While the story around reskilling and upskilling has had many chapters, the acceleration around AI has created a new urgency for employees to adopt new skills quicker than ever before. However, I know that many companies, i.e. their HR teams, encounter some very real roadblocks when trying to stand up impactful upskilling initiatives. There are many challenges that HR departments need to overcome, such as lack of financial support and little buy-in from the rest of the c-suite meant we struggled to leverage new technologies or create scalable training solutions.
Today, AI is rapidly transforming almost every role in the workforce – and employees are keenly aware of it. In fact, SAP SuccessFactors research found that while 87% of employees believe it’s important to their company that they improve their AI literacy, 57% say their understanding of AI is currently a barrier to their success at work, and 63% believe it will be a barrier in the future.
Organizations need to facilitate more upskilling opportunities around AI – and there is only one way to do this at scale: by making learning a critical performance metric for all employees and by using AI to bolster their learning programs.
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Turning Learning Efforts into a Competitive Advantage
In my experience as CHRO, I’d often see organizations struggle to reskill and upskill their employees because they didn’t approach the problem in a strategic way. Today, AI can make it easier to drive effective learning and development.
AI-enabled career pathing and skills gap analysis can help employees identify internal mobility and upskilling opportunities. Most HR teams don’t have the bandwidth needed to truly analyze employees’ individual roles, skills, performance, and learning styles. AI, however, can assess skill sets and identity gaps to provide tailored training content. This leads to recommended targeted training that can help them reach desired competencies for roles, ultimately making upskilling a smoother, more seamless process than ever before. AI can also help provide review assessment scores to give a clear view of what’s working and what isn’t, saving HR leaders crucial time in tracking progress and implementing new resources.
By providing a clear view of the organization’s objectives, these L&D efforts can ensure that employee upskilling efforts are aligned with current and forecasted skills needs – turning learning into a competitive advantage, rather than an afterthought.
What’s different today is that employees have already started learning about AI on their own and are already seeing the impact of AI on their jobs. Recent research from SAP SuccessFactors found that more than half (58%) of employees report that they have already saved an average of 52 minutes a day by using AI tools at work. Learning about AI isn’t just something to help prepare for the future; it’s already transforming how we work and make decisions.
Organizations that can tap into this appetite to learn about AI can build a culture where experimentation and learning is widespread – creating more innovation, creativity, and efficiency. Research from Deloitte found that high-performing organizations are 19 times more likely to use cognitive technologies like AI for design and development of learning content and roughly 50% organizations using AI reported overall cost savings and efficiencies.
Putting L&D and Upskilling at the Heart of Workforce Strategy
At Tata, we embarked on a multi-year learning transformation designed to update employee skills across the company. We used on-demand learning platforms powered by AI to develop personalized learning paths. This approach caters to three broad learning categories employees could utilize:
- Learn Whatever You Want: Unlimited learning opportunities, primarily through free, freemium and low-cost but high-quality content
- Targeted Learning: Content tailored to different roles and guided by respective managers
- Academies: Longer-term learning that leads to certifications after assessment
This tiered learning structure drove strong results, quadrupling internal hiring within a year and nearly tripling average learning days since the program began in 2017 – going from 3.5 to approximately 10 days a year.
Employees can choose their courses while developing new skills and certifications that will serve them well in their career progression within the organization, or elsewhere. By breaking out varying levels of learning, we could build a foundation that provides the data and insight to drive ongoing growth.
For someone like a mid-level software engineer, whose work is already being augmented by AI, these learning programs could help them evolve from traditional coding roles to higher-leverage positions. AI can suggest several future-ready paths, taking them to a position where they’re shaping how code is written across teams rather than just writing it. This way, their skills are not being replaced – but rather amplified by AI.
These results make the case clear: Achieving real L&D impact can only be done through proper investment. The time is now. As AI tools evolve at an ever-increasing speed, waiting to strengthen these efforts will only lead to organizations falling further behind their competition.
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