copilot can be incredibly useful. Use it to draft budgets and timelines based on your clients’ needs. You can also use it to communicate updates through Microsoft Teams and Outlook.

Copilot also supports change management by enabling you to clearly communicate the benefits of changes to your team. That way, you can get employee buy-in. Or use it to build training materials to get everyone up to speed quickly. These use cases can streamline projects and reduce stress for everyone.

Master Copilot and other innovative AI tools

Microsoft Copilot is a powerful ally for any professional. With its diverse applications, it can improve many aspects of your daily routine, from simple administrative tasks to programming and project management.

Sharpen your AI skills with a free Multiverse apprenticeship. Our AI for Business Value programme teaches you how to use Copilot and other AI solutions to make an impact in your organisation. You’ll gain hands-on experience solving real business problems while studying AI ethics and business analysis fundamentals. Together, this knowledge will help you drive data-driven change. Plus, you’ll receive personalised career coaching from industry experts.

Continue your upskilling journey by completing our quick application today.

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.