Episode 6 | Q Hamirani

As AI continues to evolve, its influence on job structures, required skills, and organizational dynamics is being transformed. RippleHire founder Sudarshan Ravi spoke to PeopleGPT founder Q Hamirani had a candid discussion on how AI is reshaping traditional HR functions, from automating tasks to redefining roles, and discussed the urgent need for HR and Talent Acquisition leaders to build expertise and adapt strategies.

Q Hamirani is a distinguished business leader and executive coach with over 20 years of experience across startups, venture growth, private equity, and Fortune 100 companies in 25+ countries. He’s a Forbes contributor, recently featured with his article on AI in HR, and a guest faculty member at London Business School. As the founder of a thriving community of people leaders and AI enthusiasts, Q has also made significant impacts at Paper as Chief People & Communication Officer and at Airbnb as its first global People Operations leader. Passionate about personal growth and the arts, Q combines his extensive expertise with a commitment to innovation and creativity.

How do you think AI will change HR?

I believe AI has the potential to fundamentally change how jobs are performed. As tasks become increasingly automated and enhanced by AI tools, the nature of jobs and the required skills will shift. This evolution is already happening, altering traditional job structures and the way humans interact with technology in their roles.

For HR, this means a significant transformation in how they partner with business functions. Unlike past transformations with clear roadmaps, the future with AI is uncertain, and HR must adapt by identifying new skills, crafting policies, and ensuring effective integration of technology. The key challenge will be supporting organizations through this ongoing, unpredictable change. HR needs to stay ahead and understand AI’s impact to ensure organizations don’t fall behind.

How critical is it for HR and TA leaders to build expertise immediately, given the rapid changes in technology and the unclear end state? How can they help their organizations navigate this transformation effectively?

Organizations will adopt AI at different levels, but HR and TA leaders should encourage teams to embrace ambiguity. Given the current economic environment, it’s crucial to allow room for experimentation while managing risks. Start with small, simple use cases, like using AI for tasks such as writing job descriptions. This approach allows teams to gradually integrate AI, refine processes, and identify the necessary skills for the future. Leaders should support and fuel experimentation, ensuring teams can adapt to the evolving technological landscape.

How do you see jobs being restructured in organizations as they align more with candidate personas?

AI will dramatically change organizational structures. The need for entry-level workers will decrease as AI can handle many tasks previously done by humans. However, the demand for experienced professionals to oversee and validate AI outputs will rise. This shift will create excess capacity, leading to either leaner organizations or the emergence of new, smaller businesses. Ultimately, AI will boost efficiency and innovation, but it also raises questions about job displacement and workforce adaptation.

How can organizations leverage AI-generated capacity to accelerate growth and innovation?

HR leaders are uniquely positioned to identify and harness excess capacity created by AI. By analyzing organizational capacity and output, HR can reallocate resources to accelerate strategic initiatives. Similar to the impact of Excel on productivity, AI has the potential to supercharge human capabilities and drive innovation. However, unlike Excel, the rapid advancement of AI requires a period of adjustment and learning to fully realize its benefits.

How does AI-driven commoditization of basic tasks impact human creativity and innovation?

As HR leaders, you’re uniquely positioned to assess and leverage excess capacity within your organization. By aligning this capacity with business strategies, you can accelerate progress and achieve long-term goals more quickly. Just as Excel transformed productivity by moving beyond calculators, emerging technologies have the potential to drive similar advancements. However, the fast pace of tech development requires time for adjustment and calibration. Future tools might simplify complex tasks through voice commands, making sophisticated functions more accessible. Be cautious of accuracy and overconfidence in AI outputs, but recognize the significant potential for positive impact.

How can organizations implement safeguards to prevent AI from generating incorrect or misleading information?

To mitigate risks with AI, especially regarding sensitive data, start small and in a controlled manner. For instance, begin with tasks like automating backend processes or creating job descriptions using public information. Avoid exposing employee or candidate data until you fully understand AI’s capabilities and limitations. Ensure leadership buy-in and involve relevant teams to oversee and evaluate AI experiments. Be cautious with data privacy, as leaked information can harm both individuals and your brand. Gradually scale up your AI initiatives while maintaining strict safeguards against data exposure.

Why can’t HR take ownership of enabling AI change within the organization?

HR can handle some aspects of AI implementation, such as setting broad usage guidelines, consolidating tool access, and ensuring consistent adoption. HR is well-suited for change management and establishing policies, like prohibiting the sharing of employee data. However, HR cannot fully own the development and testing of specific AI tools, particularly those used outside HR functions. Functional leaders should take responsibility for experimenting with and deploying these tools. While HR can centralize change management and support new talent and resources, functional owners must ensure proper integration and business impact assessment. Thus, HR has an umbrella role in overseeing AI adoption, while individual functions manage their specific tools and deployment.