Prashasti Rastogi, Director, Coursera for Campus, and Government – India.
“India is leading the world in GenAI learning with over 2.6 million enrollments and 2 million learning hours on Coursera — that’s more than 230 years of learning in under three years. This momentum reflects the country’s potential to power the global AI talent pipeline but realizing that promise hinges on the right skilling at scale.” “As momentum builds across India — especially with more women and first-generation learners embracing AI tools like Coursera Coach — we’re focused on delivering accessible, localized, and job-aligned training to help every learner thrive in the digital economy.”
“As we approach AI Appreciation Day, it’s clear that artificial intelligence has seamlessly integrated into our daily lives, from personalised recommendations and GPS navigation to predictive text and advanced medical diagnostics. In cybersecurity, AI is proving invaluable, analysing vast datasets to distinguish threats and automating repetitive tasks to maintain secure infrastructures.
To truly harness the power of AI in our computing environments, organisations must champion AI as a tool for augmentation, not replacement. This means designing systems where AI handles repetitive tasks, freeing humans to focus on complex problem-solving, innovation, and ethical oversight. Prioritising human creativity and judgment is paramount as AI continues to advance. Alongside AI literacy, educational initiatives should emphasise critical thinking and adaptability.
However, the rapid advancement of AI also presents multifaceted cybersecurity threats. We’re seeing everything from sophisticated AI-generated deepfakes designed to trick employees into making fraudulent bank transfers, to simplistic AI-generated malware leveraging known flaws through phishing attacks. The most effective approach to defending against and mitigating these threats mirrors current cyber defence strategies: preemptive exposure management to address vulnerabilities before they’re exploited, and robust employee education on suspicious requests, no matter how compelling they may seem.
Bernard Montel, EMEA Technical Director and Security Strategist, Tenable
Invest in AI for Augmentation: Prioritise AI implementations that enhance human capabilities, empowering your workforce to focus on high-value, creative, and strategic tasks. Strengthen Cyber Defences: Implement robust exposure management strategies and ongoing cybersecurity training to protect against AI-driven threats. Champion Ethical AI Development: Foster a culture that prioritises the ethical implications of AI, ensuring its responsible and secure deployment.
By embracing these principles, we can unlock AI’s full potential while safeguarding our digital future.”
Rob Newell, Group Vice President Solutions Consulting, Asia Pacific & Japan, New Relic
“On AI Appreciation Day, it is important to celebrate the significant progress made in recent years but also recognise that the AI race is far from over. APAC’s emerging leadership in AI adoption and investment means that AI is weaving its way into our everyday lives and systems. Organisations are using large language models (LLMs) and generative AI (genAI) to optimise operations, and AI agents promise to reshape our most common digital experiences. The value that organisations receive by augmenting human capabilities with AI are clear: there’s significant cost and productivity efficiencies that help businesses unlock new frontiers of innovation.
For organisations to integrate these AI tools and realise their potential, they will have to fundamentally rethink their technology architectures. Regardless of the size, all companies are facing the same harsh reality: AI tools are expensive to use, and the costs of building new AI-backed technologies are unpredictable. Organisations that win in our inevitable AI-enabled future won’t necessarily be the ones with the best ideas; instead, the winners will be those that have figured out how to effectively balance cost, value, and performance.
Despite the rapid evolution of generative AI technology, the fundamental questions underpinning the cost of AI are simple: How often do companies query an LLM and how much do those queries cost? By controlling these queries effectively and getting the most out of every call by adopting AI-supportive techniques such as retrieval augmented generation (RAG) and agent frameworks, companies can more reliably predict and lower their AI expenses.
Historically, observability has offered organisations the ability to detect and respond to anomalies in their systems and optimise performance. But with AI driving a revolution in processes and architectures, observability needs to evolve to keep pace and continue providing users with a window into their own systems and processes. New Relic research found that 39% of IT leaders in India regarded AI as a key driver for observability adoption.
Organisations need intelligent observability to rise and meet the challenge brought by AI. This next phase of observability will be preventive, self-healing, and autonomous, so that it can surface the right insights to the right person at the right time. AI monitoring tools give companies end-to-end visibility into their AI-integrated workflows, but more importantly real-time insight to troubleshoot, compare, and optimise approaches to using LLMs to improve their features or offer brand new experiences. This allows companies to adjust when necessary to manage costs, improve performance, and reduce common issues that can cause costly hiccups.
In the long term, AI will truly become ubiquitous when we can reliably achieve the right balance between cost, performance, quality, value, and reliability. Companies developing AI features need to identify the right use cases to get the most out of those LLMs while still delivering value and innovation to their customers.
Observability helps companies maintain reliability, quality, and efficiency throughout all components of the AI technology stack, alongside services and infrastructure, so that they have the data they need to make decisions that limit expenses, maximise ROI, and accelerate business outcomes.”