As architects of the digital future, Marlabs is committed to creating a tomorrow that transcends today's boundaries. Marlabs is unique in his lab for digital alchemy, design-driven solutions, innovation, transformative impact, and emotionally moving technology.
Sriraman Raghunathan, Global AI Leader at Marlabs, tells us more. Excerpt from the interview:
DQ: How can companies effectively integrate AI and ML innovations into product engineering to improve customer experiences?
Sriraman Raghunathan: Companies are using AI/ML in the product engineering lifecycle to better understand requirements, generate user stories for backlog management, predict and identify potential risks, and create better visuals. You can automate design and UI development and provide education to help customers understand the benefits of leveraging AI. Features and how to use them effectively. These collectively improve the customer experience.
DQ: What strategies can companies adopt to seamlessly integrate AI into core business functions and operations to improve productivity and efficiency? How was Marlabs able to leverage this? ?
Sriraman Raghunathan: The strategies we utilized include education, awareness, and training programs tailored to each business function, baselined productivity and efficiency KPIs for business functions, and continuous monitoring and measurement of improvements. Includes piloting selected AI tools and technologies to enhance daily workflows. Determine your KPIs and ROI.
DQ: In what ways do you think AI will prioritize human empowerment over human elimination in the future, especially in the context of business operations?
Sriraman Raghunathan: With an augmented intelligence approach, AI does not replace humans, but augments them by automating repetitive tasks, providing insights, and supporting decision-making, increasing productivity and job satisfaction. This will lead to improved performance.
The use of AI often leads to job transformation with the emergence of new roles, creating opportunities for reskilling and upskilling. The use of AI in certain industry sectors also improves safety and risk management by predicting and preventing accidents and predicting risks. This not only protects your employees, but also increases operational resiliency and reliability.
DQ: What specific challenges do companies face when building a data talent pool in India, and what approaches can be taken to address these challenges? What approach do you take to address this?
Sriraman Raghunathan: Marlabs, like other digital services companies, is facing a shortage of talent in India, especially in the AI space, due to rising hiring costs, skills gaps and, more importantly, competitive pressures from product companies and a vibrant startup ecosystem. Pool is in trouble.
The approaches taken by Marlabs to address these include upskilling existing talent pools, better compensation structures for AI-enabled talent, partnerships with academia, an environment that fosters innovation, and the provision of higher quality work. and so on.
DQ: Please outline Marlabs' roadmap to accelerate AI with a focus on upskilling employees. And are you planning how to effectively implement this strategy?
Sriraman Raghunathan: Marlabs has launched a comprehensive AI upskilling program across its technology workforce, including data, engineering, test, infrastructure, and experience areas.
The approach to effectively implementing this strategy includes identifying skills gaps and areas for upskilling to support AI initiatives, and clear learning objectives that align with the organization's AI strategy and comprehensive support curriculum. definition, flexible training methods, and hands-on support experience. Monitor progress against infrastructure and recognition and reward systems, learning KPIs, and measure its business impact.
Executing this strategy also requires strong leadership support, appropriate resources, investment in upskilling employees, and a commitment to fostering a culture of innovation and learning.
