AI News Archive: June 25, 2026 — Part 5
Sourced from 500+ daily AI sources, scored by relevance.
- How much water does AI really use?
The heaviest demand on America's water supply isn't data centers or AI. It's from everyday uses such as growing food, watering lawns and flushing toilets.
- Softbank CEO Who’s Invested $64 Billion in OpenAI Says It’s “Blasphemy” to Mention the AI Bubble
"It's just the beginning. AI's potential will be unlocked." The post Softbank CEO Who’s Invested $64 Billion in OpenAI Says It’s “Blasphemy” to Mention the AI Bubble appeared first on Futurism .
Score: 59🌐 MovesJun 25, 2026https://futurism.com/artificial-intelligence/softbank-ceo-blasphemy-ai-bubble - OpenAI's updated GPT-5.5 Instant is better at shopping, complex constraints, and understanding user intent — and it's already in the API
OpenAI has made a significant update to its most widely used language model, GPT-5.5 Instant, which is the default in the free version of ChatGPT. The company announced the upgraded version of GPT-5.5 Instant yesterday on X, calling it "much more fun to talk to" and saying it is "better at understanding the intent behind a question and adapting its response accordingly," as well as offering improvements in shopping results, local recommendations, and handling "complex constraints." However, it has not yet provided any benchmarks or numerical results to quantify these claims. The company said the updated GPT-5.5 Instant was rolling out first to paid ChatGPT subscribers and then to free users as of today, June 25. OpenAI also updated its chat-latest API alias , which points to the latest GPT-5.5 Instant model currently used in ChatGPT, while continuing to recommend the separate gpt-5.5 model for production API usage. That distinction matters, but it should not obscure the main news: this is primarily a ChatGPT-side update to GPT-5.5 Instant, not a new release of the broader GPT-5.5 API model family. Let's dig into what's changed... Origins of GPT-5.5 Instant, and why OpenAI updated it less than two months later GPT-5.5 Instant was first unveiled in early May 2026, just under two months ago, to replace the aging GPT-5.3 Instant engine as the baseline default model for ChatGPT users. Developed as a fast, high-throughput variant of OpenAI’s core flagship model family, the initial spring release focused heavily on correcting systemic factuality deficits. Internal benchmarks from that spring deployment reported a 52.5% reduction in hallucinated claims compared to GPT-5.3 Instant on high-stakes medical, legal, and financial prompts, alongside a 37.3% drop in factual error rates on user-flagged historical conversations. Independent evaluators noted that its predecessor, GPT-5.3 Instant, had struggled in public rankings, placing 44th overall in Arena benchmarks. That gave the May rollout a clear purpose: OpenAI needed a stronger default model for everyday ChatGPT interactions, not just a more capable frontier model for advanced users. Stylistically, the initial spring model introduced a sharper conversational baseline, demonstrating a 30.2% reduction in word count and a 29.2% drop in line usage over typical advice prompts. However, the spring deployment also introduced an operational fault line for enterprise software systems: a feature known as "memory sources." Designed to grant users visibility into the specific past chats, files, and connected Gmail accounts shaping a personalized answer, memory sources introduced a loose, model-reported observability layer. As reported by VentureBeat , these internal summaries frequently clashed with the deterministic logs of localized vector databases and enterprise Retrieval-Augmented Generation (RAG) pipelines. The resulting friction created dual, competing context records, making it difficult for administrators to reconcile what the model claimed it referenced against what it actually accessed in production. The June 24 update does not appear to expand memory sources directly. Instead, it focuses on making GPT-5.5 Instant better at understanding user intent, carrying context across turns, following multi-part instructions, and producing more useful shopping and local recommendations. A smarter, more 'fun' ChatGPT for consumers For everyday users of ChatGPT, the most noticeable change in GPT-5.5 Instant will be the model’s improved intent recognition. According to OpenAI’s latest release notes, GPT-5.5 Instant has improved at identifying the underlying goal behind a user's question, particularly in decision-support scenarios like planning, shopping, asking for advice, researching options and comparing local choices. Historically, large language models have struggled when given prompts with multiple overlapping constraints — often dropping one or two requirements in favor of a generalized response. The updated GPT-5.5 Instant handles these complex instructions more reliably. When users push back on an answer, clarify their meaning, or introduce new constraints mid-conversation, the model should adapt dynamically rather than stubbornly repeating its original approach. This contextual awareness extends heavily into commerce and local recommendations. GPT-5.5 Instant now makes better use of location context to surface nearby options, weaving together product recommendations, business information, and relevant images into a more cohesive output when those elements are useful. Furthermore, OpenAI notes that the stylistic formatting of these responses is less rigidly templated, trading robotic lists for a more intentionally designed, warmer and restrained conversational tone. Developers can test the latest Instant behavior through chat-latest For the developer ecosystem, the June 24 GPT-5.5 Instant update is accessible through OpenAI’s updated chat-latest API alias. chat-latest is not the same thing as the production gpt-5.5 model slug. OpenAI says chat-latest points to the latest Instant model currently used in ChatGPT, and it recommends the separate gpt-5.5 model for production API usage. Developers can use chat-latest to test the newest ChatGPT-style improvements, while using gpt-5.5 when they need a stable production target. The current chat-latest model page lists a 400,000-token context window and support for up to 128,000 maximum output tokens. Its knowledge cutoff is Aug. 31, 2025. On pricing, chat-latest uses the same $5.00 per 1 million input tokens and $30.00 per 1 million output tokens listed on its model page. Cached inputs cost $0.50 per 1 million tokens, a 90% discount that strongly incentivizes developers to optimize prompts by placing static instructions first and dynamic data later. The model supports text and image input, text output, streaming, function calling and structured outputs. Through the Responses API, the chat-latest page also lists support for web search, file search, image generation, code interpreter and MCP. The practical takeaway is simple: chat-latest gives developers access to the updated Instant-style behavior, but OpenAI is still steering production API builders toward the separate gpt-5.5 model. The broader GPT-5.5 API model includes a larger feature set and different production profile, but that is not the main focus of this update. Why this matters for enterprise AI teams For enterprises, the June 24 GPT-5.5 Instant update lands at the intersection of two related but distinct trends: better default user experience in ChatGPT, and more reliable orchestration behavior in the API. The consumer-facing changes make ChatGPT more useful for everyday decision-making. Users should see better handling of messy, real-world requests: planning a trip with several constraints, comparing products, finding nearby businesses, or adjusting a recommendation after adding a new requirement. The enterprise relevance is less about a new technical architecture and more about default behavior. A model that better infers intent, preserves context across turns and follows multi-part constraints can make ChatGPT more reliable for employees using it for research, planning, purchasing decisions, customer-facing drafts and internal analysis. But enterprises should remain careful about observability. Memory sources can help users understand why ChatGPT personalized an answer, but they do not provide a complete audit trail. Organizations that already rely on RAG pipelines, vector databases, orchestration logs and internal agent traces should define which record acts as the source of truth when a model’s visible memory sources do not fully match the system’s own logs. What’s next? The release of GPT-5.5 Instant and the updated chat-latest alias signals a maturation in how generative models are deployed. OpenAI is moving away from models that require heavy hand-holding and toward systems that can better infer the user’s goal, preserve constraints and adapt across multiple turns. Whether it is a consumer planning a complex multi-city vacation in ChatGPT, or a developer orchestrating a codebase-navigating agent through the API, GPT-5.5 represents a faster, smarter and more capable baseline for the future of AI workflows. The most important takeaway for developers is also the simplest: GPT-5.5 Instant, chat-latest and gpt-5.5 are related, but they are not the same product surface. GPT-5.5 Instant is the ChatGPT model users experience directly. chat-latest is a moving alias for testing the latest Instant behavior through the API. gpt-5.5 is the production model OpenAI recommends for developers building stable applications.
- YesWeHack Launches Agentic Pentest for AI Security Testing
YesWeHack, the offensive security and exposure management platform, announces Agentic Pentest, an on-demand solution using autonomous AI agents to test organisations' assets and deliver same-day findings.
Score: 59🌐 MovesJun 25, 2026https://www.itweb.co.za/article/yeswehack-launches-agentic-pentest-for-ai-security-testing/Pero3MZ31gdqQb6m - The Future of AI Is in Ted Cruz’s Hands Now
No way it can be as bad as a 10-year moratorium on regulation, right?
Score: 59🌐 MovesJun 25, 2026https://gizmodo.com/the-future-of-ai-is-in-ted-cruzs-hands-now-2000777803 - Building AI-Optical Network to Drive New Growth in the AI Era
Building AI-Optical Network to Drive New Growth in the AI Era The Straits Times
- Trusted Agents at Scale: How Open Discovery Is Unifying the Agentic Enterprise
As a founding partner to the new Agentic Resource Discovery specification, Salesforce is helping shape the open standard that gives AI agents a universal way to find, trust, and invoke capabilities across any platform.
- Exclusive: Codex agents are inching into the mainstream
AI is moving from chat and web search to delegated work. Why it matters: The frontier AI labs have spent years promising that effective AI agents will act as our minions in the workplace and at home, and that might soon be a reality. The big picture: Use of Codex — OpenAI's agentic coding and work platform — is accelerating, according to a new report from OpenAI, Columbia, Duke and the University of Pennsylvania. The researchers separate Codex users into three categories: OpenAI employees, outside organizations and individual users. Then they measured usage of Codex versus ChatGPT, by tokens. 99.8% of OpenAI employees' output tokens were produced with Codex, compared with 63% for organizations and 16.5% for individuals. OpenAI's own Codex use is meant to represent how users might turn to agents when cost, access, training and buy-in are mostly removed. Among active users of ChatGPT and Codex at organizations outside OpenAI, just above 0% used Codex in August 2025. That share is now around 17%. Between the lines: The number of individuals using Codex is still small, but those who use it use it a lot, per the report, shared first with Axios. By the numbers: In a sample of individual Codex users, 80.6% made at least one Codex request estimated to represent more than 30 minutes of work by an "experienced human." 70.2% of Codex users made at least one request estimated to save more than an hour of human work. 25.6% had delegated work estimated to take more than eight hours for a human to complete. The fine print: The report says the thresholds are model-estimated and based on a 0.1% random sample of individual users who opted to allow queries for training. Zoom in: Non-developers are the fastest-growing user group, even though software work is still the core use case for Codex. Catch up quick: The shift to agentic work began in earnest at the beginning of 2026. That's when normal people began to allow Codex, OpenClaw, and Anthropic's Claude Code to interact with their desktops, manage calendars, read and write files, control web browsers, and execute scripts. My thought bubble: As a journalist who has spent years covering cybersecurity — and whose coding knowledge tops out at early-2000s HTML — I was wary of giving agents access to my files, browser and apps. But over the last month, I've started using Codex and Claude Code for a lot of the work and life admin I used to handle manually. My agents fill out expense reports, triage email, make hair appointments and report packages stolen from my apartment lobby. Yes, this does happen often enough in San Francisco that I have saved time automating the task. What they're saying: "Agents are reducing what I'd call the psychological cost of action," workplace culture expert Jessica Kriegel tells Axios. They "make unfamiliar work feel more approachable, which means I start sooner, experiment more, and spend less energy worrying about what I don't know." Yes, but: Most AI users are still chatting with bots and not managing an army of agents. Among consumers on the Go, Free, Pro and Plus plans who were active on either ChatGPT or Codex in the last 28 days, fewer than 1% used Codex.
- Exclusive: LucidLink launches MCP server to give AI agents shared access to distributed files
LucidLink Corp., the maker of a cloud network-attached storage system based on object storage technology, today extended its distributed file system technology into agentic artificial intelligence with the public beta release of a Model Context Protocol server that lets AI agents access shared files across clouds, on-premises systems and edge environments. The company said its […] The post Exclusive: LucidLink launches MCP server to give AI agents shared access to distributed files appeared first on SiliconANGLE .
- Stanford launches AI economy indicator to match AI's pace
Stanford launches AI economy indicator to match AI's pace marketplace.org
Score: 58🌐 MovesJun 25, 2026https://www.marketplace.org/episode/2026/06/25/stanford-launches-ai-economy-indicator-to-match-ais-pace - Govt could get a minority stake in Sarvam through IndiaAI Mission support
Days after Sarvam closed its Series B round of funding, raising $234 million and becoming an AI unicorn, it has been revealed that the Indian govt. could become its 1-2% stakeholder via IndiaAI. The post Govt could get a minority stake in Sarvam through IndiaAI Mission support appeared first on MEDIANAMA .
Score: 58🌐 MovesJun 25, 2026https://www.medianama.com/2026/06/223-govt-minority-stake-sarvam-indiaai-mission/ - The ‘mass affluent’ are losing their allure for wealth managers navigating AI
The ‘mass affluent’ are losing their allure for wealth managers navigating AI The Straits Times
- Huawei lays out six priorities for AI-era mobile networks
Telecom carriers could eventually earn from AI activity on their networks.
Score: 58🌐 MovesJun 25, 2026https://kr-asia.com/huawei-lays-out-six-priorities-for-ai-era-mobile-networks - Pentesting Can T Keep Up With Ai Coding Report
Pentesting Can T Keep Up With Ai Coding Report Computing UK
Score: 58🌐 MovesJun 25, 2026https://www.computing.co.uk/category/undefined/news/2026/security/pentesting-can-t-keep-up-with-ai-coding-report - Netris raises $15M Series A from a16z to help AI neoclouds go live faster
Netris provides software that runs on network switches, and offers a platform that helps neocloud operators reduce the time it takes to go live.
Score: 58💰 MoneyJun 25, 2026https://techcrunch.com/2026/06/25/netris-raises-15m-series-a-from-a16z-to-help-ai-neoclouds-go-live-faster/ - LG CNS launches agentic AI ERP testing solution
LG CNS said Thursday it has launched an agentic AI-powered enterprise resource planning, or ERP, testing solution, as it steps up its push into the global SAP market. Called PerfecTwin ERP Edition, the solution automates ERP testing using real transaction data, helping companies detect defects before migrating to SAP's latest ERP platform, S/4HANA, or launching new ERP systems. ERP systems manage core business functions including finance, manufacturing, procurement, logistics and human resources
- Announcing The Forrester Wave™ On Extended Detection And Response Platforms: Platformization, AI, And … AI
Last week, Forrester released The Forrester Wave™: Extended Detection And Response Platforms, Q2 2026. This is the third iteration of the extended detection and response (XDR) Wave, with prior versions published in 2021 and 2024. This Wave differs significantly from the past, especially because of: The number of vendors. This year, only seven vendors were […]
- As Hollywood jobs dry up, workers are quietly training AI models to survive
As Hollywood jobs grow scarce, writers, editors, and executives are quietly taking AI training gigs just to make ends meet, even as the pay is unstable and the work chaotic.
- China Wants AI To Make Consumers Spend Again
China's Ministry of Commerce and seven other agencies released a plan to motivate customers to buy new products with AI capabilities as a way of stimulating consumer spending.
Score: 57🌐 MovesJun 25, 2026https://www.forbes.com/sites/ronschmelzer/2026/06/25/china-wants-ai-to-make-consumers-spend-again/ - Ford Made This 1 Miscalculation on AI—and Then Had to Hire More Humans to Fix It
After topping a prestigious ranking, Ford got candid about fixing AI-related mistakes.
- New York City Council candidate is accused of forgery over AI-generated posts
A former New York City Council candidate has been charged with forgery over allegations he used artificial intelligence to post fake endorsements and news articles on social media
Score: 57🌐 MovesJun 25, 2026https://abcnews.com/Technology/wireStory/new-york-city-council-candidate-accused-forgery-ai-134192509 - As better chatbots get harder to build, AI turns to simulated worlds
In pursuit of human-level intelligence, researchers are developing agents that learn by acting in virtual environments rather than simply absorbing more text
Score: 56🌐 MovesJun 25, 2026https://www.science.org/content/article/better-chatbots-get-harder-build-ai-turns-simulated-worlds - Agentic infrastructure startup Seltz raises $12.5M to help AI agents search the web for answers
Agentic search startup Seltz Inc. said today it has bagged $12.5 million in seed funding to build a more optimal infrastructure so that artificial intelligence agents can find their way around the web. The round was led by Speedinvest and B Capital. Also participating were Italian Founders Fund, Future Back Ventures, futurepresent, Arc Investors, Vento Ventures, Mango […] The post Agentic infrastructure startup Seltz raises $12.5M to help AI agents search the web for answers appeared first on SiliconANGLE .
- Improving the speed and energy-efficiency of AI agents
A new system, known as Murakkab, optimizes the design and deployment of multistep workflows that power AI applications.
Score: 56🌐 MovesJun 25, 2026https://news.mit.edu/2026/improving-ai-agent-speed-and-energy-efficiency-0625 - The Wild West era of robotaxis is starting to end
The first global robotaxi rules set common safety expectations for fully autonomous vehicles, giving automakers a clearer target while leaving city approvals, local rules, and readiness as major rollout hurdles.
Score: 56🌐 MovesJun 25, 2026https://www.digitaltrends.com/cars/the-wild-west-era-of-robotaxis-is-starting-to-end/ - Epic boss Tim Sweeney blasts Steam for putting AI tags on games — says move is ‘irresponsible of Valve’
The Epic executive said in an interview after unveiling Unreal Engine 6 that AI tools help make developers far more productive. Putting the AI tag on games discourage their use, especially as titles with this label gets fewer reviews and tend to have more negative reviews, as well.
- IPO-bound AgiBot starts eight-robot tablet QC trial
The company aims to complete experimental verification of solutions for seven industries in the first half of 2026.
Score: 56🌐 MovesJun 25, 2026https://www.techinasia.com/chinas-agibot-launches-sales-robot-types-jdcom - DeepSeek hiring spree: Chinese AI firm seeks newcomers as it pursues AGI
DeepSeek is looking to “at least double the size of every department” in a new hiring spree, according to an announcement made by the Chinese AI champion on Thursday. The firm announced openings in 33 positions across seven major categories, including full-stack development and algorithms, artificial intelligence (AI) core system R&D, deep learning research, and model data strategy product management and engineering. “DeepSeek’s hiring philosophy is to let newcomers take on the most core and...
- Protecting customers faster: How Adobe is responding to AI-accelerated vulnerability discovery
Protecting customers faster: How Adobe is responding to AI-accelerated vulnerability discovery Adobe
- Your AI coworker in Slack with context across every system
Glean’s AI coworker connects Jira, Confluence, Salesforce, meeting context, and more in Slack.
- Penn semiconductor spinout raises $10M to build chips for defense and AI
The 2-year-old company plans to use the funding to expand its engineering and commercial teams.
Score: 55💰 MoneyJun 25, 2026https://www.bizjournals.com/philadelphia/news/2026/06/25/agni-penn-ai-defense-chip-memory.html?ana=brss_6150 - Benefit claimants use AI chatbots to cash in on welfare
Benefit claimants use AI chatbots to cash in on welfare The Telegraph
Score: 55🌐 MovesJun 25, 2026https://www.telegraph.co.uk/money/consumer-affairs/benefit-claimants-use-ai-chatbots-to-cash-in-on-welfare/ - Paystack launches AI-powered checkout for Nigerian consumers
Paystack has launched an experimental product that allows users in Nigeria to check out with supported Paystack merchants using AI agents.
Score: 55🌐 MovesJun 25, 2026https://techcabal.com/2026/06/25/paystack-launches-ai-powered-checkout-for-nigerian-consumers/ - Thai stock market thriving as surprise beneficiary of AI boom
Thai stock market thriving as surprise beneficiary of AI boom The Japan Times
Score: 55🌐 MovesJun 25, 2026https://www.japantimes.co.jp/business/2026/06/25/companies/thailand-ai-stock-winner/ - Micron joins rivals pitching AI deals as cure for memory's boom-bust cycle
Micron joins rivals pitching AI deals as cure for memory's boom-bust cycle Reuters
- Robots that can identify materials and map unknown environments could aid nuclear and defense sectors
Robots that can see beyond human vision, build live 3D maps of unknown environments and identify what objects are made of are being developed by researchers at the University of Surrey, opening new possibilities for applications in nuclear inspection, rail and building safety, and search and rescue in combat zones.
Score: 55🌐 MovesJun 25, 2026https://techxplore.com/news/2026-06-robots-materials-unknown-environments-aid.html - Large Language Models Are Overkill For Some Marketing Tasks. Enter The Small Language Model
It’s no secret that large language models (LLMs) have gotten exorbitantly expensive. Companies are starting to limit their employees’ AI usage to save money; OpenAI has even discussed lowering the cost of tokens to retain financially anxious customers. But you know what’s cheaper than a large language model? A small language model. AI company ZeroGPU […] The post Large Language Models Are Overkill For Some Marketing Tasks. Enter The Small Language Model appeared first on AdExchanger .
- EisnerAmper Leverages DAS Powered by Caseware to Unify Audit and Build an Agentic Future Across Its Multi-Vertical Practice
EisnerAmper Leverages DAS Powered by Caseware to Unify Audit and Build an Agentic Future Across Its Multi-Vertical Practice Toronto Star
- Deep Agents and OpenCode are now available in the AI SDK Harness
The AI SDK Harness lets you run established coding-agent runtimes through one unified interface, so you can switch runtimes without changing your application code. Today we're adding two new adapters, Deep Agents and OpenCode, both running inside a Vercel Sandbox. Deep Agents @ai-sdk/harness-deepagents adapts LangChain's deepagents runtime, with built-in file and shell tools, skills, host tools, multi-turn sessions, attach and resume, and built-in tool approvals. Read the Deep Agents harness documentation to get started. OpenCode @ai-sdk/harness-opencode boots a real OpenCode server inside the sandbox via @opencode-ai/sdk and streams its session events through the harness. It exposes OpenCode's built-in tools, supports both built-in and host tool approvals, and lets you pick the model, provider, and reasoning variant. Read the OpenCode harness documentation to get started. The full supported list of harnesses is now: Claude Code, Codex, Deep Agents, OpenCode, Pi, with more coming soon. Read more
- AI導入の最前線——3人のCIOが語る戦略的優先事項
保険ブローカーTrucordiaのCIO、Rajeev Khanna氏の戦略的優先事項は、多くのCIOと同様、組織全体へのAI導入が最上位にある。サイバーセキュリティ、データ・分析プロジェクト、イノベーションも並行して進めている。どれも特別なものではないが、Khanna氏は汎用的なテンプレートや曖昧な目標では進められないと理解している。自動化とAIでワークフローを効率化し、テクノロジーで顧客の特定のニーズに応え、新しい製品・サービスで市場での差別化と成長を実現する。 「テクノロジーがビジネスのイノベーションと提供スピードを実現している」とKhanna氏は言う。 CIO.comのState of the CIO調査によれば、CIOが挙げる最も戦略的に重要な技術施策は、「生成AI」が最上位、続いて「エージェンティックAI」「データ・ビジネス分析」「セキュリティ・リスク管理」「IT・ビジネスプロセスの自動化」が上位5つを占めている。「モダナイゼーション」「クラウド管理」「クラウドへのアプリケーション開発・移行」といった従来型のITタスクは、それより下位に位置する。 CIOやアドバイザー、アナリストは、この施策リストがテック幹部の関心の変化を映していると指摘する。技術的な卓越性そのものを主目的とするのではなく、組織の戦略とビジネス成果を形作り、実現することにより多くのエネルギーを注いでいるのだ。「CIOは、AI導入とビジネス価値をエンタープライズ規模で推進するために必要なITアーキテクチャ、組織構造、プロセス変革の先頭に立っている」と調査は指摘する。 こうした変化は、CIOの役割が「業務の指示を受けて動く存在」から「変革のリーダー」へと進化していることを示している。CIOは事業部門のリーダーと積極的に連携し、AI導入を推進し、すべての技術施策から高い価値の成果を引き出すことに注力している。実際、2026年のCIOは事業リーダーとの協働、新興技術の学習、AI施策を支える組織構造の構築に多くの時間を割くようになった。その反面で、ベンダーとの交渉、ITの危機対応、コスト管理に費やす時間は前年より減っている。 テクノロジーが新しいケイパビリティと製品を生む Khanna氏は「組織にとって差別化につながる新しいケイパビリティを生み出し、クライアント向けの新製品をより効率的かつ速いペースで立ち上げること」を優先している。そこでは、多くの場合AIを使っているという。データと分析を活用するプロジェクトも優先しており、たとえば分析ツールにLLMを組み込み、ユーザーが自然言語でデータに問いかけられるようにしている。 そこで「常に最優先」とKhanna氏がいうのが「サイバーセキュリティ」だは言う。「サイバーは常に動く標的だ。最新の状態を保ち、現代化し、攻撃者の手口の先を行く必要がある。それは永遠に続く取り組みだ」。 AIのスケーリングが目標になる MetLifeのグローバルCIO、Nick Nadgauda氏も同様にITの戦略的施策をビジネスの推進力として語る。「最も戦略的に重要な施策は、散発的な実験にとどまっていたAIを、企業の運営に組み込まれた中核的で信頼できるケイパビリティへとスケールさせることだ。MetLifeではAIを単独の技術プロジェクトではなく、戦略の重要な実現手段として捉えている。意思決定を磨き、業務を簡素化し、最終的に顧客とビジネスにより良い成果をもたらす」。 MetLifeは社内向けのAI統合プラットフォーム「MetIQ」を展開し、「セキュアでガバナンスされた環境でチームがAIソリューションを実験・構築・展開できる」ようにしているとNadgauda氏は説明する。「データ、プライバシー、リスクに関する強固な管理を維持しながら、急速に進化するテクノロジーに適応できる柔軟性を提供している」と言う。 MetLifeのIT部門は、AIを社員のツールやプロセスに統合し、「事後ではなく、意思決定の早い段階から支援する思考のパートナー」にしている。AIの体験、ツール、トレーニングは「人々の実際の働き方に合わせて意図的に設計」されており、社員が自分の日常業務にAIの関連性を感じることで「意味のある導入」が実現している。その結果、AIは「エンジニアリング、オペレーション、顧客対応チームにおける仕事の進め方の自然な一部」になったとNadgauda氏は言う。 「テクノロジーとビジネスが完全に絡み合う世界で、企業の運営方法そのものを形作ることだ。ビジネスがより速く動き、より良い意思決定を下し、顧客により強い成果を届けられるようにすることを常に考える必要がある」（Nadgauda氏）。 エージェンティックAIが優先事項になる Tata Consultancy ServicesのCIO、Janardhan Santhanam氏も、ビジネスの変革をITの戦略的な使命と捉え、その推進力としてエージェンティックAIを位置づける。State of the CIO調査では、回答者の38%がエージェンティックAIを戦略的に重要な技術施策として挙げている。 「最も重要な施策は、エージェンティックな企業として仕事の進め方そのものを再定義すること」とSanthanam氏は言う。目標は「組織の成長に欠かせない、持続的で非線形なパフォーマンス向上」を実現することだ。 「社員の間にAIファーストの文化を作り、社内の機能とITのオペレーティングモデルを『エージェント＋アプリ＋人間』が協働してインテリジェントな意思決定と自律的な実行を行う形にリセットすることだ。AIインフラを全員の手に届けるだけでなく、権限も分散させ、2倍の力を持つワーカーとチームを生み出している」とSanthanam氏は説明する。さらにIT部門は各事業部門のプロセスを再構築し、Santhanam氏はこれを「ファンクション・アズ・ア・プラットフォーム」と表現する。同調査が挙げる別の重要施策と同様、TCSもAI推進の中でセキュリティ、プライバシー、コンプライアンスを優先している。 エージェンティックAIへの期待は高い。2026年4月のHFS ResearchとGenpactの調査では、92%の経営幹部がエージェンティックAIが仕事の進め方を根本的に変えると考えている。FTI Consultingのシニアマネージングディレクター、Oz Vural氏は「ITはガードレールの中でワークフローを実行しリアルタイムで判断できるエージェンティックAIへ移行する必要がある」と言う。これは単に時間を節約するだけでなく、CIOが収益とEBITAの向上に貢献できる機会だ。CIOの成功指標も、いかに速く「インテリジェンスへの到達時間」を短縮できるかへと変わりつつある。
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