Bridging The Learning Divide: AI & Skills Gaps
Technological advancement has created a real challenge for individuals, organizations, and societies. As Thomas Friedman aptly noted, “Technology is now accelerating at a pace the average human cannot keep up with.”
This “learning divide” – the gap between the skills people have, and the skills they need – is widening, threatening employability, organizational competitiveness, and societal cohesion.
Ironically, perhaps, it is AI that will provide the only scalable path to bridging this divide, empowering organizations to navigate an era of perpetual change.
The Learning Divide in Action
For many individuals, the shift to digital banking apps and the closure of traditional bank branches have alienated many, particularly older customers. For some, even basic financial tasks have become complex. Yet, AI-powered assistants within apps are beginning to reverse this trend – making technology more intuitive and accessible.
At the societal level, the pandemic starkly exposed educational inequalities. Low-income countries, often lacking the infrastructure for online schooling, saw millions of students fall behind. Here, AI offers hope: enabling personalized learning interventions and delivering multilingual educational materials at scale, for example.
The same principles apply when it comes to workforce development and talent management.
In the workplace, the learning divide manifests as growing skills gaps. Organizations face mounting pressure to equip their teams with the skills needed for today’s challenges and tomorrow’s opportunities; to reskill their employees and to redeploy staff as roles or tasks being “automated away”.
AI will affect 60% of jobs in advanced economies and half of these exposed jobs could be negatively impacted. (International Monetary Fund)
But achieving this at scale cannot be tackled by traditional methods, and requires more sophistication around AI and the (skills) data it relies on.
Using AI To Bridge Skills Gaps
Understanding Your Workforce
To upskill and reskill effectively, leaders need a clear, accurate view of their workforce’s current skills, potential, and readiness. This requires real-time data on employee capabilities – a task too complex for manual systems.
When you apply AI to skill data, you unlock unparalleled insights into individual and team capabilities. AI can analyze skills at a granular level, identify gaps, and predict future requirements. This enables organizations to make the right decisions about reskilling and redeploying their workers – and to match people with targeted, impactful learning strategies that evolve with business needs.
“Artificial intelligence is going to be critical in order to make sure that we are going to be able to understand the different set of skills that a person has, and that we can translate and understand those skills.” – Fernando Bellon, Head of Talent Acquisition, BBVA
A Job Architecture for the Future
Organizations must also understand the evolving nature of work. Mapping tasks, competencies, and emerging roles – as they apply to work in your specific organization – is key to building a forward-looking job architecture.
It’s a lot of work for a team of humans. But, with the right AI, you can easily map roles, tasks and skills, dynamically update job descriptions based on market trends, and identify new roles that will emerge as industries evolve.
This ensures alignment between workforce capabilities and business objectives, and provides the framework or blueprint for ensuring you can always find (or train) talent to fill critical roles.
“Some of the basics... are even just simply looking at our role architecture and outlining and being more clear about the skills, capabilities and roles that we have at the firm, and mapping those to skills, and thinking about a framework that would allow us to leverage it more broadly.” – Caroline Heller, Senior Managing Director, Global Head of HR, BlackRock
Dynamic Decision-Making
AI transforms static data into actionable insights, enabling leaders to match employees with the right roles, projects, and learning opportunities – quickly and at scale. As automation fundamentally changes the nature of many Customer Service roles, for example, AI can identify transferable skills amongst impacted employees, recommend training pathways to help them transition into new or enhanced roles, and support redeployment strategies that optimize workforce utilization.
Each decision that you make feeds back into the system: creating a skills data “flywheel” that improves with every use.
“We are, from the Wells Fargo perspective, collecting really homegrown skills data for our employees. And our next phases of work will be expanding those to our external candidates and prospects. And the tools like Beamery, allow us to comb through that data to find the right person for the right job.” – Art Lokerson, HR Product Management Director – Talent Acquisition, Wells Fargo
When HR uses AI effectively, according to McLean and Company, organizations are:
- 1.3 times more likely to be highly effective at recruiting (by effectively filling vacant roles with quality external talent and at providing a great candidate experience)
- 1.2 times more likely to be highly effective at facilitating data-driven people decisions, and
- 1.4 times more likely to be highly effective in learning and development.
AI’s ability to analyze trends and predict skills demands ensures companies remain agile and are ready for the future – and even makes it possible for leaders to take action more quickly. If you have skills and talent data connected across systems, the AI can work across the entire stack in a joined up way – and surface the insights you need, wherever you happen to be working.
And what creates that connective tissue? That’s right: intelligent AI models that can push data to where it provides the most value.
Sixty-three percent of HR executives say they are using “skills-related technology embedded in core HR information systems” – but just 33% say they have a single source of skills data across the entire workforce. (Deloitte)
The learning divide is not insurmountable. By harnessing the power of AI, leaders can transform talent management into a dynamic, responsive system that adapts to the (accelerating) pace of change. This not only ensures organizational success but also supports individuals in staying employable and engaged in a rapidly evolving world.
It’s time to embrace AI and connected skills intelligence to bridge the learning divide – and unlock the full potential of your workforce.