Building AI competencies and ensuring the right talent is available, is a critical part of our strategy: Makarand Joshi, Global Head – IT and Digital Sourcing, Tata Technologies
In a rapidly evolving digital landscape, organisations are turning to AI and machine learning to revolutionise operations, enhance efficiency, and unlock new opportunities. Makarand Joshi, Global Head – IT and Digital Sourcing, Tata Technologies, shares insights into how his organisation is implementing AI-driven initiatives, the impact of generative AI across industries, and their strategic vision for integrating these technologies into the future roadmap. From predictive analytics for incident management to automating complex processes, Joshi discusses the challenges and rewards of embracing AI at scale, offering a glimpse into what’s shaping the future of digital transformation.
Can you take us through some of the AI/ML driven digital initiatives you have taken? What has been the impact?
We have implemented several AI-driven initiatives aimed at enhancing our IT operations through automation and predictive analytics. One of the key areas we focused on was predictive analytics for incident management. By utilising AI-powered tools, we can now monitor system logs and performance data, enabling us to predict when a server or application might fail. This allows us to proactively address issues before they escalate. Similarly, we applied AI for automated patch management, streamlining security updates to minimise disruptions across our IT environment. Leveraging tools like Microsoft Intune, we can automatically identify and prioritise security vulnerabilities, ensuring critical patches are applied seamlessly. Another significant initiative was capacity and performance optimisation using Nutanix’s AI-powered infrastructure. This system helps us automate resource management and ensure high performance by effectively balancing workloads. These initiatives have collectively improved operational efficiency, reduced downtime, and enhanced system reliability, making our IT operations more resilient and responsive.
How do you see the traction for GenAI in the industry?
Generative AI (GenAI) is experiencing rapid growth across various industries, becoming a transformative force in multiple sectors. In design and engineering, companies are leveraging GenAI to create optimised product designs and prototypes. For example, Autodesk Fusion 360 uses generative design to help engineers achieve better performance with lower material costs. Similarly, in software development, tools like GitHub Copilot are now assisting developers by suggesting code and improving productivity. Healthcare is another sector where GenAI has made a significant impact by generating models for drug discovery and predicting patient outcomes. During the COVID-19 pandemic, AI played a crucial role in accelerating the development of treatments and vaccines. The gaming and entertainment industry is also utilising GenAI to create immersive virtual worlds, character animations, and music compositions, while finance and risk management are using it for generating insights from data, automating risk models, and detecting fraud. The widespread adoption of GenAI is revolutionising these industries by enabling personalised experiences, optimising processes, and driving innovation.
What are some of the areas in which you are using GenAI? What impact does it have?
We are at the early stages of exploring GenAI and are carefully assessing its potential in various areas based on objectives like improved efficiency, personalised experiences, and cost savings. One of the primary areas we are targeting is the employee onboarding process. With GenAI, we aim to automate documentation, personalise training plans, and streamline onboarding tasks, enhancing the overall experience for new hires and reducing the workload on HR teams. Additionally, we are considering using GenAI in our Source to Settle (S2S) processes to optimise supplier research, automate contract generation, and support demand forecasting. These applications can significantly transform our sourcing activities by automating routine tasks, improving decision-making, and fostering stronger supplier relationships. By integrating GenAI into these areas, we anticipate improvements in efficiency, scalability, and user satisfaction.
How do you plan to integrate AI strategically into the organisation’s IT roadmap, and what challenges do you foresee in this implementation?
Integrating AI strategically into the organisation’s IT roadmap requires a comprehensive approach to ensure alignment with business goals, resources, and capabilities. Our first step involves a thorough assessment of our current IT infrastructure to identify where AI can provide the most value. Next, we plan to focus on identifying high-impact use cases, such as automating processes and optimising customer experiences. Building AI competencies and ensuring the right talent is available is also a critical part of our strategy. This might involve upskilling existing teams or hiring data scientists and AI engineers. A strong data management and governance framework is essential, as AI relies heavily on large, high-quality datasets for training and decision-making. Additionally, we will explore cloud and edge computing integration to handle the intensive computational resources AI requires. We also recognize the importance of addressing AI ethics, compliance, and security to ensure that AI models are fair, transparent, and compliant with regulations.
However, we foresee several challenges in AI implementation. Data quality and availability can be significant obstacles, as poor or fragmented data sources can hinder AI model training and deployment. Change management is another challenge, as integrating AI may lead to resistance from employees concerned about the impact on their roles. Scalability is also a concern, as AI solutions require substantial computational resources. Finally, ethical considerations and biases in AI models need to be managed to prevent unfair or discriminatory outcomes. We are committed to addressing these challenges through data governance strategies, transparent communication, and adopting scalable cloud-based platforms to ensure a smooth AI integration.
What are the top 5 digital or technology focus areas for the future?
In the next six months to a year, organisations are expected to focus on several key digital and technology initiatives. Enhancing cybersecurity measures will be a top priority, given the increasing threats and stringent regulatory requirements. Organisations will also continue to invest in AI and machine learning to automate processes, gain insights from data, and improve decision-making. Transforming customer experiences through digital channels and personalised interactions will be another major area of focus, as businesses aim to offer seamless and engaging experiences. Additionally, advancements in data analytics and business intelligence will drive data-driven decision-making, with companies investing in self-service analytics platforms and real-time dashboards. Finally, cloud migration and optimisation will remain a significant focus, as organisations look to enhance scalability, flexibility, and cost-efficiency by adopting hybrid or multi-cloud strategies. These initiatives reflect a growing emphasis on leveraging technology to boost efficiency, security, and innovation, positioning organisations to achieve their strategic goals in an increasingly digital landscape.
