Learning By Sharing: How GenAI Can Be The Giving Tree
Nitin Rakesh is the CEO and Managing Director of Mphasis and coauthor of the award-winning book 'Transformation in Times of Crisis.'
Our world is witnessing a wave of advancements, from the emergence of automation to the implementation of artificial intelligence. For senior leaders, this acceleration presents opportunities and challenges. While striving to adopt cutting-edge technologies, they are also attempting to ensure these align with business objectives and ethical standards.
One of the most transformative yet polarizing of these technologies is generative AI (GenAI). While it promises new avenues for creativity, problem-solving and efficiency, it also raises apprehensions about its impact on typical decision making processes.
In this sense, GenAI remains a bit of a paradox for business leaders, as it is both a source of curiosity and a cause for concern. While executives see its immense potential as a transformative tool capable of boosting creativity, streamlining operations and generating efficiency gains across functions, there is an underlying wariness about how it can disrupt established workflows.
In the face of GenAI's dual nature, executives are navigating a critical challenge of how to integrate this powerful technology without losing the distinctiveness of human intuition.
Rather than framing GenAI as a disruptive force to be managed, a more productive perspective may be to see it as a collaborator—an enabler of shared growth and continuous learning. When viewed this way, I believe GenAI can become more of a partner in learning and development with whom leaders can foster a mutually beneficial relationship mirroring the spirit of mutual giving.
However, embracing this potential demands a shift in mindset. It invites leaders to move beyond passive adoption and toward active stewardship of the human-AI dynamic. This reframing introduces important questions: Are leaders thoughtfully measuring GenAI's contributions, not just in efficiency but in depth and relevance? Are they engaging with it in ways that reflect their own values and expertise—training it, shaping it and learning from it in return? And perhaps most importantly, is their ongoing interaction with GenAI expanding their capacity for insight and growth?
AI is not an autonomous force—it is a reflection of the data, intentions and perspectives we bring to it. Its development is inseparable from human input. The real opportunity lies not just in what AI can do for us, but in how the human-AI relationship can evolve into one of reciprocal enrichment.
Consider an iconic children's literature classic: The Giving Tree by Shel Silverstein. In the story, the tree selflessly offers its apples, branches and eventually its entire trunk to the boy.
This tale invites us to reflect on the nature of giving, taking and the balance of relationships. In much the same way, GenAI can be seen as a tireless provider—offering its computational power, adaptability and insights to organizations. Yet unlike the tree, GenAI does not give from a place of emotion or altruism. It responds to the quality of its inputs, the clarity of its training and the intentionality of its use.
This analogy prompts a critical shift in how leaders approach AI. While it's tempting to focus solely on what GenAI can do for us—automating tasks, generating insights, fueling innovation—the more profound question is: What are we giving back? How are we shaping, stewarding and engaging with AI to ensure it grows in a direction aligned with human values and long-term impact?
If organizations treat AI merely as an extractive tool, they risk building unsustainable dependencies. But if leaders approach the technology as a partner in co-evolution—offering guidance, expertise and ethical oversight—then GenAI becomes more than a resource. It becomes a trusted collaborator, capable of growing alongside the organization.
Beyond GenAI's adoption, leaders must know its value, inspiring their teams to integrate AI into daily workflows. Evangelizing AI within the executive team is crucial to ensuring collective alignment, fostering a culture where AI is viewed as an augmentation of human expertise rather than a replacement. This requires a deep understanding of what GenAI can do, allowing leaders to define where it can have the most meaningful impact.
For GenAI to truly benefit organizations, leaders must anchor its application in clear, measurable business objectives. Identifying the right problems for GenAI to solve and aligning its deployment with strategic goals ensures its use remains practical and value-driven.
Governance is equally critical, ensuring that AI-driven decisions uphold ethical standards and comply with regulatory frameworks. Data quality, infrastructure readiness and an AI-savvy workforce further determine how effectively GenAI can be leveraged. The organizations that invest in these foundational aspects will be best positioned to turn AI into a long-term growth partner like the enduring relationship between the boy and the Giving Tree.
When leaders take ownership and adopt an interactive approach, they create an environment of collaboration. Talented individuals are also drawn to such leaders—not just for their effectiveness but for their generosity and team-focused mindset.
It is crucial that leaders actively coach GenAI so it evolves in tandem with organizational needs. By continuously refining and adapting its algorithms, leaders can make GenAI more iterative, refined, intelligent and thoughtful. Much like mentoring human employees, providing AI with feedback allows it to improve over time.
For instance, organizations have enhanced customer service chatbots by training them on real user interactions, enabling them to respond with greater empathy and accuracy. These iterations ensure that AI evolves to handle more complex queries, improving both customer satisfaction and operational efficiency.
With each successive interaction, AI becomes better suited to the evolving needs of an organization. This illustrates the timeless relevance of Moore's Law, which predicts that computing power will double every two years. Just as computing capacity expands exponentially, so too can GenAI's ability to solve complex problems as long as it is actively coached.
As AI models become more advanced, the need for a growing network of skilled, human trainers becomes essential for their continued improvement. The constant feedback and refinement will fuel GenAI's exponential development—enhancing its capacity to transform businesses.
The key to thriving in this new era of AI is learning how to strike the right balance with thoughtful strategy. As organizations continue to work closely with GenAI, partnerships will evolve, leading to exciting outcomes. What will be crucial to keep in mind is that this exchange between human and machine fosters sustainable progress built on collaboration and just practice.
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