Vishwadeep Khatri

Calling AI "probably the single biggest ​opportunity" for ​the industry and comparable to the discovery of electricity or ⁠the internet, he said current debates focus too narrowly ​on automation while missing a broader structural shift. Shetty argued that, much like cloud computing, AI will broaden rather than diminish the responsibilities of service providers. View the full article

Everyone at last week’s India AI Impact Summit was debating power, water, and capital. Those are necessary conversations. But India’s AI infrastructure story has two other protagonists that nobody is talking about and without them, the puzzle never gets finished. View the full article

During the session, Altman dismissed viral claims that each ChatGPT query requires the same energy as charging a smartphone, saying they were “totally fake.” He also deemed as misinformation the reports of each ChatGPT query using up about 17-18 gallons of water. View the full article

AI companies, groups tied to the industry and top executives of both donated at least $83 million in 2025 to federal campaigns and committees, according to a New York Times analysis of Federal Election Commission filings. That figure, combined with a $65 million push by tech giant Meta at the state level, reveals about $150 million and counting that is flowing from AI interests into the midterms. View the full article

Governments are increasingly focused on how to govern artificial intelligence and secure digital systems, Quinn said, but noted that policymakers often lag technology. View the full article

The event was jointly organised by the University of Mumbai, the Centre of Excellence in Robotics & Automation Process under the School of Engineering & Applied Sciences, in collaboration with JANYU Technologies. View the full article

The US-based firm has partnered with top IT sector companies, such as TCS, Cognizant, LTIMindtree and Tech Mahindra, among others, and will look to have more such collaborations in the near future, according to a top company official. View the full article

The 86 signatories included the European Union as well the US and the UK, two key nations that had opted out of a global pact on AI at the previous year's summit in Paris. Other major participants include China, Germany, Japan, France, Italy, Russia and Canada. All the shared priorities mentioned in the declaration are voluntary and represent non-binding guidelines and principles. View the full article

The artificial intelligence revolution sweeping through the entertainment sector was at first glance not evident at this year's Berlin Film Festival, but the potential for widespread changes was still on people's minds. The tools have the potential to help the sector become more efficient and "save time at every stage of production", particularly in the more "bureaucratic" aspects of the process. View the full article

Indian AI startup Sarvam.AI has launched Indus, a new chat interface. This chatbot is built on Sarvam's own 105 billion sovereign model. Indus is positioned as a competitor to global AI giants like OpenAI's ChatGPT and Google's Gemini. The company is currently focused on accuracy and usefulness for the Indian context. View the full article

Indian-made robots captured attention at the AI Impact Summit in New Delhi. The SVAN-M2 robot dog from xTerra Robotics impressed attendees. A UNWFP robot designed for food warehouses also drew significant interest. These indigenous innovations showcased India's growing capabilities in artificial intelligence and robotics. The summit also saw a controversy regarding a university's misrepresentation of a foreign product. View the full article

India has released the AI Impact Summit Declaration, a voluntary global framework for AI cooperation inspired by "welfare for all." The declaration, endorsed by multiple nations, outlines seven pillars for collaboration, including human capital development, trustworthy AI, and democratising AI resources. View the full article

Silicon Valley touts AI as revolutionary, but public skepticism is high. Surveys show limited workplace impact, widespread fear, and strong support for regulation. View the full article

Indian entrepreneurs must run cos from own country to ensure innovation stays here, says founder Mensch. View the full article

Sarvam is already deploying its models in enterprise and government use cases, including voice AI and language technologies. Cofounder Pratyush Kumar said the company trained multiple models internally, without relying on any external technology stack. View the full article

Umakant Soni, cofounder of Bharat1.ai, said the idea of the park is to create AI models grounded in the real world and the park is equipped with robots, GPUs and researchers, which will create data for the real world. View the full article

OpenAI has more than 200 people ​working on a ​family of AI-powered devices that will ​include a smart speaker and possibly smart glasses and a smart lamp. View the full article

The study, published by essayhumaniser.io, evaluates over 100 countries using a weighted framework combining artificial intelligence (AI) R&D, economic integration, infrastructure, talent readiness, governance, responsible AI, public opinion and academic strength. View the full article

Cloudflare CEO Matthew Prince advocates for widespread AI access. He stresses AI should not be controlled by a select few companies. Prince calls for AI to benefit everyone, regardless of location or economic status. He highlights the need to support small businesses and preserve cultural diversity. Affordable and accessible AI for all is a key message. View the full article

Prime Minister Narendra Modi met with tech leaders Sam Altman of OpenAI and Cristiano Amon of Qualcomm. This occurred on the sidelines of the India AI Impact Summit in New Delhi. Altman praised India's AI progress and its focus on sovereign AI infrastructure. He noted the significant use of ChatGPT in India, especially by students. View the full article

Microsoft has launched a major initiative in India to train teachers in Artificial Intelligence. The program aims to skill twenty lakh teachers and reach two lakh schools by the year 2030. This effort will integrate AI literacy and computational thinking into the curriculum. India is the first Asian country to receive this program. View the full article

A UN panel on artificial intelligence will work towards "science-led governance", the global body's chief said on Friday as leaders at a New Delhi summit weighed their message on the future of the booming technology. - 'Science-led governance' - Guterres said the UN General Assembly had confirmed 40 members for a group called the Independent International Scientific Panel on Artificial Intelligence. View the full article

Prime Minister Narendra Modi engaged in a series of high-level meetings. He met with AI and deeptech startup leaders to explore artificial intelligence applications. The Prime Minister also held bilateral discussions with leaders from Sri Lanka, Slovakia, Liechtenstein, and Mauritius. Discussions focused on strengthening relationships and exploring cooperation in various sectors. View the full article

Q849As AI systems take on parts of analysis, pattern recognition, drafting, and even recommendation-making, the nature of human contribution changes. We may no longer hire primarily for raw processing speed or memorized knowledge — but for judgment, framing, and oversight. Think of a specific role in your domain where AI is now part of the workflow. How should hiring criteria evolve for that role? What qualities become more important — and which traditional requirements may become less critical? ⚠️ Any answer that is generic or does not connect with a specific role or process will not be approved. 💡 Participants are free to use AI tools while preparing their response — clarity of thinking and relevance will determine the best answer. 🏆 The best answer will be selected on the basis of: Relevance of the chosen role Depth of insight into capability shifts Practicality of revised hiring criteria Standard Note for Website VisitorsThis platform hosts two weekly questions — one on Monday and the other on Thursday. All previous questions can be found here: https://www.benchmarksixsigma.com/forum/lean-six-sigma-business-excellence-questions/ To participate in the current question, please visit the forum homepage at: https://www.benchmarksixsigma.com/forum/ The question will be open until Tuesday or Friday at 9:00 AM Indian Standard Time, depending on the launch day. Responses will not be visible until they are reviewed. Responses will not be visible until they are reviewed, and only non-plagiarised answers with less than 5-10% plagiarism will be considered for winner selection. If you are unsure about plagiarism, please verify your answer using a plagiarism checker tool such as https://smallseotools.com/plagiarism-checker/ before submitting. Participants are welcome to use AI tools while preparing their answers. However, selection of the winning response will depend on the quality of thinking, contextual relevance, clarity of reasoning, and practical insight demonstrated. All correct answers shall be published, and the top-rated answer will be displayed first. The author will receive an honourable mention in our Business Excellence dictionary at: https://www.benchmarksixsigma.com/forum/business-excellence-dictionary-glossary/ along with the related term.

🏆 WINNER (1)Taby Sheikh This is the most complete, realistic, and job-relevant answer — it clearly explains how performance shifts when AI enters a workflow, with strong examples of both upside and risk. The metrics redesign and training intervention sections are especially strong and demonstrate the highest maturity and depth. ✅ APPROVEDManish_Gupta_Tpgl This is a well-structured response that explains the before/after workflow and shows a credible learning curve, including risks like data quality and iterative refinement. It could be tightened for clarity, but it is relevant, practical, and publishable. Smitha Muralidharan This response is detailed, grounded in a real professional workflow, and clearly shows how AI changes the analyst’s role from creator to reviewer and quality owner. The risk section is especially strong because it highlights misinterpretation and hallucination in a way that feels realistic. Aloke Biswas This is a strong real-world example with a balanced view of AI as an accelerator for root-cause direction, not a replacement. It also demonstrates the key insight that AI fails when the system lacks updated context, which is an important learning point. Anil Kumar CAISA This is a high-quality response with strong domain relevance and a mature understanding of how AI changes work from “queue clearing” to investigative oversight. The performance metric redesign (“value of overrule”) and the adversarial training suggestion are excellent. Vijay Yivaturi This is a strong operational example with clear root cause breakdown and measurable impact (1232 hours annually), which adds credibility and business value. While it focuses more on process automation and dashboarding than on deeper shifts in judgment, metrics redesign, and skill evolution, it is practical, structured, and worthy of publication. Domz D Your example clearly shows how AI shifts effort from manual extraction to structured drafting support, and you correctly highlight the need for quality checks when OCR accuracy is imperfect. To strengthen this further, you could add a more concrete performance metric shift (for example, measurable reduction in rework or error rate) and a deeper risk scenario beyond conversion accuracy, such as subtle content distortion or over-standardization affecting report insight. ❌ REJECTED (Not strong enough / too generic)Harjeet This response is too high-level and lacks a specific workflow, measurable performance change, or realistic risk scenario. It reads more like a generic AI summary than an applied workplace answer. Dhruva KapurThis answer is currently not specific enough and does not clearly follow the structure the question asks for (workflow, improvement case, risk case, metrics, training). It needs more concrete examples and clearer linkage to performance outcomes. Himanshu_Lohani_WpY8This is too brief and does not provide enough depth to be useful to readers. It lacks specific examples, risks, and a meaningful discussion of performance metrics and training. Vijay GonsalvesThis answer does not sufficiently address the question in the required structured way and lacks detail on what AI changes in performance. It also does not provide a strong example of risk, metrics redesign, or training intervention. Preethi BijeshThe response has good intent but is too short and does not demonstrate a clear before/after workflow or performance shift. It needs more specificity and stronger examples to be publishable. Jinad_Padiyath _tPv5 This response does not contain enough detail to meet the standard for publication. It needs clearer structure, realistic examples, and a stronger treatment of risk and performance metrics.