6 months ago
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Speaking at Cypher 2024, India’s Biggest AI Conference by AIM Media House, Shashank Dubey, co-founder and chief revenue officer at Tredence explained that the key to thriving in the Generative AI era lies in redefining how we perceive job roles. He stressed the importance of focusing on the outcomes delivered by skill sets rather than the skills themselves.
“It’s important not to define our jobs by the skills we possess. Instead, we should define our roles by the outcomes those skills deliver, and those outcomes are business outcomes,” he said. For instance, he compared two types of engineers, one whose sole expertise was in Hadoop, and another who ensured enterprise data was delivered effectively to meet business needs.
Apache Hadoop is an open-source software framework designed for distributed storage and processing of large datasets across clusters of computers using simple programming models. Back in 2013, 2014, 2015, and 2016, moving data into Hadoop served as an example of modernization.
“The latter engineer will have far more opportunities because they focus on the outcome,” Dubey explained. “As leaders, we must encourage our teams to embrace this mindset, prioritising results over rigid skill definitions.”
Embrace Change, Fear Not About AI
Dubey shared a personal anecdote from a recent Uber ride he took from LaGuardia Airport to Manhattan. His driver, Mike, a 75-year-old retired engineer, initiated an insightful discussion about adapting to change and being resilient.
Mike, who had started his career sorting physical mail in Manhattan’s corporate offices, had navigated several industry transformations throughout his life.
“At 17, I sorted physical mail, but as emails took over, I knew I had to pivot,” Mike shared. “I became an executive assistant and later transitioned into logistics as e-commerce emerged. Now, I drive for Uber and even dabble in learning Python.”
Generative AI Is Like Formula One
To illustrate the complexities of generative AI, Dubey drew a parallel to driving a Formula One car. “Just like a Formula One car requires special driving skills, specific traffic regulations, and a specialized racing track, generative AI is also a full ecosystem and platform. This is not just a skill set game,” said Dubey.
Dubey also highlighted a staggering disparity in investments within the AI sector. “In the past year, there has been about $200 billion invested in acquiring chips, but less than $5 billion has gone into developing the software and services needed to utilise those chips effectively,” he said.
According to him, this gap presents a significant opportunity for organizations willing to invest in the right solutions.
The Roadmap to Effective Leadership
Dubey outlined four essential pillars for leadership in the GenAI era: Tech Literacy, Accountability, Virtual Orchestration, and Responsible AI.
Tech Literacy: According to Dubey, leaders must familiarise themselves with generative AI applications. He shared a successful initiative at a U.S. telecom company that involved business leaders developing their own ideas and collaborating with analysts to explore feasibility. “This approach teaches leaders the art of what is possible,” he noted.
Accountability: As organisations embrace AI, Dubey said that accountability becomes paramount. Leaders must ensure that their teams not only understand AI but are also responsible for its ethical deployment. Citing Tesla as an example, he noted that whenever inadvertent accidents or incidents occurred during Tesla’s development, the company took accountability for those events, regardless of who was at fault.
Virtual Orchestration: Dubey emphasised the importance of creating an environment that fosters collaboration between humans and machines. This involves designing workflows that use AI to augment human decision-making rather than replace it.
Responsible AI: With great power comes great responsibility. Leaders must advocate for ethical AI practices that prioritise transparency, fairness, and accountability.
The Future is Collaborative
In closing, Dubey reiterated that the future of work in the Generative AI era is not about human versus machine, it is about human-machine collaboration. As leaders, it is essential to cultivate an environment where team members are empowered to adapt and innovate in response to technological advancements.
“Human-machine collaboration is very important. The biggest destruction of value occurs not because the models are poor or the sites are lacking, but because human change management is missing,” he concluded.
