Latest news with #MaryMeeker
NZ Herald
13-07-2025
- Business
- NZ Herald
Mary Meeker returns with AI-focused Internet Trends report
Mary Meeker has released her first Internet Trends report since 2019, focused entirely on artificial intelligence. Photo / Getty Images THE FACTS After a six-year hiatus, venture capitalist and former Wall Street analyst Mary Meeker has released her first Internet Trends report since 2019. It's 340 pages long, and focused entirely on artificial intelligence (AI). Dubbed the 'Queen of the Internet' by Barron's magazine, Meeker is known for her ability
Time of India
26-06-2025
- Business
- Time of India
GenAI adoption in India: Bridging the gap between promise and proficiency
Developers now save about 30% in manual effort by auto-generating boilerplate code using GenAI. An Indian e-commerce company recently reduced costs by 75% by utilizing a GenAI-powered voice bot for customer support. It's more than a tech trick; it's a micro-revolution. India now claims 13.5% of global ChatGPT usage, beating the US, according to the recent Mary Meeker's AI Trends Report, It is quite evident that Generative AI has arrived, and with it, a wave of change that has the potential to redefine the way we work, learn, heal, and innovate. The Indian government recently announced its plan to invest INR 10,000 Crore on the AI mission to build computing infrastructure (with recent compute capacity exceeding 34,000 GPUs), promote start-ups, train an AI-ready workforce, and develop ethical AI. However, as India advances with vernacular GenAI innovation, the gap between promise and proficiency has never been more pronounced. This is not merely a technology problem; it's a human one. The promise: Not just hype, but tangible potential India has more than 5 million tech workers, a vibrant startup ecosystem, and digital-first policies accelerating GenAI adoption across industries. According to a report by EY , GenAI is estimated to impact 38 million jobs in India by 2030, boosting productivity by 2.61% across the organized sector and 2.82% in the unorganized sector. The report also points out that by the coming year, 24% of tasks across industries can be fully automated, freeing up to 8–10 work hours weekly per employee. In healthcare, AI-powered assistants are enabling faster diagnoses and personalized treatment plans. In financial services, GenAI is improving fraud detection rates and automating compliance processes. The Indian IT-BPM sector is poised for a 45% productivity gain, with software development expected to see a 60% increase, and BPO and consulting experiencing 52% and 47% growth, respectively. Even tier-2 startups are leveraging GenAI to design pitch decks, write product descriptions, and localize marketing, without hiring large teams. These GenAI applications aren't hypothetical; they're today's reality. The advantages are real, including better accuracy, quicker service, improved personalization, and, ultimately, greater accessibility. The promise has moved decisively beyond hype into real-world value. The proficiency gap Despite all the hype and exciting GenAI adoption across India, very few Indian businesses have implemented GenAI at scale. A substantial proficiency gap is holding many organizations back from achieving real, scalable impact. Why? Talent shortages The talent required to deploy GenAI is niche and limited. Every year, millions of engineers graduate in India, but only a few are educated in prompt engineering, model tuning, or AI ethics. The consequence? Most companies desire to take up GenAI but do not have the human resources to build or maintain it. Integration overload Most companies weren't designed or built with AI in mind. Siloed data, legacy systems, and old workflows make it difficult to install GenAI without deep transformations. And unlike previous IT upgrades, GenAI requires both technical adaptability and cultural preparedness. Data privacy & risk GenAI lives and thrives on data. Yet in a nation where data sovereignty, consent, and responsible AI practices are still taking shape, companies naturally are hesitant, particularly in industries working with health, finance, or identity data. Outdated IT systems in organizations further hamper progress. Human hesitation A less talked-about but very present problem is the uncertainty of AI. The lack of measurable ROI, clear objectives, and assessable impacts feeds into the anxiety of the managers, creating resistance based on uncertainty, and hinders adoption more than any technical challenge. What will Bridge the Gap? To shift from hype to habit, GenAI in India requires more than pilot projects and flashy demos. It requires conscious investment in capability, confidence, and culture. Skill-based training Upskilling cannot be a one-time workshop. Developers require hands-on, problem-specific training, using real tools, not just in theory. In one study, organizations that trained workers in GenAI over 5+ modules achieved triple adoption. Training isn't a nice-to-have; it's the path between fear and fluency. Recently, Snowflake partnered with the state-backed FutureSkills Prime initiative to train over 100,000 students on AI & Data, clearly showing how the government and private sector are together pushing the peddles on upskilling. Measuring what matters It's easy to get caught up in what the model can do. But the real question is- Does it save time? Does it reduce errors? Does it help people do better work?. To overcome this, we need to track what matters. The focus must shift from 'What can GenAI do?' to 'What did GenAI do?'. Leaders should start tracking GenAI impact via dashboards on time saved, error reduction, cost saving, and quality uplift. This visibility builds confidence and helps secure long-term ROI. Centers of excellence Building specialized spaces like GenAI Labs or a Centre of Excellence where teams synthesize learnings, iterate models, and showcase proofs of concept. It de-risks innovation and speeds bottom-up GenAI adoption. Psychological safety The fear that "AI will replace me" is legitimate. Rather than ignoring it, organizations must address it. Conversations around data use, ethics, and responsible AI use foster trust and transparency in communication, open roadmaps. Participative planning goes a long way. There have been some emerging success stories budding in the market, as some Indian organizations are showcasing what is possible: Health industry platforms are employing GenAI to respond to patient queries in local languages, reducing call center education businesses are offering personalized content based on student behavior and performance data, driven by GenAI summarization and generation and individual entrepreneurs are applying GenAI tools to develop pitch decks, contracts, ad copy, and even Instagram copy without needing to engage with agencies. The way forward: An Indian model for GenAI India does not need to follow the way GenAI is being taken up in Silicon Valley or Shanghai. We have our own set of challenges—22 official languages, bandwidth limitations, informal economies—but our own set of strengths too: a problem-solving culture, fast digital penetration, and an ever-curious, inquiring workforce. The challenge is not merely to deploy GenAI. It's to define it, create Indian-context models, open datasets in vernacular languages, and develop innovative and inclusive governance models. We can achieve this, but it will take: Public-private cooperation on AI literacy and GenAI creation, rather than mere API inclusion of small businesses and non-tech guardrails that reflect Indian values concerning data and fairness. GenAI won't change India overnight, but over the next decade, it can potentially revolutionize the way we learn, serve, build, and grow. To unlock this potential, we need more than rollout plans; it takes a human-focused strategy based on training, transparency, trial and error, and trust. At its best, GenAI does not merely create content or code; it creates confidence; the certainty that by adapting the right GenAI strategies, individuals can do more, reach farther, and solve problems previously thought to be unsolvable. That is its greatest promise.
Associated Press
26-06-2025
- Business
- Associated Press
Lighthouse Unveils Connect AI: Bridging the Divide Between Hotels and AI-Powered Travel Planning
New AI engine enables hotels to be discovered, understood, and booked by AI agents as travel planning shifts to AI-powered platforms DENVER, COLORADO / ACCESS Newswire / June 26, 2025 / Lighthouse, the leading commercial platform for the travel and hospitality industry, today announced the launch of Connect AI, an innovative AI engine designed to seamlessly enable deeper connection between hotels and AI powered search and travel planning platforms. Connect AI addresses two critical industry challenges: AI agents lack the ability to access structured rate, availability, and contextual hotel information; while hotels lack the ability to enable direct booking capabilities and provide real-time information through AI platforms. Consumer adoption of AI has grown faster than any disruptive technology in history, as Mary Meeker recently highlighted with ChatGPT reaching 100M users in less than three months. Yet, despite the rapid adoption of AI for travel planning, hotels are significantly underrepresented in AI-driven search results. According to a recent report by Skift, not a single hotel brand currently appears among the top 10 citations for travel planners in leading AI Overview search results. This lack of discoverability and accessible information presents a significant missed opportunity for hotels to drive direct bookings with a new generation of travelers. Hoteliers face enormous opportunity risk without an AI data and connectivity strategy. Connect AI solves this by creating a comprehensive data bridge between the hospitality industry and the rapidly expanding ecosystem of AI travel planning platforms. 'We're seeing travelers increasingly turn to AI tools for trip planning, and our data shows this shift is accelerating faster than anyone anticipated,' said Juanjo Rodriguez, Head of Marketing & Direct Growth Products at Lighthouse. 'According to Phocuswright research, 50% of travelers plan to use generative AI for leisure travel within the next 12 months. Hotels that connect with AI platforms now will be positioned to capture more value, while those that wait risk missing this transition entirely. Connect AI helps hoteliers get ahead of this curve.' The primary benefits of Connect AI include: Lighthouse is uniquely positioned to address these industry challenges due to its unparalleled scale, data accuracy, and extensive integrations: 'Connect AI represents a new approach to marketing and distribution strategy,' said Sergio Zertuche, Chief Sales & Marketing Officer at Palladium Hotel Group, a pioneering company in the adoption of this technology. 'We see this as an exciting opportunity to connect with travelers in new ways. With the speed of AI adoption, we want to ensure our properties are discoverable and bookable when guests search through these new channels.' Connect AI is now available to select hotel partners as part of an early access program. Hotels interested in exploring connection opportunities are encouraged to visit: to learn more. Contact InformationAdam Swart Global Head of Brand 917-359-8969 SOURCE: Lighthouse Ltd press release
Time of India
18-06-2025
- Business
- Time of India
Eating into SEO budgets, GEO is pushing CTRs to obsolescence
AI-driven search may currently account for just 3% of total search traffic, according to BCG (Boston Consulting Group) data, but its growth trajectory can not be ignored. In India, it's already eating into traditional SEO ( Search Engine Optimisation ) budgets and making long-standing metrics like CTR ( Click Through Rate ) increasingly obsolete. The shift is not just theoretical. Semrush predicts that AI-driven channels could rival traditional search in economic impact by 2027, with AI-powered visits converting at 4.4 times the rate of organic search. Marketers can't simply ignore these figures, as the implications for marketers are profound and demand immediate attention. Adding to the urgency is the fact that India now leads the world in ChatGPT usage, accounting for 13.5% of its global user base, according to Mary Meeker's 'Trends – Artificial Intelligence ' report. According to Parul Bajaj, India leader, marketing, sales & pricing, BCG (Boston Consulting Group), 'Over the past year, visits to top 10 AI chatbots have nearly doubled, from around 30 billion in April 2024 to approximately 55–60 billion by March-April 2025. In our view, this is not a short-term change. It represents a fundamentally new discovery model where AI plays a central role in how consumers find, evaluate, and engage with information.' These developments raise important questions for brands operating in India: How are marketers in India responding to 'conversational commerce'? Are they rethinking their strategies, reallocating budgets, and optimising content for AI-driven discovery? Let's hear directly from the marketers and take a closer look at the AI search ecosystem, unpacking one layer at a time. Status check on GEO SEO (Search Engine Optimisation) was built for a world of clickable links and ranked results. It relies on keywords, backlinks and metadata (information describing the data) to push content to the top, but brands can no longer rely on keyword stuffing or legacy optimisation tricks to gain visibility in AI search. To stay relevant, they must optimise content for how AI models read, interpret and surface information. This optimisation is referred to as GEO ( Generative Engine Optimisation ). 'Our research shows that tactics like keyword density, backlinks, and metadata that were important in SEO do not guarantee visibility in AI results. Some of the most-cited pages in AI answers often have fewer keywords and backlinks than top-ranking SEO pages,' Bajaj noted. AI engines typically prioritise content that is conversational, easy to extract, and clearly presented. Brands need to create content that is well-structured, neatly formatted, and includes numerical facts and credible expert quotes. But, the question remains: where do Indian brands stand when it comes to optimising content for AI-led search? 'We have begun structuring our content for AI visibility, whether through schema-rich explainers (content with structured data, making it more understandable for AI engines), FAQs, or simplified jargon-to-journey formats (simplifying industry jargon into clear content guiding consumer decisions). We are seeing a shift from traditional blogs to content that answers rather than just ranks,' said Sandeep Walunj, executive director and group CMO, Motilal Oswal Financial Services (MOFS). For the BFSI (Banking, Financial Services and Insurance) sector, Walunj believes that future content strategies will focus on creating content that earns trust and citations within AI ecosystems. Highlighting the shift from traditional to AI-driven search in BFSI, Arvind Iyer, marketing head, Piramal Finance, said, 'We're already experiencing the shift where our visibility in AI-generated answers is outpacing our traditional SEO rankings for certain keywords. We are seeing that a significant number of our target keywords that don't rank in the top 50 on Google are already being surfaced by AI platforms in their generative responses. This includes important terms in lending, personal finance, and credit awareness.' It's now evident that AI-driven search isn't just a buzzword; it's a reality for categories like BFSI brands in India. Yet, the question is: is this trend significant enough for marketers to start reallocating budgets for GEO? Investments in GEO While AI-driven search is gaining momentum, it still accounts for just 3% of total search traffic, according to BCG. As a result, most brands in India are not yet making sizable standalone investments in GEO. Instead, they are reallocating a small fraction of their existing digital content budgets to explore this emerging space. Iyer noted that Piramal Finance has begun dedicating 5-8% of its digital content and SEO budget specifically toward AI search optimisation , which includes reformatting content for AI summarisation, tracking how the brand appears in generative answers, and testing what influences being referenced by AI engines. 'In a world of zero-click search, you either get summarised or sidelined. While we have not seen a significant uplift in branded search volumes yet, we believe this is a space worth investing in,' Iyer noted. Speaking of budgets, Boult (a D2C brand known for its audio products and smartwatches) is allocating 3-5% of its content budget on AI search-related initiatives and anticipates this allocation to grow in the next two quarters. Varun Gupta, co-founder, Boult, mentioned that early adopters of GEO practices have seen up to a 20% increase in snippet visibility. Moreover, Walunj noted that while investing in GEO is a priority, the current budget allocation remains in the single-digit percentage range. However, early indicators such as increased citations in AI summaries, reduced bounce rates on educational pages, and higher conversions from AI-generated leads are already encouraging. 'In broking and AMC (Asset Management Company), where the journey is high-stakes and trust-led, appearing in authoritative AI responses is an edge,' Walunj resolved. Resonating with the above-mentioned marketers, Bajaj also emphasised that most aren't carving out separate budgets for AI search optimisation. Instead, they're reallocating a portion of their existing SEO content spend towards GEO efforts. 'At this stage, no major brand in India has fully cracked the code or committed to large-scale investment in AI-driven search,' Bajaj quoted. A different game While BFSI brands are actively exploring GEO, other categories remain hesitant, waiting to see how AI search evolves. The hesitation largely stems from the challenges AI-driven search presents, but what exactly are they? Varadharajan Ragunathan, head of ad tech and retail media, TCS (Tata Consultancy Services), pointed out that one of the biggest challenges in embracing GEO is the lack of clarity around how advertising will function on AI engines. 'GEO operates very differently from SEO. Think of it like a roll call in school. Earlier, the teacher would call out a name, but now, it's more like, who's fanatical about cricket and has Virat Kohli's autograph? If that's you, you're called upon. It's an entirely new, contextual way of being recognised. That's not how our brains have traditionally processed search. So the question becomes: how do I change my name, or in this case, my content, so that AI recognises and references me?,' said Ragunathan. Another key challenge, according to Ragunathan, is the need for dual strategies: one for conventional search and another for AI-friendly content. He likens this approach to being a car manufacturer who must now build both electric and conventional vehicles and excel in both. Calling out another challenge, Ragunathan shared that brands now face the challenge of optimising their content for multiple AI search engines, without knowing which one will ultimately dominate. Unlike the past, when Google was the clear winner, the AI search landscape is fragmented and evolving rapidly. 'It's like not knowing whether I'm playing cricket, football, or tennis, yet, I need to impress my cricket coach in the morning, my tennis coach in the evening and my football coach at night,' noted Ragunathan. Ragunathan's words raise an important question: do brands need to create separate content optimised for both SEO and GEO? Addressing this challenge, Bajaj said, 'SEO and GEO are not in conflict with each other. It's not an 'either-or' scenario; it's an 'and'. Both strategies can and should coexist. In my view, GEO isn't replacing SEO, it's augmenting it. And despite the tactical differences, both strategies share a common core: delivering value through intent-driven, user-centric content. GEO extends SEO's reach into zero-click (searches that end without the customer clicking on a web page), AI-powered environments, enhancing discoverability and relevance where search results are increasingly synthesized rather than linked.' This brings us to the next dilemma many marketers face: which AI search engine should they prioritise when optimising their content? As Gupta puts it, 'It is tough to optimise one piece of content across every AI search platform plus traditional SEO. These models interpret information differently, and our biggest challenge so far is identifying how to make our content simultaneously 'citable' for LLMs and 'rankable' for Google, without fragmenting our team's bandwidth.' Bajaj offers a clear approach. She said, 'There's a growing list of AI chatbots in the market today, but when we look closely, we begin to see clear differences in their user profiles. The right strategy begins with identifying on which AI platform your customer base is over-indexed on.' Elaborating her stance with an example, she said, 'ChatGPT, for instance, commands the largest and most diverse user base globally. It's widely used across age groups and demographics, making it the most popular in education and workplace contexts. On the other hand, Claude tends to skew more male and shows a higher concentration of users in the United States. Meanwhile, Google's Gemini leans towards a younger demographic. These nuances are essential for brands crafting their GEO strategies as each platform brings its own audience.' Measuring the impact In the past, one of the main measures of SEO success was CTR (Click Through Rate), which measures the number of people who click on a link or an ad. But now, with a growing number of searches, around 60% (BCG data), ending without any clicks, CTRs will increasingly become less relevant. This raises the challenge of how brands will measure the effectiveness of their GEO strategy . 'Unlike SEO, where we have ranking reports, AI search lacks direct feedback loops. It's unclear why certain sources are preferred or ignored. Moreover, it is difficult to quantify the exact impact of being mentioned in an AI answer since there's often no click-through or attribution. Therefore, we are correlating AI visibility timelines with branded search spikes, time-on-site improvements, and conversion lifts - helping us infer the ROI of being AI-visible,' Iyer revealed. Drawing attention to the challenge posed by the evolving nature of AI, Bajaj said, 'What works today in AI search may not work a month from now. The pace of change is rapid, with platforms constantly evolving and new versions of chatbots being released regularly. This makes it difficult for marketers to rely on fixed playbooks or long-standing best practices.' The rise of social listening In the world of SEO, the formula was relatively straightforward: create quality content, ensure it ranks at the top when customers search for your brand, and move on. But the AI search landscape is changing that dynamic. Since AI engines generate contextual answers by citing third-party sources, brands must now also be concerned with how they are portrayed across the broader internet, not just on their own platforms. This shift means marketers will need to go beyond owned content and actively monitor how their brand is represented in external sources. It calls for continuous engagement with publishers, online communities, and customers. As Bajaj points out, this will drive a greater focus on social listening, with brands enhancing their capabilities to shape and manage their narrative in an AI-driven environment. Naturally, this also signals a growing demand for social listening and online reputation management tools. Tackling AI biases Imagine you're using a voice assistant like Alexa or Siri and you say, 'Call me a cab.' That sentence sounds simple. But behind the scenes, the assistant has to understand what you mean, turn that into a command, find an app that can do it, and then book the ride. Now, let's say a cab company gives Alexa a special set of instructions to help it complete that task. It seems helpful, free code, easy connection and a smooth experience. But here's the catch: those instructions are written in a way that makes Alexa more likely to pick that one company. It doesn't block other ride-hailing apps, but it quietly gives one an advantage. Things like default settings or backup options are all tilted in its favour. Referring to this challenge, Ragunathan said, 'If another cab company wants to show up with the same voice command, they will have to build their own integrations and try to compete against a deeply embedded default algorithm. Eventually, saying 'Call a cab' might always bring up that one company, not because it is the only option, but because the system was quietly built to prefer it. That's how bias can sneak into technology that looks fair on the outside.' AI tools overlook branded content Shedding light on the challenges faced by BFSI brands, Walunj mentioned that BFSI content is typically too jargon-heavy, leading AI tools to skip it. Compounding the issue is the lack of transparency in tracking how and where content appears in AI search results. Additionally, much of the legacy content is not easily understood by large language models like ChatGPT. 'We're solving this by rewriting core education and product pages in LLM-friendly formats, auditing brand presence in AI platforms and building reporting frameworks, and training internal teams to think 'answer-first', not 'SEO-first',' Walunj noted. The challenge of consistency Like humans, AI is also prone to errors and can sometimes hallucinate, generating information that is inaccurate or off-brand. For marketers, ensuring consistency across various AI search engines remains a significant challenge, particularly as content is interpreted and presented differently by each platform. Shifting attention to this challenge, Rajat Abbi, VP - marketing, Schneider Electric, Greater India, said, 'The primary issues include data availability, hyperpersonalisation, and LLM-specific concerns such as hallucination. Delivering contextually relevant content at scale while maintaining consistency is a complex task. Additionally, LLMs pose risks like hallucination, where AI-generated responses may misrepresent facts or dilute brand messaging.' While challenges remain in optimising content for AI-driven search, sectors like BFSI are leading the way through continuous experimentation, setting an example for other industries. The lack of clear feedback loops, combined with the fast-evolving nature of AI platforms, has led many brands to adopt a cautious, wait-and-watch approach. However, AI-driven search is rapidly gaining ground and poised to disrupt traditional SEO practices. With growing optimism around its potential, especially among digitally savvy consumers, brands, particularly consumer-focused D2C players, must begin preparing for this shift now to stay ahead of the curve.
Yahoo
17-06-2025
- Automotive
- Yahoo
Applied Intuition raises $600 million as it pushes further into defense
Buzzy autonomous vehicle software company Applied Intuition has closed a $600 million Series F funding round, pushing its valuation up to $15 billion. The round was co-led by BlackRock-managed funds and Kleiner Perkins, and included new investments from the Qatar Investment Authority, Abu Dhabi Investment Council, Greycroft, and more. Existing investors General Catalyst, Lux, Elad Gil, and Mary Meeker's growth fund Bond also participated. Applied Intuition's raise comes just one year after it completed a $250 million Series E, which put the company at a $6 billion valuation. The company makes software that helps companies and government agencies develop autonomous vehicle solutions. That includes simulation software and managing data. 'When they think like, 'I have this software or AI problem,' we generally want them to think about us,' CEO Qasar Younis told TechCrunch last year. 'Like we want to be that first call.' Applied Intuition works with most of the major automakers, as well as autonomous vehicle companies such as Gatik and Kodiak. The company has also increasingly pushed into the defense space. In its newsletter announcing the funding round, Applied Intuition shared that it was asked by the U.S. Army to help bring autonomous tech to some of their vehicles. The company was able to take an infantry squad vehicle from 'bare-bones' to autonomous in just 10 days. This included developing a 'pedal-pushing robot to physically turn the wheel and press the throttle and brake pads.' Error in retrieving data Sign in to access your portfolio Error in retrieving data Error in retrieving data Error in retrieving data Error in retrieving data
