As artificial intelligence (AI) continues to rapidly transform the business landscape, organisations must empower their workforce to stay competitive and adapt.
We held a webinar to explore strategies for developing talent, overcoming challenges, and leveraging AI to enhance learning initiatives and future-proof your organisation.
To catch up on the full discussion:
Event panellists
- Chiraag Swaly, Head of Apprenticeship Design, Kaplan
- Michael Lafferty, Head of Data and Technology Apprenticeships, Kaplan
Bringing over 20 years of combined experience in digital and IT apprenticeships, the experts have collaborated extensively in their roles at Kaplan. Their deep background in technology and curriculum development includes partnering with numerous major training providers to develop technology-focused apprenticeship programmes.
Topics discussed in the webinar include:
- Defining upskilling and reskilling, and why both are important
- The best practices for implementing AI-driven training programmes
- Challenges when transforming the workforce
- How AI can accelerate skill development
- Leadership’s role in fostering a culture of continuous learning.
What is upskilling and reskilling, and why does it matter?
The panellists discussed how upskilling involves enhancing existing capabilities. For example, a finance analyst might learn to integrate AI tools into financial modelling. Reskilling, however, supports significant career shifts, like a customer support representative transitioning into a data analyst role. The distinction lies in scale - upskilling deepens knowledge in a current role, while reskilling prepares individuals for new responsibilities.
Both upskilling and reskilling are becoming increasingly urgent. The World Economic Forum predicts that 39% of core job skills will change by 2030. Likewise, LinkedIn has reported a 177% increase in demand for AI skills since late 2023. Organisations prioritising workforce development are better positioned to innovate, retain staff, and adapt to rapid technological advancements.
Best practices for AI-driven training programmes
Training professionals for the AI era isn't as simple as creating a course catalogue. A more strategic approach is essential to ensure meaningful results.
1. Build a skills graph
Identify gaps by assessing current roles, required skills, and future demands. Start with a skills graph, which maps out what your team knows and what they need to learn. Experts like the team at Kaplan can help with this if necessary.
2. Use a product development mindset
Adopt an iterative approach to training. Launch a learning module, gather feedback, and then refine the experience. At Kaplan, for example, we introduced ‘promptathon’ workshops where employees solve business problems using AI. The feedback from these sessions refines our training approach.
3. Blend AI and human learning
Leverage adaptive AI platforms alongside traditional live-cohort models. AI tools can provide instant feedback, enabling professionals to improve in real-time. This combination ensures personalised, contextualised learning.
4. Link training to KPIs
Shift focus from course completion to measurable outcomes. For example, evaluate how upskilling impacts performance metrics, like productivity and task efficiency.
5. Celebrate microlearning
Rather than overwhelming your team with long courses, integrate small learning sessions into their daily workflows. Ten minutes of daily learning can accumulate to nearly an hour each week, creating sustained growth over time.
Overcoming challenges in workforce transformation
Effective workforce transformation isn't without obstacles. The panellists outlined common challenges while asking the audience to share their biggest obstacles to scaling AI‑driven learning. They responded with actionable solutions.
- Address the fear of job loss: The introduction of AI often sparks anxiety about redundancies. Transparent communication is key to mitigating these fears. Share how AI augments existing roles and invest in showing your team the tangible benefits.
- Combat training fatigue: Several mandatory courses can overwhelm the workforce. Embed microlearning into regular workflows to make training feel less intrusive and more impactful.
- Overcome the digital divide: Ensure inclusivity by tailoring resources to all teams within your business. For example, frontline staff or remote workers may not have immediate access to training tools, so it's important that they are given a fair opportunity to upskill or reskill.
- Prove the return on investment (ROI): Training can be considered a cost centre. Connect learning outcomes directly to business metrics, like improved efficiency, reduced turnover, or higher engagement rates.
- Celebrate quick wins: Given the constant pace of change, small successes can keep momentum alive. Share stories about what’s working and encourage teams to experiment without fear of failure.
To summarise the challenges of workplace transformation, a statistic was shared that indicates only 12% of workers received AI-specific training in 2024, highlighting that many organisations are still developing their approach to this area of upskilling. Despite the relatively recent surge in Gen AI adoption since 2023, Chiraag shared how this presents significant opportunities for improvement and for organisations to seek guidance on their training needs.
How AI itself can enhance skill development
The experts discussed AI as a tool that can enhance skill development. Generative AI platforms, like ChatGPT or Gemini, offer dynamic and personalised pathways for learners.
Chiraag highlighted ways that AI is revolutionising skill development:
- Adaptive learning paths: AI provides real-time, custom-tailored lessons based on individual knowledge gaps.
- Instant feedback: Professionals can use AI as a virtual coach, validating their understanding and correcting errors on the spot.
- Simulations and scenarios: AR, VR, and AI-driven simulations create practical learning environments that would otherwise be costly or logistically impossible.
- Using AI as a partner: Instead of merely following prompts, learners can collaborate with AI and foster critical thinking and creativity. For example, a customer support agent can utilise Gen AI to rehearse difficult conversations or handle queries more efficiently.
Leadership’s role in AI adoption
The speakers discussed the importance of leadership taking ownership of AI narratives, investing in training at scale, and creating psychological safety:
1. Own the narrative
Leaders should clearly communicate why AI is important and how transformation aligns with the organisation’s goals. When professionals see senior leaders actively engaging in learning, it inspires buy-in across teams.
2. Fund training at scale
Avoid limiting AI programmes to pilot projects or select teams. Investing broadly creates an inclusive environment and accelerates adoption.
3. Tie learning to performance
Leadership can link upskilling to tangible incentives, such as promotion criteria or KPI recognition, ensuring employees see the value of their efforts.
4. Signal psychological safety
Encourage experimentation without fear of failure. Mistakes during AI adoption are inevitable, and leaders who model resilience and adaptability will boost overall morale.
5. Include everyone in the organisation
Every individual should feel empowered to explore AI tools and opportunities, from entry-level employees to senior executives.
AI applications in accountancy
If you’re unsure where to begin, here are some practical steps you can take to get started:
- Conduct skills assessments across departments to identify high-priority gaps.
- Introduce AI literacy workshops targeting the whole organisation.
- Leverage micro-credentials or certifications to boost employee confidence and expertise.
- Build AI-driven tools directly into workflows. At Kaplan, Gemini has become a game-changer for productivity, allowing teams to analyse emails and data faster than ever.
Why AI transformation can’t wait
As discussed, relatively few workers received AI-specific training in 2024, which reflects the enormity of the opportunity gap for organisations. For businesses, this means the time to act is now. AI adoption isn’t a fleeting trend, it’s the foundation of a competitive future.
By investing in workforce transformation today, your organisation can achieve sustainable growth, attract top talent, and leave competitors behind.
Transform your workplace
Technology’s rapid advancement means that it’s more important than ever to upskill and reskill your teams to ensure your business remains future-proof and competitive. Apprenticeship programmes within the data and technology sector are a cost-effective solution for upskilling, allowing you to develop in-house expertise and avoid expensive outsourcing.
Read more about the return on investment of apprenticeships for the business. Alternatively, contact the team who can talk you through the full process so that you can make an informed decision regarding the future of your organisation.
All data and technology apprenticeship programmes at Kaplan include our free Generative AI course and micro-credential (in partnership with CertNexus).