Understanding Technological Evolution

AI is becoming a make-or-break factor for banks. But success will not depend on their ability to offer #AI, but on their competence in integrating it. Let’s take a look.   Banking is forecasted to feel the biggest impact from generative AI among sectors and industries as a percentage of their revenues with the additional value calculated between $200 bn and $340 bn annually (source: McKinsey). But why is the impact so powerful? One of the main reasons is because the abrupt surge of gen AI is exponentially increasing the speed with which #banking is being transformed. That is not to say that the transformation has started with or due to AI. On the contrary: during the past 10 to 15 years banking was already in the middle of transforming from a human-based, relationship-first industry to a more automated and technology-driven business following the #fintech revolution and the ascend of nimbler and more innovative competitors. But AI now does 2 things: —  It brings the transition to a new level, across 3 dimensions: speed, outcome and impact. —  It turbo-charges one of the biggest challenges in modern FS: the combination of AI and data that brings under the same roof two inherently opposing forces: mass and customization. In other words, AI seems to find a credible answer to achieving hyper-personalization. In a recent report Deloitte has provided realistic examples on how this is done across both cost efficiency and income growth: Cost efficiency: —  Workforce acceleration efficiencies across the board: 0–15% of total staff cost —  IT development and maintenance acceleration: 10–20% of IT staff cost —  Improved credit-risk assessment leading to 10-15% savings in impairment charges —  Improved FinCrime/fraud detection reducing litigation/redress charges and fraud losses Income growth: —  Next generation market analysis / predictive trading algorithms: 5–7% uplift on trading income —  Improved customer retention: 1–2% uplift on fees & commissions —  Improved customer acquisition through hyper-personalised marketing: 5-10% uplift from interest income and fees & commissions —  Tailored loan pricing based on credit risk assessment: 2–3% increase on net interest income Despite all the excitement around these estimated benefits, success will not be a walk in the park. It will depend on the banks’ ability to integrate AI in a seamless way into their day-to-day operations. Going forward AI will be re-writing much of the scenarios and use cases of the banking value chain. That doesn’t necessarily mean that they will all be different, but most will certainly be enhanced with impact spanning both across the back-end and the front-end. Given that resources are limited, one of the main challenges will be how to identify the ones to focus on. Factors such as #strategy, potential impact and a match with the existing skillset should be guiding the selection process.   Opinions: my own, Graphic source and use cases: Deloitte

AI is rapidly moving from passive text generators to active decision-makers. To understand where things are headed, it’s important to trace the stages of this evolution. 1. 𝗟𝗟𝗠𝘀: 𝗧𝗵𝗲 𝗘𝗿𝗮 𝗼𝗳 𝗟𝗮𝗻𝗴𝘂𝗮𝗴𝗲 𝗙𝗹𝘂𝗲𝗻𝗰𝘆 Large Language Models (LLMs) like GPT-3 and GPT-4 excel at generating human-like text by predicting the next word in a sequence. They can produce coherent and contextually appropriate responses—but their capabilities end there. They don’t retain memory, they don’t take actions, and they don’t understand goals. They are reactive, not proactive. 2. 𝗥𝗔𝗚: 𝗧𝗵𝗲 𝗔𝗴𝗲 𝗼𝗳 𝗖𝗼𝗻𝘁𝗲𝘅𝘁-𝗔𝘄𝗮𝗿𝗲 𝗚𝗲𝗻𝗲𝗿𝗮𝘁𝗶𝗼𝗻 Retrieval-Augmented Generation (RAG) brought a major upgrade by integrating LLMs with external knowledge sources like vector databases or document stores. Now the model could retrieve relevant context and generate more accurate and personalized responses based on that information. This stage introduced the idea of 𝗱𝘆𝗻𝗮𝗺𝗶𝗰 𝗸𝗻𝗼𝘄𝗹𝗲𝗱𝗴𝗲 𝗮𝗰𝗰𝗲𝘀𝘀, but still required orchestration. The system didn’t plan or act—it responded with more relevance. 3. 𝗔𝗴𝗲𝗻𝘁𝗶𝗰 𝗔𝗜: 𝗧𝗼𝘄𝗮𝗿𝗱 𝗔𝘂𝘁𝗼𝗻𝗼𝗺𝗼𝘂𝘀 𝗜𝗻𝘁𝗲𝗹𝗹𝗶𝗴𝗲𝗻𝗰𝗲 Agentic AI is a fundamentally different paradigm. Here, systems are built to perceive, reason, and act toward goals—often without constant human prompting. An Agentic system includes: • 𝗠𝗲𝗺𝗼𝗿𝘆: to retain and recall information over time. • 𝗣𝗹𝗮𝗻𝗻𝗶𝗻𝗴: to decide what actions to take and in what order. • 𝗧𝗼𝗼𝗹 𝗨𝘀𝗲: to interact with APIs, databases, code, or software systems. • 𝗔𝘂𝘁𝗼𝗻𝗼𝗺𝘆: to loop through perception, decision, and action—iteratively improving performance.    Instead of a single model generating content, we now orchestrate 𝗺𝘂𝗹𝘁𝗶𝗽𝗹𝗲 𝗮𝗴𝗲𝗻𝘁𝘀, each responsible for specific tasks, coordinated by a central controller or planner. This is the architecture behind emerging use cases like autonomous coding assistants, intelligent workflow bots, and AI co-pilots that can operate entire systems. 𝗧𝗵𝗲 𝗦𝗵𝗶𝗳𝘁 𝗶𝗻 𝗧𝗵𝗶𝗻𝗸𝗶𝗻𝗴 We’re no longer designing prompts. We’re designing 𝗺𝗼𝗱𝘂𝗹𝗮𝗿, 𝗴𝗼𝗮𝗹-𝗱𝗿𝗶𝘃𝗲𝗻 𝘀𝘆𝘀𝘁𝗲𝗺𝘀 capable of interacting with the real world. This evolution—LLM → RAG → Agentic AI—marks the transition from 𝗹𝗮𝗻𝗴𝘂𝗮𝗴𝗲 𝘂𝗻𝗱𝗲𝗿𝘀𝘁𝗮𝗻𝗱𝗶𝗻𝗴 to 𝗴𝗼𝗮𝗹-𝗱𝗿𝗶𝘃𝗲𝗻 𝗶𝗻𝘁𝗲𝗹𝗹𝗶𝗴𝗲𝗻𝗰𝗲.

Looking backwards to predict the future is misleading. New technologies scale far faster than their predecessors. Solar took just eight years to grow from 100 TWh to 1,000 TWh—and only three more years to double again, surpassing 2,000 TWh in 2024. For each of the past three years, solar has been the largest source of new electricity worldwide. Nothing else in power generation has scaled this quickly. Falling costs, modular design, and rapid deployment are turning solar into the backbone of the emerging global energy system. It’s clean, scalable, and increasingly central to modern economies. And as battery costs tumble and storage deployment accelerates, a growing number of projects are targeting round-the-clock solar electricity.

NEW in Foreign Affairs Magazine: Kurt Campbell and I argue that any serious China strategy must begin with an old truth: “Quantity is a quality all its own.” Scale matters. China has it. We can only match it through a new grand strategy of allied scale. We hang together—or separately. 🔗 Read here: https://lnkd.in/dxiRnNZN 🔸 Eight highlights from the article: 1️⃣ UNDERESTIMATING CHINA: China is slowing, aging, and indebted. But economic challenges don’t neatly translate into strategic disadvantage—especially not on the metrics and timeframes that matter in great power competition. 2️⃣ SCALE AND GREAT POWER DECLINE: The UK had a first-mover advantage. But once larger countries industrialized—Germany, the US, Russia—they outscaled it. From 1870–1910, Britain’s manufacturing share halved. 3️⃣ AMERICAN SCALE: American scale built Pax Americana. Hitler called the US a “giant state with unimaginable productive capacities." Yamamoto said Japan could hold out 6 months—no more. Italian leaders feared US “stamina.” 4️⃣ CHINA OUTSCALES THE US: That scale now belongs to China. China has: • 2× US manufacturing, 4× by 2030 (UN) • 2× US power generation • 3× car production • 13× steel output • 20× cement • 200× shipbuilding Global share: • 50% of chemicals, ships • 67% of EVs • 75% of batteries • 80% of drones • 90% of solar panels, rare earths It’s seizing the future: • 50% of industrial robots (7× US) • Leading in 4th-gen nuclear • 100+ new reactors planned • Top in patents, pubs Military scale: • 1.5× US naval vessels by 2030 (PRC 435 to US 300) • Leads in hypersonics, quantum comms • Indigenizing jet engines • Building 100 4th-gen fighters/year 5️⃣ ASSESSING CHINA: China is slowing—but also formidable. In GDP, China is 25% larger adjusted for PPP ($30T vs $24T). It is aging, but the under-15 share rose (2010–2020 “echo boom”) and the dependency ratio worsens post-2050. Debt is high, but similar to US. Housing is a bust, but credit is redirected to industry. US firms lead on profits, but Chinese firms pursue market share at a loss to win the long game. 6️⃣ BUT US ALLIES OUTSCALE CHINA: Today, the US, EU, Japan, Korea, India, Australia, Canada, Mexico, and NZ outscale China: • 3× China’s nominal GDP • 2× PPP GDP, defense spending • 1.5× manufacturing share • More patents, citations • Top trading partner of most countries 7️⃣ UNLOCKING ALLIED SCALE: Allies scale outclasses China—but only in theory. Making this real is the central task of US statecraft. Alliances must become platforms for building capacity. Japan & Korea build US ships, Taiwan makes US chips, US shares defense tech with allies, allies erect a shared wall against China’s overcapacity, etc. 8️⃣ THE WAY FORWARD: We need to go beyond even Biden’s alliance-first approach. We must avoid go-it-alone instincts and act on what Beijing already knows: 👉 Our alliances are our decisive asymmetric advantage.

The Hoysaleswara Temple in Halebidu, Karnataka, stands as a testament to India's rich architectural and engineering heritage. Among its many intricate carvings is a depiction of Masana Bhairava, a fierce form of Lord Shiva, holding what appears to be an advanced mechanical device. This sculpture has sparked discussions about the technological prowess of ancient Indian artisans. The device in question resembles a planetary gear system, characterized by an outer gear with 32 teeth and an inner gear with 16 teeth—a precise 2:1 ratio. Such mechanisms are fundamental in modern engineering, used in applications ranging from automobile transmissions to sophisticated machinery. The presence of this depiction in a centuries-old temple raises intriguing questions about the depth of mechanical knowledge possessed by our ancestors. Key Insights: 1. Advanced Understanding of Mechanics: The accurate representation of a planetary gear system suggests that ancient Indian craftsmen had a sophisticated grasp of mechanical principles. This challenges the conventional narrative that such knowledge was absent in ancient times. 2. Integration of Art and Science: The fusion of intricate artistry with precise mechanical representation indicates a holistic approach to knowledge, where art and science were not seen as separate domains but as interconnected disciplines. 3. Preservation of Knowledge: The detailed carvings serve as a medium to transmit complex ideas, ensuring that such knowledge was preserved and communicated across generations. This discovery not only highlights the ingenuity of ancient Indian artisans but also underscores the importance of re-examining historical artifacts with a fresh perspective. It prompts us to appreciate the advanced understanding embedded in our cultural heritage and encourages further exploration into the technological achievements of ancient civilizations. As we marvel at the Hoysaleswara Temple's architectural splendor, let us also acknowledge and celebrate the profound scientific insights it encapsulates. This serves as a powerful reminder of the rich legacy of innovation and knowledge that forms the foundation of our present and future advancements. #AncientIndia #EngineeringMarvels #CulturalHeritage #PlanetaryGears #HoysaleswaraTemple #Innovation

Saw literally 100's of posts saying: USA : ChatGPT China : DeepSeek India : Course on how to use them I couldn't resist but ask a simple question to all these people: When was the last time you built something? An app? A tool? Even a simple automation script? Or is your biggest contribution to tech is such posts? Because here’s what’s actually happening in India: ✅ AI & LLMs – India is home to Bhashini, a government-led multilingual AI initiative, and Sarvam AI, developing indigenous LLMs tailored for Indian languages. ✅ Semiconductors & Chips – Companies like Vedanta, Tata, and ISRO are investing heavily in semiconductor fabs, reducing dependency on global supply chains. ✅ Space Tech – ISRO’s Chandrayaan-3, Aditya-L1, and the upcoming Gaganyaan mission are pioneering space exploration on a budget that puts Hollywood sci-fi movies to shame. ✅ Fintech Revolution – India leads in UPI, Aadhaar-enabled banking, and RBI-backed digital currency, with real-time payments surpassing the USA, China, and EU combined. ✅ 5G & Telecom – Jio and Airtel are deploying indigenous 5G solutions, positioning India at the forefront of telecom innovation. ✅ EV & Clean Energy – India is pushing hard in EV manufacturing, solar energy, and green hydrogen with companies like Ola Electric, Tata, and Adani leading the way. ✅ Startups & Deep Tech – India has 100+ unicorns, with cutting-edge work happening in robotics, blockchain, and AI-driven healthcare. Meanwhile, in the USA and China, innovation continues in AI chip design, quantum computing, self-driving tech, and advanced robotics. And guess what? India has the talent to be right there, but only if more people build instead of tweet. Innovation doesn’t happen in comment sections or such posts—it happens when you do something. So, the next time you feel like typing one of these lazy takes, ask yourself: "Am I just talking about innovation, or am I actually creating it?" #BuildSomething #Innovation #Tech #IndiaInTech 🚀

𝗜𝘀 𝗔𝗜 𝘁𝗵𝗲 𝗨𝗹𝘁𝗶𝗺𝗮𝘁𝗲 𝗚𝗮𝗺𝗲 𝗖𝗵𝗮𝗻𝗴𝗲𝗿 𝗶𝗻 𝗕𝗮𝗻𝗸𝗶𝗻𝗴? 🤔 After exploring our latest Deloitte report, "𝐶ℎ𝑎𝑛𝑔𝑖𝑛𝑔 𝑡ℎ𝑒 𝐺𝑎𝑚𝑒: 𝑇ℎ𝑒 𝐼𝑚𝑝𝑎𝑐𝑡 𝑜𝑓 𝐴𝐼 𝑜𝑛 𝑡ℎ𝑒 𝐵𝑎𝑛𝑘𝑖𝑛𝑔 𝑎𝑛𝑑 𝐶𝑎𝑝𝑖𝑡𝑎𝑙 𝑀𝑎𝑟𝑘𝑒𝑡𝑠 𝑆𝑒𝑐𝑡𝑜𝑟", I’m convinced that AI isn’t just another tech upgrade - it’s a transformative force reshaping the entire industry. 🔹 𝗧𝗼𝗽 𝗜𝗻𝘀𝗶𝗴𝗵𝘁𝘀: 1️⃣ 𝗔𝗜 𝗮𝘀 𝗮 𝗦𝘁𝗿𝗮𝘁𝗲𝗴𝗶𝗰 𝗗𝗿𝗶𝘃𝗲𝗿: In the next 5 years, AI will be the controllable factor defining competitive advantage in banking. It's moving from an operational enabler to a core strategic component. 2️⃣ 𝗘𝗳𝗳𝗶𝗰𝗶𝗲𝗻𝗰𝘆 𝗨𝗽𝗹𝗶𝗳𝘁 𝗼𝗳 𝟱-𝟭𝟱%: Banks that adeptly embrace AI can anticipate significant improvements in their cost-income ratios. Agility will be the key differentiator. 3️⃣ 𝗘𝗺𝗽𝗼𝘄𝗲𝗿𝗶𝗻𝗴 𝘁𝗵𝗲 𝗪𝗼𝗿𝗸𝗳𝗼𝗿𝗰𝗲: Rather than widespread displacement, AI is set to augment human roles, freeing up employees to focus on high-value tasks like relationship management and strategic oversight. 4️⃣ 𝗧𝗵𝗲 𝗚𝗲𝗻𝗲𝗿𝗮𝘁𝗶𝘃𝗲 𝗔𝗜 𝗥𝗲𝘃𝗼𝗹𝘂𝘁𝗶𝗼𝗻: GenAI is unlocking new possibilities - from hyper-personalized customer experiences to advanced real-time analytics and innovative credit risk assessments. 5️⃣ 𝗙𝗶𝗻𝗧𝗲𝗰𝗵 𝗙𝗶𝗿𝗺𝘀 𝗟𝗲𝗮𝗱𝗶𝗻𝗴 𝘁𝗵𝗲 𝗪𝗮𝘆: Agile and risk-tolerant FinTechs are poised to outpace traditional banks in AI adoption, challenging incumbents to innovate despite legacy constraints. 💭 𝗪𝗵𝗮𝘁 𝗗𝗼𝗲𝘀 𝗧𝗵𝗶𝘀 𝗠𝗲𝗮𝗻 𝗳𝗼𝗿 𝗬𝗼𝘂? How do you see AI transforming your corner of the banking world? Are traditional banks ready to meet the challenge? 👉 𝗗𝗶𝘃𝗲 𝗶𝗻𝘁𝗼 𝘁𝗵𝗲 𝗳𝘂𝗹𝗹 𝗿𝗲𝗽𝗼𝗿𝘁 𝗵𝗲𝗿𝗲 👇 If you're curious about how AI can drive transformation in your organization, let's connect! Feel free to reach out or share your thoughts below. #AI #BankingInnovation #GenerativeAI #FinTech #DeloitteInsights #FinancialTransformation ¦ Deloitte

In 1998, Google launched a search engine that would forever change how we access information. Google wasn't the first search engine. Back then, giants like Yahoo and AltaVista dominated the digital landscape. But Google, unlike its competitors, understood something intrinsic. The true pain points of searching for information. Even when there is a leader in the market, if you understand a non-obvious but major consumer pain point, and you can build a product that delights — you take over the market, as Google did. The customer simply cannot go back to the ‘old’, when the product experience is far superior. Imagine searching for "pizza near me". In the days before Google, you might end up with a mishmash of pizza delivery services, historical information about pizza, or even an article on the geometry of a perfect pizza slice or even a recipe about pizza. ‘Search’, was merely a dumb listing of words looked up. It lacked any concept of ranking based on context. Now, let's say you typed "best pizza near me” on Google today. With its understanding of location and user intent, it would prioritize highly-rated local pizzerias with positive reviews, catering to your specific need for a delicious, close-by meal. This seemingly simple innovation — understanding the ‘why’ behind the ‘what’ —  transformed online searches from a frustrating hunt to a seamless discovery process. Google wasn't about being first; it was about being better. From incorporating voice search to offering real-time translation, it continues to adapt and anticipate our ever-changing information needs. Google Search is a game-changer when it comes to the power of user-centric design. It’s a reminder that the most revolutionary ideas sometimes lie in solving the simplest problems, like page ranking algorithms. Almost any student of Computer Science knows how to write the basic code for the algorithm. The insight is in applying it to a specific problem and user experience of the outcome. We take the power of search for granted today, but it has really been an incredible journey of information access we've been handed. As Search continues to evolve, what exciting possibilities lie ahead? Future of search will be transformed by AI. Perhaps your simple voice command “Pizza”, is enough to predict what pizza you feel like eating and automatically order it from your preferred vendor to be delivered at your home. One thing is certain, today's search algorithms will look rudimentary within the next decade. Now, a fun question to search: "Can squirrels actually fly?" Video source: Google #Google #innovation #artificialintelligence #technology #future

The global tech race isn't just about innovation speed anymore. Our latest research reveals three critical success factors: 1. AI infrastructure drives measurable growth 2. Financial discipline shapes market value 3. Geopolitical adaptability determines long-term survival The data tells a clear story— Top performers like NVIDIA (100.0) and Microsoft (96.7) aren't just innovating… …they're mastering all 3 elements while maintaining strong financial performance. See my complete analysis of how market dynamics are reshaping global tech leadership ↓ https://lnkd.in/eHqii48t

New streaming data sources and AI’s use of them have revitalized the real-time event stream processing market and boosted revenue. Product leaders can use this research to assess how real-time data, analytics and AI can enhance and differentiate their offerings and adjust their roadmaps to leverage this potential. Gartner recommends that product leaders: 🔵 Allocate a portion of the engineering budget to evaluate the accessibility and applicability of real-time data and analytics that can impact desired business outcomes. Do so by experimenting with new data streams and event logs to understand their ability to inform and adapt products and services. 🔵 Work with engineering teams to design an architecture that can leverage real-time event stream data by identifying technology and requisite technology partnerships to consume the data within the reasonable confines of your product’s existing architecture. 🔵 Demonstrate the positive effect on decision quality and outcomes that result from including real-time contextual data in your products and services. Do so by measuring the accuracy of models that either predict outcomes or recommend actions, as well as embedding the best models in decision workflows. I asked Kevin R. Quinn, Vice President, Analyst - Technical Product Management, Gartner why he believe this research matters: 💡 "AI is accelerating every aspect of business. Decisions can’t just be based on what happened, but need to account for what is happening right now." 💡"Real-time data enables timely decision-making, enhances responsiveness, improves operational efficiency, and provides a competitive edge in rapidly changing environments." Our research shows how the market for real-time streaming data is changing, and how it is more accessible and relevant for providers and end-users, than ever before. Check out the insights from Kevin R. Quinn and myself (David Pidsley) which is exclusively available to Gartner clients who are product leaders subscribed to our "Emerging Technologies and Trends Impact on Products and Services" research. ▶️ "Emerging Tech: Revolutionize Your Products With Real-Time Data and AI" [Published 31 January 2025] 🔗 https://lnkd.in/ev7nk82R (requires client login) #DecisionIntelligence #RealTime #Data #AI #RealTimeData #StreamingData #StreamingAnalytics #StreamAnalytics #EventStream #EventStreamProcessing