Tom Brown
CHRO
Druva
Episode 168
Beyond Fear: The AI Job Transformation Demands Learning and Risk-Taking
Current chapter: Built by People podcast features insights from world's top HR leaders
Built By PeopleMay 30, 2025 · 8:29
Thesis
“The future impact of AI on jobs is largely unknown, but organizations and individuals must proactively embrace learning, curiosity, and responsible risk-taking to leverage AI's augmenting benefits and navigate its societal transformation, rather than succumbing to fear.”
Show notes
Navigating AI and Workforce Transformation with Tom BrownIn this episode of the Built by People Podcast, the host welcomes Tom as they delve into his diverse career journey across various countries and industries, culminating in his current role at Druva.
Tom shares insights on the intersection of AI and HR, addressing concerns about job displacement and the potential for AI to create and enhance job roles. He emphasizes the importance of curiosity and proactive learning in adapting to technological advancements.
The discussion includes specific examples of AI implementation within his organization, such as improving customer service operations.
Tom also outlines strategies for preparing the workforce for an AI-augmented future and offers his parting advice on embracing rapid change and leveraging opportunities for positive societal impact.
00:00 Welcome and Introduction
00:41 Tom's Career Journey
01:35 Addressing AI and Job Concerns
03:47 Balancing AI Implementation and Workforce Transformation
05:23 Successful AI Implementation Examples
06:15 Preparing Workforce for AI Future
07:24 Parting Advice and Conclusion
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What you'll take away
- 1The true impact of AI on job creation versus erosion is still uncertain, making adaptability crucial for the workforce.
- 2Individuals and organizations must cultivate curiosity, explore AI's capabilities, and be willing to take calculated risks to stay ahead.
- 3AI can significantly augment roles, enabling employees to shift from administrative tasks to more value-added work, as evidenced in customer services.
- 4Fostering an AI-positive organizational culture that encourages exploration while maintaining checks and balances for data security is key to successful adoption.
- 5Balance the fear of AI's disruptive potential with the consideration of positive societal upsides, such as increased productivity and new work models like the 4-day week.
What most organizations get wrong
- •Tom Brown pushes back on definitive predictions about AI's job impact, emphasizing the wide range of possibilities and the unknown nature of the revolution.
- •He states pragmatically that AI is not only predicted to take jobs but is 'already taking people's jobs away,' countering narratives that solely focus on future or net-positive job creation.
In Tom's words
“we don't know. And there's lots of people out there saying, we know what's going to happen. But if you listen to the reports coming out of the World Economic Forum or Goldman Sachs or McKinsey, the range of possibilities from it's going to add tens of millions of jobs to it's going to erode hundreds of millions of jobs is really clear.”
Highlights the significant uncertainty and wide range of expert predictions regarding AI's impact on employment, challenging confident forecasts.
“AI not only will take people's jobs away, it's already taking people's jobs away. The interesting balance to that is what are the jobs it's going to create? What are the jobs it's going to augment and make better?”
Offers a direct and realistic statement about AI's immediate impact on the workforce, balancing job displacement with creation and augmentation.
“getting as far ahead as we can on knowledge of AI, what AI can do, and the opportunities, rather than getting paralyzed by the fear of what it might deliver societally, is going to be really important. So it's really trying to get people to be curious, to explore, and to take some risks with AI.”
Emphasizes proactive learning, curiosity, and a willingness to experiment as crucial strategies for individuals navigating an AI-driven future.
“it was getting everybody in the team to a certain level and understanding of how AI was going to be used and what the opportunities were for them to see it as a powerful augmentation and not as a potential kind of replacement and an important kind of philosophy to start with.”
Provides a practical example of successful AI implementation by reframing it as an augmentation tool rather than a job threat for employees.
“we have an AI task force in the company. So AI is carefully looked at as we implement it, but it's being looked at from the sector of we want this to happen, not we don't want this to happen.”
Illustrates a progressive and encouraging organizational philosophy towards AI adoption, balancing eagerness with necessary oversight for responsible implementation.
“the folks that tend to do worse are the ones who are most worried about it and therefore the most risk-averse.”
A strong piece of parting advice encouraging proactive engagement and a less risk-averse mindset to benefit from technological revolutions rather than being left behind.
The problems this episode addresses
- •Organizations struggle to effectively address employee anxieties and concerns about AI replacing their jobs.
- •Companies face the challenge of balancing rapid AI implementation with the complex process of workforce transformation and upskilling.
- •The inherent risks of large language models, particularly concerning data scraping and protecting confidential information, pose a significant challenge for safe AI adoption.
- •Cultivating a company culture that encourages curiosity, exploration, and responsible risk-taking with AI, rather than resistance or paralysis by fear, is a key hurdle for HR leaders.
In this episode
Built by People podcast features insights from world's top HR leaders
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Topics covered
Organizations and entities mentioned
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