Latest news with #AI-first
Time of India
a day ago
- Business
- Time of India
India's next AI wave to be driven by inclusive, monetisable solutions, say experts
Academy Empower your mind, elevate your skills India must focus on building scalable, inclusive, and monetisable AI applications tailored for the next billion users, experts said at a panel discussion as part of an event that brought together over 75 early-stage startups supported by IIM Calcutta Innovation Park , which incubates panel featured Prof Vimal Kumar M of IIM Calcutta, angel investor Deepak Daftari, and SuperProcure Co-founder Manisha Saraf, and was moderated by Gaurav Kapoor, Chief Business Officer of IIM Calcutta Innovation Park (IIMCIP).Speakers highlighted India's unique position to lead in AI innovation if startups focus on affordability, access, and meaningful application in sectors such as logistics, agriculture, education, and public in a statement, said startups from the region were exposed to hands-on training in Google's generative AI tools , including Gemini 2.5, Gemma 3.0, Vertex AI, and AI Studio, as part of a national initiative by Google for Startups Participants engaged with Google engineers, venture capitalists, and domain experts through product workshops, mentorship sessions, and investor connect opportunities, gaining practical insights on building AI-first ventures from the ground up, the IIMCIP statement added."Generative AI is not just a tech evolution - it's a shift in how solutions for India can be imagined. We want startups to build with impact and scalability in mind," said Enisha Kalita, Program Manager, Google for Sanyal, CEO of IIMCIP, said the collaboration aims to fuel innovation that supports sustainable development and livelihoods."By bringing these tools and networks to early-stage founders, we're enabling them to solve real-world problems through purposeful innovation," he added.
Forbes
3 days ago
- Business
- Forbes
Why Governance Is The New Security Perimeter For AI
Abhi Sharma , Founder and CEO at Relyance AI. As organizations increasingly deploy AI across their operations, many are unknowingly expanding their digital attack surface. Traditional security architectures, built around network boundaries, application endpoints and static access controls, weren't designed for today's AI-first environments. And as a result, there's a growing blind spot where sensitive data moves fast, decisions happen autonomously and accountability blurs. This hidden layer of exposure stems from the shadow AI problem: AI models, SaaS tools and agents that operate without clear governance or full visibility. These systems often touch sensitive data—personal, regulated or proprietary—but aren't consistently tracked, monitored or risk-assessed. The consequences can be severe: regulatory violations, data leakage, brand erosion and even systemic model failures. AI doesn't need to be malicious to be dangerous. Even well-intentioned use can create risk if the right controls aren't in place. Most critically, these systems evolve continuously, learning from new data, generating outputs and interacting with other models in ways that aren't always transparent. This creates a dynamic risk surface that legacy security tools struggle to address. To stay ahead, security leaders must rethink their role. The perimeter has shifted—it now begins at the level of data trust and model transparency. Governance is no longer a compliance afterthought. It's the new front line of defense. Three Immutable Laws For Securing AI Our approach to this front line of defense centers around three foundational truths, or what we call the "physics of data trust." They form the bedrock of modern AI governance and offer CISOs a new way to frame risk: 1. The Law Of Information Asymmetry Trust collapses when one party (whether internal or external) knows far more about how data is used than others. Your governance architecture must be built for discoverability, explainability and developer-friendly compliance. Architectures that obscure how data is processed or how decisions are made inherently increase operational exposure. AI systems don't just process data—they combine and reshape it. Seemingly harmless datasets, when merged or inferred upon, can reveal highly sensitive or regulated insights. Traditional static scanning tools aren't enough. Security must evolve to understand the systemic behavior of data across workflows, business logic and downstream decision making. 3. The Law Of Conservation Of Accountability You can delegate tasks, automate controls or outsource operations—but you can't outsource responsibility. Systems must produce traceable audit trails and verifiable lineage so that accountability is always recoverable, even in highly distributed AI ecosystems. These laws are practical design principles for organizations looking to scale AI securely. They serve as a foundation for both policy and architecture, helping CISOs identify blind spots before they become liabilities. From Reactive Security To Proactive AI Risk Mitigation Leading CISOs are beginning to shift from reactive post-incident analysis to continuous AI risk elimination. That means: • Identifying and eliminating shadow AI systems before they introduce exposure. • Simulating AI-specific breach scenarios tied to real business impact. • Tracking identity access to models, training data and outputs with precision. • Demonstrating board-level accountability for AI risk posture, not just regulatory readiness. Metrics are changing, too. Trust scores, model transparency indices and governance coverage are becoming KPIs alongside traditional threat detection metrics. Compliance As A Competitive Edge In highly regulated industries like healthcare and finance, the ability to prove compliance in real time is becoming a market differentiator. Regulators are increasing pressure, and enterprise customers are demanding stronger assurances around data handling, model behavior and ethical use. Organizations that embed governance directly into AI development pipelines can accelerate responsible AI adoption while minimizing regulatory exposure. That, in turn, creates real economic advantages from reduced insurance premiums to faster procurement cycles. More broadly, governance done well becomes a business enabler. When engineers and data scientists know that guardrails are in place, they can move faster and innovate more confidently. Governance doesn't have to slow development; it can actually de-risk velocity. Governance Is The New Perimeter AI doesn't defy the rules so much as it silently rewrites them. That's why the next wave of AI risk management won't be defined by firewalls or forensic tools but by intelligent, continuous governance frameworks that scale with innovation. Security and compliance are no longer separate silos. In an AI-first world, they're inseparable, and governance is the connective tissue. CISOs who embrace this shift won't just reduce risk. They'll build trust across customers, regulators and partners. And in a world increasingly shaped by autonomous systems, trust is the most valuable perimeter you can defend. Forbes Technology Council is an invitation-only community for world-class CIOs, CTOs and technology executives. Do I qualify?
Time of India
7 days ago
- Business
- Time of India
Google Cloud sets Guinness World Records title for 'Largest AI Agent Training Event'
Google Cloud India has officially entered the record books, securing a Guinness World Records title for hosting the largest Agentic AI hackathon during its landmark Agentic AI Day 2025 event. Held on July 27 in collaboration with Hack2Skill, the event brought together over 2,000 developers forming more than 700 AI-first teams for a high-energy, 30-hour innovation sprint. A total of 1,941 developers were adjudicated to break the world record, tackling six real-world problem statements ranging from urban data overload to personalized financial coaching . The winning teams built functional MVPs using Google Cloud's AI ecosystem, including Gemini 2.5 Pro, Vertex AI, AI Studio, and Firebase Studio. "We are incredibly proud to have been recognized by Guinness World Records for this achievement," a Google spokesperson said. "Agentic AI Day was more than just a training session; it was a testament to the future of AI. Our goal is to empower developers to build intelligent agents that can solve real-world problems, and this event proved that our platform is ready to support that vision at an unparalleled scale." With over 57,000 registrations and more than 1 million online impressions, the event not only broke records—it ignited a movement. Want to explore what Agentic AI means or how these tools can be used in your own projects? I'd be thrilled to walk you through it. by Taboola by Taboola Sponsored Links Sponsored Links Promoted Links Promoted Links You May Like Luxury Awaits at Paras Floret | Paras Sector 59 Gurgaon Paras The Florett Book Now Undo Highlights from the Hackathon * Arealis Agents: Built a platform to manage city data overload using real-time analytics and visualization tools. * GuruMitra: Created an offline-first AI platform for multi-grade classrooms, supporting 22+ Indian languages. * Blue Bird: Developed CrowdSense, a privacy-first crowd intelligence system for public event safety. * Kovai Shines: Introduced an AI Farming Companion for crop diagnosis and market insights. * Raah: Launched Raseed, an AI-powered receipt manager integrated with Google Wallet. * Built Artha, a personal finance coach that automates ITR filing and offers year-round guidance. AI Masterclass for Students. Upskill Young Ones Today!– Join Now
IOL News
29-07-2025
- Business
- IOL News
South Africa is not ready for the coming white-collar AI bloodbath
South Africa is not ready for the coming white-collar AI bloodbath, says the author. Image: AI LAB A major disruption is unfolding in global white-collar employment. According to Anthropic CEO Dario Amodei, up to 50% of entry-level white-collar jobs could vanish in the next five years due to advances in artificial intelligence. As detailed in Axios' article 'Behind the Curtain: A White-Collar Bloodbath', this isn't science fiction; it's a forecast from one of the leading minds in the AI field. South Africa, already battling youth unemployment and graduate underemployment, is ill-prepared for this transformation. According to StatsSA, South Africa's youth unemployment rate stood at 45.5% in quarter one 2024, and even university graduates struggle to find meaningful, skills-aligned work. Our economy continues to rely heavily on labour-intensive sectors like mining and retail while offering limited pathways into knowledge work. Now, with AI rapidly mastering entry-level professional tasks, such as document drafting, basic analysis, and customer interaction, the last buffer between graduates and long-term exclusion may collapse. This shift is not about robots in factories; it is about machines replacing tasks traditionally assigned to junior professionals. Legal clerks, marketing interns, junior auditors, and admin graduates' roles, meant to build workplace experience, are increasingly handled by AI systems that are faster, cheaper, and tireless. Employers may not downsize immediately, but they are already freezing hiring or redesigning roles to be 'AI-first.' Without access to these stepping-stone roles, South Africa's already marginalised youth may find themselves locked out of the formal economy altogether. The government, academia, and business sectors are largely unresponsive to this looming crisis. Government conversations remain stuck in Fourth Industrial Revolution (4IR) rhetoric, disconnected from the speed and nature of current technological shifts. We are no longer preparing for change; we are reacting too late to one that is already here. To date, responses have been piecemeal. The Department of Communications and Digital Technologies has produced documents like the National Data and Cloud Policy and launched an AI Institute with the CSIR and UJ. However, these efforts lack a coordinated AI-readiness strategy that connects automation with job protection, ethical deployment, and skills development. The 2020 Presidential Commission on the 4IR laid out strong recommendations, but implementation has stalled. Meanwhile, digital upskilling initiatives funded through the National Skills Fund or SETAs focus mostly on basic IT literacy and coding, not AI fluency or workplace adaptation. Universities and TVET colleges continue to produce graduates for roles vulnerable to automation. While some institutions offer data science or entrepreneurship programmes, the majority of curricula remain outdated. Employers, for their part, are adopting AI in operations, particularly in banking, consulting, and customer service, but without public commitments to ethical deployment, job transition planning, or internship preservation. Public discourse is also behind. Civil society and researchers have begun tackling data ethics and algorithmic bias, but little attention is paid to AI's role in reshaping the graduate labour market. As a result, policy and pedagogy remain misaligned with the rapid automation of professional tasks. Video Player is loading. Play Video Play Unmute Current Time 0:00 / Duration -:- Loaded : 0% Stream Type LIVE Seek to live, currently behind live LIVE Remaining Time - 0:00 This is a modal window. Beginning of dialog window. Escape will cancel and close the window. Text Color White Black Red Green Blue Yellow Magenta Cyan Transparency Opaque Semi-Transparent Background Color Black White Red Green Blue Yellow Magenta Cyan Transparency Opaque Semi-Transparent Transparent Window Color Black White Red Green Blue Yellow Magenta Cyan Transparency Transparent Semi-Transparent Opaque Font Size 50% 75% 100% 125% 150% 175% 200% 300% 400% Text Edge Style None Raised Depressed Uniform Dropshadow Font Family Proportional Sans-Serif Monospace Sans-Serif Proportional Serif Monospace Serif Casual Script Small Caps Reset restore all settings to the default values Done Close Modal Dialog End of dialog window. Advertisement Video Player is loading. Play Video Play Unmute Current Time 0:00 / Duration -:- Loaded : 0% Stream Type LIVE Seek to live, currently behind live LIVE Remaining Time - 0:00 This is a modal window. Beginning of dialog window. Escape will cancel and close the window. Text Color White Black Red Green Blue Yellow Magenta Cyan Transparency Opaque Semi-Transparent Background Color Black White Red Green Blue Yellow Magenta Cyan Transparency Opaque Semi-Transparent Transparent Window Color Black White Red Green Blue Yellow Magenta Cyan Transparency Transparent Semi-Transparent Opaque Font Size 50% 75% 100% 125% 150% 175% 200% 300% 400% Text Edge Style None Raised Depressed Uniform Dropshadow Font Family Proportional Sans-Serif Monospace Sans-Serif Proportional Serif Monospace Serif Casual Script Small Caps Reset restore all settings to the default values Done Close Modal Dialog End of dialog window. Next Stay Close ✕ South Africa urgently needs a coordinated national strategy for AI integration and labour resilience. This strategy must include: Regulation of AI deployment in sectors like finance, education, and HR. An AI usage tax or levy to fund reskilling, digital public employment schemes, or universal basic income pilots. Labour market forecasting that tracks which roles are most vulnerable and identifies growth sectors suited to human skills. The education sector must act now. From basic education through to postgraduate study, curricula must equip students with data literacy, AI ethics, systems thinking, and interdisciplinary problem-solving. All disciplines, not just STEM, must be AI-aware. Pedagogies must evolve from rote learning to adaptive, applied learning. Employers must also take responsibility. Ethical AI adoption should include commitments to preserving pathways for young professionals, supporting employee reskilling, and maintaining entry-level learning opportunities. Without these, automation will deepen inequality and economic exclusion. We must also be bolder in where we look for future jobs. Care work, social entrepreneurship, the digital creative economy, rural innovation, and climate adaptation all require skills that AI cannot easily replicate, such as human judgement, emotional nuance, and cultural intelligence. If supported with funding and training, these sectors could provide both dignity and economic inclusion. While structural change is vital, individuals, especially tertiary students, must act proactively. First, they must become AI literate, understanding how platforms like ChatGPT, Claude, and are transforming work. Many free or low-cost online courses are available. Second, students must strengthen human-centred skills such as ethical reasoning, creativity, communication, and teamwork, areas where machines still struggle. They should build real-world experience through volunteering, student leadership, and interdisciplinary collaboration. Third, graduates must build adaptable portfolios, showcasing skills through blogs, digital artefacts, or small projects. A certificate alone will no longer open doors. Finally, students should demand more from their institutions, AI-informed teaching, curriculum updates, and exposure to emerging tools and thinking. This moment demands courage and clarity. AI is not on the horizon; it is in the room. Without urgent, collaborative action across government, higher education, and business, South Africa risks cementing a two-tier society: those who build and manage the machines, and those left behind. If we act wisely, we can still shape a future where human talent and machine capability work together to create inclusive, ethical prosperity. Dr Zamandlovu Sizile Makola is a senior lecturer in the College of Economic and Management Sciences (CEMS) at Unisa. *** The views expressed here do not necessarily represent those of Independent Media or IOL. BUSINESS REPORT
News18
28-07-2025
- Business
- News18
TCS Enters The Tech Layoff Wave With Microsoft, Intel – AI Or Attrition To Blame?
Last Updated: The global tech industry is undergoing a massive shake-up. In just the first half of 2025, over 94,000 tech workers have lost their jobs Tech Job Cuts 2025: The global tech industry is undergoing a massive shake-up. In just the first half of 2025, over 94,000 tech workers worldwide have lost their jobs, averaging about 507 roles eliminated per day, according to multiple reports. From Microsoft and Intel to Meta and TCS, companies are announcing large-scale layoffs as they adapt to an AI-first, leaner future. AI: The Convenient Culprit? Artificial intelligence is at the center of this narrative. Executives such as Amazon CEO Andy Jassy have acknowledged that AI efficiencies will inevitably lead to a leaner workforce. Others, however, push back on the notion that AI alone is driving job cuts. For instance, TCS CEO K Krithivasan recently told Moneycontrol that the company's plan to cut 12,000 jobs — about 2% of its global headcount — is not because of AI productivity gains. Instead, he attributed the move to skill mismatches and limited deployment feasibility, especially among middle and senior-level employees. 'This is not because of AI giving some 20 percent productivity gains. We are not doing that," Krithivasan said, adding that the layoffs were part of a broader transformation to make TCS a 'future-ready organisation." Despite upskilling over 550,000 employees in AI and emerging tech, not all staff could transition effectively into TCS's evolving operating model. Many were trained in legacy systems and found it difficult to align with product-led, agile structures. Even as Microsoft hit record highs in the stock market, it has laid off over 15,000 employees so far this year. The cuts were primarily focused on non-technical roles like sales and regional support. CEO Satya Nadella, in a memo cited by The Economic Times, explained that the company must 'align with long-term strategic goals" centered around AI, cloud, and enterprise tools. Microsoft is reportedly encouraging all employees to integrate Copilot AI tools into daily workflows and is revamping performance metrics to include AI usage. Traditional sales roles are being replaced with 'solution engineers", trained in technical demos and AI implementation. Intel: Up to 24,000 Jobs Slashed Intel is also reducing its workforce drastically — cutting up to 24,000 jobs or nearly 25% of its global staff. New CEO Lip-Bu Tan admitted on an earnings call that the company had overestimated demand and that automation had become necessary to boost efficiency. Intel is also halting new projects in Germany and Poland and relocating operations from Costa Rica to Vietnam, impacting an additional 2,000 roles. While many firms are vague about AI's role in workforce reductions, a few are more transparent. IBM revealed that 200 HR jobs were replaced by AI tools, while Klarna CEO Sebastian Siemiatkowski told CNBC that the company shrank from 5,000 to 3,000 employees after adopting AI systems. Meta also reduced its workforce by 5% earlier in 2025, citing increased automation as a key driver. The company's Reality Labs division, which works on AR/VR technologies, was among the most impacted. Meanwhile, Panasonic announced 10,000 global layoffs, attributing the decision to a strategic shift toward AI-powered product development. Some analysts argue that AI is being used as a convenient scapegoat for broader cost-cutting and restructuring strategies. Jason Leverant, President of AtWork Group told CNBC, 'Firms laying off as they adopt large-scale AI is too coincidental to ignore." Christine Inge, a workforce strategist at Harvard, added, 'Being direct about AI displacement provokes backlash from employees and regulators. Remaining vague helps control optics during transition." She noted that while AI is accelerating the shift, economic slowdown, changing client expectations, and skills gaps are just as responsible. 'Job losses will be extremely large. The only thing we can do as individuals is adapt," Inge told CNBC. Not Just AI – But AI Is a Catalyst Whether it's TCS, Microsoft, or Intel, the layoffs of 2025 are clearly part of a deeper transformation. AI is undeniably a catalyst — streamlining operations, reducing redundancy, and reshaping business models — but it's not the sole cause. Instead, a mix of automation, cost pressures, macro uncertainty, and the need for organizational agility is driving the global wave of tech layoffs. Location : New Delhi, India, India First Published: July 28, 2025, 12:09 IST Disclaimer: Comments reflect users' views, not News18's. Please keep discussions respectful and constructive. Abusive, defamatory, or illegal comments will be removed. News18 may disable any comment at its discretion. By posting, you agree to our Terms of Use and Privacy Policy.
