Beyond Cubicles: Navigating the Future with Tech-Enhanced Employee Experience

By: Neha Gupta, VP-People, Material

With two decades of international experience, Neha is a people and Business Leader whois passionate about data led diversity, culture, performance, and fairness that make organizations and people successful.

In a recent interaction with Women Entrepreneur Magazine, Neha shares her views and thoughts on the challenges of maintaining a cohesive learning culture in a hybrid work environment as well as how learning can be inclusive to all in an organization.

In what ways can HR leverage AI and technology to enhance employee training and skill development?

AI, both as a tool and a scientific field, currently is at a fascinating juncture in its journey. Every day, we see iterative innovations that open up new possibilities. Notably, AI has become ingrained in many facets of daily life, with mobile phones being a prime example of this. The ubiquitous nature of AI necessitates a revaluation of how organizations and individuals harness its potential, particularly in the context of learning. Organizations must reassess the learning needs of individuals and tailor curricula accordingly. Drawing parallels to the evolution brought about by computers, where training shifted from paper-based methods to a dynamic, paperless format, AI brings about a new paradigm. With AI, traditional learning roles, such as content writers, trainers, and assessors, could potentially be automated. Tasks like training needs analysis may become seamlessly integrated into organizational processes.

While AI can streamline many aspects of learning, it does not render human roles obsolete. The essence of human interaction, coaching, empathy, and connection remains crucial. Despite the automation of tasks like content design, the need for human involvement in fostering a conducive learning environment, providing coaching, and maintaining interpersonal connections persists. Recognizing this, organizations should not overlook the importance of learning specialists who can provide the human touch in the ever-evolving landscape of AI-driven education.In brief, it is imperative for organizations to strike a balance, leveraging AI for efficiency while ensuring that the human element remains integral to the learning experience.

How should we plan to address the challenges of maintaining a cohesive learning culture in a hybrid work environment?

The advent of the hybrid work model has significantly transformed our daily lives, particularly in terms of communication through phones. Creating a cohesive learning culture within such a dynamic work environment poses a unique challenge. The reliance on hybrid work, where some individuals operate virtually while others are physically present, makes it tempting to lean solely on eLearning and pre-made modules. However, fostering a cohesive learning culture demands that organizations ensure live learning opportunities are readily available and customized to unique learning needs.To achieve this, organizations must invest in tools that facilitate live learning sessions, ensuring that both in-person and virtual participants have a conducive environment for interaction. Equally crucial is the proficiency of those delivering the learning content, aligning with the curriculum designed to cater to diverse audiences. Open communication tools should be integrated to enable participants to see and engage with each other during these sessions. Additionally, beyond formal sit-down learning, organizations should focus on creating a holistic learning experience. This involves pre-learning and post-learning programs where participants can interact on a live basis, discuss their learnings, collaborate on projects, and engage in assessments. Additionally, coaching and mentoring should be seamlessly integrated into the live environment, providing valuable support and guidance.

In your opinion, what role do data analytics and AI play in measuring and optimizing employee learning outcomes?

The integration of data analytics and AI has not only been instrumental in assessing past learning outcomes but is now poised to advance into predictive learning insights. Beyond measuring the effectiveness of learning through existing models such as Kirkpatrick, the next frontier involves leveraging AI advancements to gain predictive insights into learners' behaviors and preferences.Examining learning data can unveil valuable information about engaged and disengaged learners, their preferences, and their responsiveness to various tools. By correlating learning data with work and engagement metrics, organizations can predict factors such as employee engagement, potential attrition, and talent assessments. This predictive capability enables strategic decision-making, identifying individuals with high learning agility and potential for growth or internal mobility.

Furthermore, the synergy between AI, data analytics, and learning extends to industry insights. By aligning organizational data with market trends, companies can gain a deeper understanding of industry dynamics. This proactive approach allows businesses to anticipate changes, such as the potential impact of AI on their business model, and prepare accordingly. This foresight enables organizations to develop the necessary skills among their workforce to adapt to future industry shifts.

In a hybrid work scenario, how can we ensure equal access to learning opportunities for both remote and in-office employees?

When organizations design learning initiatives, it is crucial to ensure the learning mode accommodates both in-person classroom settings and remote scenarios, facilitated through virtual learning platforms. The entire learning process, from delivery and assessments to exercises, should be strategically structured to function seamlessly in both virtual and live environments. This includes the incorporation of eLearning or other offline methods to complement the ongoing learning experience.Considering the plethora of tools and technologies available, such as Teams, Zoom, or WebEx, it is imperative to factor them into the learning design. Organizations must evaluate if their content designers and learning delivery leaders are proficient in adapting to the diverse needs of remote learners and those working from the office. Moreover, the learning environment should be sensitive to the realities of remote work, acknowledging that not everyone has a dedicated home office. Individuals may be juggling family responsibilities, and creating a culture that motivates remote participation while recognizing and accommodating unique situations is paramount.To achieve this, fostering empathy and acceptance for diverse learning contexts is crucial.

How can learning be inclusive to all in an organisation.

Ensuring diversity in the workforce remains a fundamental challenge, with a particular emphasis on increasing women's representation, which lags even behind global benchmarks. Additionally, there is a regional disparity in workforce composition, often influenced by the geographical location of organizations. Beyond gender and regional considerations, organizations often neglect consciously building diversity, be it in terms of caste, neurodiversity, or other attributes.Turning to the learning aspect, inclusivity becomes paramount. In hybrid work models, there is a need to challenge the mindset that devalues remote workers' commitment to learning. Acknowledging the diverse situations of employees, such as young parents or those without a dedicated home office, is crucial for effective learning programs. Moreover, addressing neurodiversity is essential in learning programs. Incorporating features like caption subtitles and creating an environment where everyone, regardless of communication challenges, feels comfortable speaking up is key. Learning creators and delivery professionals need to shift their focus from traditional methods to embracing inclusivity, diversity, and flexibility in their approach. This evolving role emphasizes human intervention in creating a learning environment that caters to the unique needs of each individual, rather than a one-size-fits-all approach.