In the annals of technological advancement, from the discovery of fire to the dawn of computing, one pattern has remained constant: new technologies have predominantly benefited people with specialized skills. This historical trend has created increasingly steep learning curves and a widening skills gap within organizations. However, we stand at a unique inflection point where artificial intelligence (AI), particularly Generative AI (GenAI), is poised to reverse this pattern by democratizing access to advanced capabilities.

The Traditional Skills Conundrum

The progression of technology has traditionally demanded increasingly specialized skills, making it economically challenging for organizations, and leaders such as chief human resources officers (CHROs) and chief learning officers (CLOs), to develop talent internally. Consider modern programming: while many individuals possess the basic logical thinking required, the journey to becoming a proficient developer involves years of training and substantial investment. This reality has led many organizations to prioritize external hiring over internal development, resulting in escalating talent costs mitigated by outsourcing and missed opportunities for workforce development.

A Paradigm Shift in Learning

Drawing inspiration from Nobel laureate Daniel Kahneman's concept of System 1 (intuitive) and System 2 (analytical) thinking, we can better understand the transformative potential of AI. While previous technological advances required humans to adapt to complex System 2 thinking, AI now offers the unprecedented ability to handle these analytical tasks while working harmoniously with humans' intuitive processes. This shift fundamentally changes the equation for workforce development.

The New Economics of Skill Development

Traditional approaches to upskilling and reskilling have often proved prohibitively expensive, with organizations spending an average of $1,300 per employee on training programs that might take 18-24 months with inconsistent returns. AI-assisted learning programs are dramatically altering this calculation, reducing costs by 30-50% while shortening the return on investment (ROI) timeframe to 6-12 months. This economic transformation makes comprehensive workforce development viable for organizations of all sizes.

Modern roles demand a diverse set of competencies and traditionally require significant time and effort to master. However, AI is now transforming this landscape by reducing the number of specialized skills needed for job proficiency, effectively flattening the learning curve. This unprecedented shift makes internal talent development more accessible and cost-effective than ever before. For organizations, this represents a game-changing opportunity to develop their workforce without the historically prohibitive investment in time and inability to achieve meaningful results.

Here are the top three ways organizations can embrace AI when it comes to skills development:  

1. Make AI a Core Business Function – For organizational leaders, this transformation demands a fundamental rethinking of learning and development's role. Rather than treating it as a support function, learning must be elevated to a core business function. Like the CIO’s organization, CHROs and CLOs should explore leveraging external partners to deliver outcome-based, relevant upskilling programs. This requires not only financial investment but also structural changes to support continuous learning and development. CHROs and CLOs should also establish clear metrics for success, including reductions in time-to-proficiency, increases in internal mobility and improvements in employee satisfaction. More importantly, learning should be constant and not a “just-in-time” tactic.

2. Build an AI-Enhanced Learning Culture – Creating a culture that embraces AI-enhanced learning requires careful attention to both technological and human factors. Organizations should focus on developing blended learning programs that combine traditional skill development with AI tool proficiency. These programs should emphasize practical application, allowing employees to immediately apply new skills in their daily work while receiving support and guidance.

3. Measure Success and Scaling Impact – Success in AI-enabled skill development can be measured through various metrics, including reduced training times, increased internal mobility and improved productivity. Organizations that have implemented comprehensive AI-learning programs report up to a 60% reduction in training time for complex tasks and a 40% faster time onboarding for new roles. These metrics provide concrete evidence of the approach's effectiveness and can help justify further investment in scaling successful programs.

The Path Forward

As we move into an AI-driven future, organizations have an unprecedented opportunity to break the historical pattern of technological advancement benefiting only the highly skilled. By leveraging AI to democratize access to advanced capabilities, organizations can build more inclusive, capable and adaptable workforces. Success in this new era won't be determined by access to top talent alone, but by how effectively organizations can enhance the capabilities of their entire workforce through AI-enabled learning.

The time for action is now. Organizations that recognize and act upon this fundamental shift will gain significant competitive advantages. The future of work isn't about choosing between human skills and AI – it's about creating synergies between human potential and AI capabilities to achieve outcomes that neither could accomplish alone. This is our opportunity to create more equitable and capable organizations, where continuous learning and development are not just aspirational goals but practical realities for every employee.

This article was originally published on TrainingIndustry.com here.  

Ashwin Bharath is the co-founder and executive chairman of Revature, a talent as a service technology company, and has been in the IT industry for nearly three decades.

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