AI News Archive: July 13, 2026 — Part 4
Sourced from 500+ daily AI sources, scored by relevance.
- Tesla Says It’s Building a Wheelchair-Accessible Robotaxi
A Tesla representative at a DC hearing said the vehicle is “an active product being built.” But its timeline isn’t clear.
Score: 59🌐 MovesJul 13, 2026https://www.wired.com/story/tesla-says-its-building-a-wheelchair-accessible-robotaxi/ - Apple fails to stem data exfiltration, as OpenAI poaches hundreds
Apple's lawsuit describes a campaign of theft – and also a failure of basic security, such as managing company laptops and spotting sensitive documents being emailed.
Score: 58🌐 MovesJul 13, 2026https://www.thestack.technology/apple-failed-to-spot-data-exfiltration-openai/ - What is BrainCo, the Chinese startup taking on Neuralink in brain computer interfaces?
What is BrainCo, the Chinese startup taking on Neuralink in brain computer interfaces?
- Lazard's Bilicic Sees 'Tremendous' Demand for AI Data Center Power
George Bilicic, Lazard's global head of power, energy and infrastructure, says we're a long way from solving the issue of energy demand for AI data center power and expects upward pressure on gas prices. He speaks on "Bloomberg Open Interest." (Source: Bloomberg)
Score: 58🌐 MovesJul 13, 2026https://www.bloomberg.com/news/videos/2026-07-13/lazard-s-bilicic-sees-tremendous-demand-for-ai-power-video - Anthropic starts localizing Claude pricing for India, its biggest market after the US
Claude users in India are starting to see Indian rupee-denominated subscription plans.
- Integrated Transport Centre introduces the first special license plates for trial and commercial autonomous vehicles in Abu Dhabi
Under the Supervision of the Smart and Autonomous Systems Council
- Amazon preps robotics-equipped sorting warehouse in Texas
The site will sit within the e-commerce giant’s fulfillment network and further expand its use of automation across the supply chain.
Score: 58🌐 MovesJul 13, 2026https://www.supplychaindive.com/news/amazon-preps-robotics-equipped-sorting-warehouse-in-texas/824978/ - OpenAI just took the handcuffs off your ChatGPT Work and Codex usage limits, at least for now
OpenAI is temporarily removing the 5 hour usage limit for Plus, Business, and Pro users across Codex and ChatGPT Work, and making GPT 5.6 Sol more efficient so your usage goes further.
- AI agents create virtual playgrounds to help robots get crucial training data
“SceneSmith” system uses collaborative AI agents to create realistic 3D environments of places like kitchens, hotels, and living rooms, where robots can simulate everyday chores.
Score: 57🌐 MovesJul 13, 2026https://news.mit.edu/2026/ai-agents-create-virtual-playgrounds-to-help-robots-get-crucial-training-data-0713 - Rethinking Ethernet For The AI Scale-Up Era: Inside ESUN
Evolving Ethernet into a lossless, low-latency, deterministic transport built for the way AI accelerators actually talk to each other. The post Rethinking Ethernet For The AI Scale-Up Era: Inside ESUN appeared first on Semiconductor Engineering .
Score: 57🌐 MovesJul 13, 2026https://semiengineering.com/rethinking-ethernet-for-the-ai-scale-up-era-inside-esun/ - HCLTech net profit rises 20%, plans Rs 3500 cr investment in AI data centres
HCLTech net profit rises 20%, plans Rs 3500 cr investment in AI data centres YourStory.com
Score: 56🌐 MovesJul 13, 2026https://yourstory.com/enterprise-story/2026/07/hcltech-net-profit-rises-20-rs-3500-cr-investment-ai-data-centres - Sunrun CEO offers customers cash to use rooftop solar for mini AI data centers
Sunrun CEO Mary Powell plans to transform homes with solar and batteries into AI computing hubs, noting that homeowners could earn hundreds of dollars a month by hosting AI compute nodes.
- AI adoption is changing how enterprises think about intellectual property
As enterprises adopt AI, the challenge is shifting from protecting data to safeguarding institutional knowledge. Here's why governance, portability and AI ownership are becoming critical
- A manifesto for Sustainability Robotics
Nature Machine Intelligence, Published online: 13 July 2026; doi:10.1038/s42256-026-01260-6 Song et al. propose Sustainability Robotics as a new discipline to overcome fragmentation and enhance societal and environmental impact. They define three guiding principles, alongside two dimensions spanning sustainable design and robotics for sustainability.
- AISec: The New Security Imperative For The AI-Driven Enterprise
AI is reshaping software and enterprise operations, creating new risks. AISec emerges as a critical discipline to secure AI-driven systems and autonomous processes.
- Permitting, Licensing Tech Firm Accela Buys Civira AI
The gov tech supplier, which also sells disaster recovery, plan review and other software to public agencies, aims to make AI deployments easier and less expensive for customers. A company executive discusses the deal.
Score: 55💰 MoneyJul 13, 2026https://www.govtech.com/biz/permitting-licensing-tech-firm-accela-buys-civira-ai - Now, defenders are embracing the prompt injection, too
"Context bombing" tricks hacking agents into shutting down before they can do harm.
Score: 55🌐 MovesJul 13, 2026https://arstechnica.com/security/2026/07/now-defenders-are-embracing-the-prompt-injection-too/ - How Enterprises Should Respond to Economists’ AI Risk Letter
With this letter, policy changes may be coming, so enterprises should attempt to get ahead of them.
Score: 55🌐 MovesJul 13, 2026https://aibusiness.com/generative-ai/how-enterprises-should-respond-economists-ai-risk-letter - Meet the magnetic liquid metal robot that merges & squeezes through tiny gaps
Meet the magnetic liquid metal robot that merges & squeezes through tiny gaps
- LTM partners with Anthropic to accelerate Claude adoption and expand enterprise delivery
LTM announced a partnership with Anthropic to accelerate enterprise-scale adoption of Claude, Claude Code and Claude Cowork across engineering, modernisation, and business workflows. The post LTM partners with Anthropic to accelerate Claude adoption and expand enterprise delivery appeared first on Express Computer .
- The cold data challenge behind India’s AI ambitions
The cold data challenge behind India’s AI ambitions Techcircle
Score: 55🌐 MovesJul 13, 2026https://www.techcircle.in/2026/07/13/the-cold-data-challenge-behind-india-s-ai-ambitions - Tata Communications builds the foundation for Asia’s AI future
Tata Communications’ latest investment to build a new subsea cable connecting India to Singapore is more than another cable announcement.
Score: 55🌐 MovesJul 13, 2026https://www.techmonitor.ai/comment-2/tata-communications-builds-the-foundation-for-asias-ai-future - SoftBank, Yaskawa demo AI platform for robots
The companies said the platform covers robot motion data collection and AI training.
- Companies turn to Chinese AI models to cut costs
DoorDash, Siemens and Airbnb are among those seeking to curb ballooning bills and reduce reliance on US technology
- Microsoft Intros ROI Tracking for AI Agents, Expands Copilot in Forms
Microsoft is introducing new capabilities aimed at showing organizations whether artificial intelligence agents deliver measurable value while expanding how Copilot can create and analyze surveys.
- Indian companies look to Chinese LLMs as AI costs bite
Indian companies look to Chinese LLMs as AI costs bite Nikkei Asia
- Monzo founder joins AI giant Anthropic
Monzo founder joins AI giant Anthropic The Telegraph
Score: 53🌐 MovesJul 13, 2026https://www.telegraph.co.uk/business/2026/07/13/monzo-founder-joins-ai-giant-anthropic/ - Anthropic expanding Claude Cowork to mobile and web, details here [U]
Update 7/13: Fable 5 access on all paid plans has been extended once more through Sunday, July 19. Anthropic announced today that it is expanding Claude Cowork capabilities from the desktop app to the web and mobile. Claude Cowork on mobile and the web will start as a beta feature with a gradual rollout on select paid plans. Additionally, Anthropic is extending Claude Fable 5 access to all paid plans for a few more days.
Score: 53🌐 MovesJul 13, 2026https://9to5mac.com/2026/07/13/anthropic-expanding-claude-cowork-to-mobile-and-web-details-here/ - Claude’s values across models and languages
Claude’s values across models and languages
- One in four social media posts is AI-speak
LinkedIn and Medium top the list as AI-generated posts proliferate, says Pangram report
Score: 53🌐 MovesJul 13, 2026https://www.thehindubusinessline.com/news/one-in-four-social-media-posts-is-ai-speak/article71218629.ece - AI Was Supposed to Save Companies Money. Instead, It’s Blowing Up Budgets in a Big Way
A new report from KPMG finds that executives are aghast at their AI bills. It’s a warning for any business leader planning to go all-in on the tech.
- CX Daily: China Tech Giants Battle to Build the Ultimate AI Concierge
CX Daily: China Tech Giants Battle to Build the Ultimate AI Concierge Caixin Global
- Marines eye cloudless networks to keep AI tools running when the cloud goes down
The software company Ditto says it can solve a key problem by networking “whatever transports the customer brings.”
Score: 52🌐 MovesJul 13, 2026https://www.defenseone.com/defense-systems/2026/07/marines-cloudless-networks-ai-cloud/414716/ - An AI can invent entirely new languages. But is it creative?
Researchers debate whether tool produces genuinely novel tongues, or simply spits out a remix
Score: 52🌐 MovesJul 13, 2026https://www.science.org/content/article/ai-can-invent-entirely-new-languages-it-creative - AI is killing low cost smartphones
Except for the second user/refurbished smartphone markets, AI means the days of cheap phones are over, with huge price pressures putting low-end vendors out of business. Omdia data confirms that Apple and Samsung are undisputed kings of the hill, combining for 42% of the market even as smartphone sales overall have seen a 4% average decline. The two companies increased market share by 4% (Apple) and 2% (Samsung) compared with 2Q25. Meanwhile, the situation is becoming much worse for smaller vendors as memory prices spiral, leaving their businesses under immense strain. Data from Counterpoint Research tells a similar story, indicating Apple growth against a background of market decline. It’s important to put the impact of raised RAM costs into perspective. While Apple and Samsung make products at the kind of scale that enables them to cut better deals, smaller makers don’t have the same advantage, leaving them far more exposed to memory price driven pressures. Memory prices are crushing the low end And they really are exposed; not only are sales declining, but Omdia analyst Runar Bjorhovde notes that vendors at that end of the market are dealing with hugely destructive DRAM price hikes over just the past year — up to four or five times higher in some cases. That degree of increase is the kind of business-focused tsunami that drives people out of the market altogether and certainly leaves companies exposed to M&A activity. Right now, memory and storage can account for more than 60% of the product cost, Bjorhovde said. And as costs continue to increase, what profitability that does exist in the low-cost, high competition lower end smartphone space is being utterly mauled. Omdia forecasts a 22% decline in the sub-$400 smartphone segment as a result. “Samsung Electronics and Apple — the two market leaders — made huge market share gains…, whereas most players beyond went through steep volume declines,” Bjorhovde said. From volume to value Apple’s decision to expand its addressable market with the iPhone ‘e’ series just adds pressure, while Samsung’s enduring popularity helps make it difficult for smaller vendors to generate profit through market scale. “To adapt, vendors are shifting their strategies from volume to value by reoptimizing portfolios and adjusting retail pricing,” he said. “Although memory and storage costs are the biggest challenges for vendors, they are far from the only challenge,” Bjorhovde said. “New semiconductor bottlenecks, such as within foundries, are adding further cost pressures.” With the cost of manufacturing set to continue to rise, it’s generally accepted that we’ll see the average selling price of smartphones climb in the coming 12 months, with Apple set to lead the market toward higher cost builds with the new Pro and Ultra iPhones this September. Apple’s decision to hold smartphone prices so far has added another price pressure to low-end vendors; the longer it holds its prices down, the longer and more painful will smaller vendors hang onto their own low-price structure to compete. Future shock: AI hardware A further wild card is in Apple’s recent lawsuit against OpenAI , which accuses the ChatGPT maker of “illegal reliance on misappropriated trade secrets” in its hardware plans. OpenAI is thought to be planning an AI-driven iPhone competitor. We’ve heard speculation about these plans before, of course. But what seems to be emerging in the wake of Apple’s litigation are hints OpenAI intends to introduce its first AI hardware product at some point in 2027. Assuming that schedule remains on track, OpenAI will likely impose further component pricing pressure across the whole industry. After all, Apple’s customer loyalty leads the industry, and Samsung has built something similar. So, the companies with the most to lose to OpenAI will be the same set of smaller vendors who are already struggling with component price-driven market complexity. OpenAI products will demand the same memory, similar processors, manufacturing, and other components as other devices, prompting further pricing pressure. That’s likely to put some small vendors out of business entirely, even as standard smartphone prices increase. Fragmentation will be next Those outcomes won’t be universal, as the desire for sovereign data services and growing mistrust of US tech companies suggest OpenAI’s products might see limited adoption in most markets. But they could serve to accelerate divergence in smartphone purchasing patterns worldwide, while adding to market pressure. You can follow me on social media! Join me on BlueSky , LinkedIn , Mastodon , and subscribe to The Core .
Score: 52🌐 MovesJul 13, 2026https://www.computerworld.com/article/4196262/ai-is-killing-low-cost-smartphones.html - The Agentic Age Needs A Cognitive Operating Model
Last October, I published a blog proposing a different mental model for AI agents: Treat them as cognitive skills and products, not as digital employees. That framing has since resonated strongly with Forrester clients, particularly technology leaders building agentic capabilities inside the enterprise. But the concept of a cognitive skill in that blog was deliberately loose. […]
Score: 52🌐 MovesJul 13, 2026https://www.forrester.com/blogs/the-agentic-age-needs-a-cognitive-operating-model/ - Why Authentication Is Not Enough For Agents
Logging can tell you something happened. But none of that alone determines whether the action should be allowed, given the full chain of authority behind it.
Score: 52🌐 MovesJul 13, 2026https://www.forbes.com/councils/forbestechcouncil/2026/07/13/why-authentication-is-not-enough-for-agents/ - Singapore’s SimpleAI raises $15m funding for acquisition-led growth
Singapore’s SimpleAI raises $15m funding for acquisition-led growth DealStreetAsia
Score: 52💰 MoneyJul 13, 2026https://www.dealstreetasia.com/stories/singapores-simpleai-raises-15m-funding-for-acquisition-led-growth-488886 - AI is freeing up capital. Most companies have no plan for what comes next
AI tools today enable faster processes, leaner operations and lower costs, making efficiency wins the new baseline. However, for many businesses, the strategy stops at those first wins. This has created a growing leadership blind spot: Once you achieve AI ROI, how do you make the most of it? If there is no clear reinvestment strategy, AI gains burn out quickly and disappear into the business without meaningfully compounding their value. For CIOs, the next challenge is not just proving AI can make the business more efficient but deciding how those gains can build a stronger company and sustain growth over the long term. Start by investing in a crystal ball One of the smartest ways to reinvest AI gains is to improve how the business evaluates what is worth building in the first place. Leaders who chase “cool” use cases without defining the business impact or path to ROI upfront often end up with systems that drain funds without creating compounding returns. Instead, a clear reinvestment strategy uses AI to assess the strongest use cases before scaling up. AI tools today can help teams move from idea to prototype to impact analysis much faster than before. That makes it easier to identify which projects have a credible path to ROI and which ones can be filed away. Access to these quick insights allows businesses to test whether a use case has real value before committing larger engineering or model costs. This is especially crucial right now as AI is becoming more costly as businesses scale it . What looked inexpensive in early pilots can become far pricier once it is embedded in day-to-day work and as AI providers tokenize and meter its use. The more central AI becomes, the more intentional leaders need to be about where it is used, what it actually returns and how to reinvest those gains. Not every workflow belongs in the same model. Not every task needs an agent. As AI vendors mature and monetization models evolve, the businesses that will win will be the ones that make those distinctions early, reinvest accordingly and keep building ahead of customer needs rather than reacting to them. Not every workflow belongs in the same model. Not every task needs an agent. Cycle ROI gains back into tooling Once AI activations start to show dividends, it’s time to reinvest in stronger tooling. This should include new AI tools that continue to advance the business, as well as continued investment in what has already worked. That compounding effect is ultimately what separates businesses that sustain AI-driven growth from those that plateau after early wins. I’ve seen firsthand the benefits of investing in new tools that make AI more usable, repeatable and valuable in workflows. For example, automated product man agement to ols enable rapid prototyping and product rationalization. Decision intelligence platforms can help teams simulate scenarios. Customer behavior modeling tools can help predict churn and shift customer demand patterns. These advanced solutions can help teams move from an idea to a working concept in days instead of months. Smart reinvestment is about building the right technical mix for the outcomes the business needs , rather than funding more AI for its own sake. To maximize impact, start with tooling for governance and upskilling. 1. (Re)invest in governance As AI usage spreads and matures across teams, products and functions, a strategic policy framework becomes all the more vital. CIOs should work to reinforce the governance foundations already in place so they can support broader adoption, rather than rebuilding new policy from scratch each time AI usage expands. This means reinvesting in shared standards, oversight mechanisms and supporting roles that make governance more durable and practical over time. Without doubling down on governance, businesses risk creating siloed, disconnected pockets of experimentation. Those pockets quickly become expensive to monitor and difficult to secure, creating further risk to consistency, compliance and trust. The consequence is often wasted spend as experiments stall or overlap, or outcomes that are too fragmented to scale. When businesses keep governance investment at the center of their reinvestment strategy, it becomes a force multiplier. It reduces duplication across teams, creates more commonality across products and makes it easier to expand AI use without increasing fragmentation or risk. 2. Empower employees to grow Smart tools only create real value when people are equipped to use them well. That is why reinvestment should go beyond technology alone. As AI tools become more powerful and accurate, the skills barrier to building something useful is dropping. Employees can get much closer to a viable concept much faster with AI, but that only works if businesses create learning pathways, academies and practical enablement that help teams use these tools well. Smarter tooling can help product, operations and technology teams collaborate with fewer layers between idea and execution. As employees build new skills, they can stay closer to a single initiative from start to finish. That reduces handoffs, empowers employees to learn new skills and offers a more direct path from the original idea to the final result. Let AI ROI fund your fight against siloes Over the next few years, the businesses that pull ahead are not simply going to be the ones with the most AI pilots or the biggest efficiency gains. They will be the ones that invest AI ROI in bridging what has long been disconnected: systems, teams, workflows and ecosystems. In telecom, for example, AI is already creating savings inside billing operations and other back-office work tied to the BSS layer. The smart move for telcos is not to stop at those savings, but to reinvest them in connecting their BSS and OSS, where fragmentation and siloes have long slowed telcos down. Think about what that means in practice: instead of billing, service configuration and network operations functioning as separate systems with separate handoffs, AI can help orchestrate them. That makes it easier to move from order to activation to support with less internal friction, better visibility and fewer breakdowns between what was sold and what is actually delivered. For the customer, that means a broadband outage, plan change or installation appointment is handled as one connected journey rather than a chain of handoffs. The outcome is a more connected operating model that makes the customer experience feel far less complex. The same logic applies across industries. In banking, a customer with a mortgage, checking account and credit card at the same institution is often still treated as three separate relationships – because the underlying systems do not communicate. AI orchestration can change that, giving banks a unified view of the customer and employees the context to act on it. Not using AI to do the same work faster, but using AI dividends to build a business that works better. That is what smart investment looks like. ROI is just the start AI can absolutely free up capital. That, however, is only the first chapter. The bigger story is what leaders choose to do next: reinvest in better tooling, more consistent governance, smarter workforce enablement and operating models built to connect across silos. The payoff will be a more resilient, agile business ready for what’s next. This article is published as part of the Foundry Expert Contributor Network. Want to join?
- 9Yards X announces acquisition of Labib AI
The acquisition marks an important milestone in 9Yards X’s journey
Score: 51💰 MoneyJul 13, 2026https://www.zawya.com/en/business/m-a/9yards-x-announces-acquisition-of-labib-ai-lldi4l17 - AI’s Next Challenge Isn’t Models — It’s Managing Data at Scale
AI’s future depends on strong data foundations.
- Why Everyone in China Wants an AI Inference Chip
Restricted Nvidia access opened the market. The economics of serving AI are pushing chipmakers, cloud providers and model developers toward custom hardware.
- The AI effect: University of Chicago Law School opts to prohibit electronic devices in some classrooms.
The AI effect: University of Chicago Law School opts to prohibit electronic devices in some classrooms. Chicago Tribune
- Skilling vital in India's goal of becoming AI solutions capital
Speaking at the CII GCC Business Summit, Krishnan noted that the deployment of AI in enterprises is still lagging across the world, not just in India, presenting an opportunity for GCCs here to play a critical role.
- Forrester: Managing supply chain volatility with agentic AI
Supply chain management has induced headaches at enterprises struggling with geopolitical challenges, sustainability mandates, and the sheer volume and velocity of decisions they must take to win, serve and retain customers. While not yet realised in the wild, artificial intelligence (AI) agents offer the prospect of boosting supply chain resilience and sustainability. Most agentic deployments are still being established, but agents in the supply chain will help supply chain analysts scale their insights. These analysts monitor the balance between anticipated demand and expected supply by stock-keeping unit (SKU) and fulfilment location for each period in the planning horizon. Enterprises that offer more product options to serve long-tail customers, value propositions like direct to consumer, or products as a service risk overwhelming analysts, desperately rebalancing stock across proliferating SKU/location combinations – not to mention generating frequent scenario analyses for executives to assess risk. Enterprises that fail to seize the opportunity to deploy agents for scaling supply chain insights risk stockouts that fail customers and overstocks that fail shareholders. Agentic AI also helps to reduce the burden of mundane logistics tasks. Supply chain resilience depends on a combination of capacity or inventory buffers and sourcing and transportation options. But the exercise of options is often surprisingly labour-intensive. According to Logistics Management’s DispatchTrack benchmark survey, a typical dispatcher in an enterprise transportation office makes 120 to 200 calls in an eight-hour shift. We’ve all heard stories about the scramble for alternate carriers and routes during recent crises, such as the port congestion on the US West Coast or the Ever Given ship stuck in the Suez Canal. Fortunately, there are already live examples of agents finding and negotiating rates with carriers. Another benefit is that agentic AI can manage the avalanche of paperwork across the supply chain . The flow of documents should match the flow of goods in every supply chain: for example, purchase orders, purchase order acknowledgements, advanced shipping notices and bills of lading. There are also customer expectations about supply chain carbon footprint transparency, together with multi-tier supply chain visibility mandates, such as the EU’s Supply Chain Due Diligence Law . These add to the mountain of documents that supply chain professionals must parse and match to file the correct customs declarations, remit the correct tariffs, and authorise carrier or supplier invoices. Missing data elements or mismatched data inevitably lead to delays in customs clearance or invoice settlement, so agents that can reduce discrepancies are essential. For instance, global shipping giant Maersk uses AI agents to streamline documentation and supplier interactions, while Schneider Electric uses AI agents for document validation and sustainability tracking. Read more about supply chain management SAP introduces Autonomous Supply Chain Management : At SAP Sapphire 2026, SAP presented what it thinks autonomy in the supply chain actually looks like when translated into production systems. Top 8 KPIs for 3PL organisations : Supply chain leaders can use 3PL key performance indicators to evaluate vendor performance, manage costs and ensure logistics partners meet service-level and customer experience expectations. A foundation for agentic AI success Beyond these benefits, agentic AI offers the prospect of mitigating supply chain instability and managing supply chain complexity by automating some analysis and supplying imbalance remediation interventions. But to seize the opportunity, technology and innovation leaders must lay the policy and planning foundation for agentic AI success and focus on data preparation, protocols and standards for execution success. To set the foundation for their agentic AI journey, Forrester recommends that technology and innovation leaders estimate the business opportunity. Supply chains break down when the volume, velocity and complexity of decisions overwhelm decision-makers. Supply chain decision complexity depends on factors like the combination of SKUs and supply chain nodes, as well as the level of institutional and market uncertainty. Savvy technology and business leaders keep track of growth in SKU/fulfilment channel combinations and layers in the supply chain and regulations – such as supply chain traceability – carefully noting the potential or actual financial impact of rushed or poorly informed decisions. But technology leaders need to acknowledge the frustration of rules-based automation. Forrester notes that enterprises like Siemens have successfully invested in their own operations and those of their clients’ rules-based automation technologies – such as robotic process automation (RPA) – to boost supply chain performance. Traditional cyber security architectures were designed for organisations built around people – agentic AI disrupts this However, enterprise applications governance is adapting to accommodate the changing future of work. Forrester warns that rigid rules-based task automation can fossilise the status quo, jeopardising fluid adaptability to new business opportunities, such as selling through multiple new channels or the servitisation of assets or products. Forrester recommends establishing a framework for agent security and authorisation. Traditional cyber security architectures were designed for organisations built around people – agentic AI disrupts this. To deploy goal-oriented, ephemeral, scalable, dynamic agents, where unpredictable emergent behaviours are incentivised to accomplish objectives, it recommends enterprises adopt Forrester’s Aegis (Agentic AI Guardrails for Information Security) framework , which is designed to help chief information security officers (CISOs) secure, govern and manage AI agents and related infrastructure. Authorisation also applies to usage, which means enterprises will need to apply FinOps to agents. Forrester recommends that technology leaders develop a semantic model that embraces all supply chain processes and apps. Agentic systems require high-quality and consistent data to support precise decision-making and accurate actions. Enterprises investing in creating and maintaining a high-quality metadata layer, such as knowledge graphs , to help agents understand the data and business context in which they operate, are already seeing more success than those that lag. Building a complete semantic model that connects payments, enterprise resource planning, procurement and other areas of enterprise logistics management to partners in sales, product and customer support is essential for building next-gen, differentiated agentic applications. Trusting agentic decisions Explainability is another area technology leaders need to focus on. Trust is the primary challenge for AI agents, as most supply chain professionals bear the scars of project failures in forecasting and replenishment automation. AI-powered supply chain implementations have a 72% failure rate, so savvy technology and innovation leaders applying any technology to supply chain use cases must invest in explainability and compliance: for example, with regional AI regulations like the EU’s AI Act . Forrester urges technology leaders to exercise caution over proliferating agents in an agentic chain Overall, Forrester urges technology leaders to exercise caution over proliferating agents in an agentic chain. Technology and innovation professionals should consider factors like latency and performance in real-time or near-real-time applications; cloud pricing models that discourage long chains; error propagation, which amplifies ambiguity or error in agents; context window limitations that depend on token limits in large language models; and orchestration overhead. Wherever there are multiple agents in a chain, IT leaders must introduce tooling to verify agent outputs, ensuring the feasibility of results that pass to downstream agents. Forrester recommends that organisations establish human-in-the-loop and human-on-the-loop guidelines. This limits the responsiveness of complex supply chains to frequent shocks. However, autonomous agents always require human-in-the-loop and human-on-the-loop resolution for exceptions. For instance, companies such as Costco use supplier onboarding technology – from companies like Osapiens – to orchestrate agents retrieving data that’s vital to comply with regulations, such as the EU Supply Chain Act. But agents always route ambiguous cases to experts for resolution. Agentic systems behave unpredictably, and even competent artificial general intelligence (AGI) requires close supervision. Forrester urges IT leaders to govern decision boundaries between humans and AI, such as by deploying tools like Nvidia NeMo Guardrails. This article is based on Forrester’s Agentic AI will scale and accelerate your response to supply chain volatility report by Forrester vice-president and principal analyst George Lawrie .
Score: 50🌐 MovesJul 13, 2026https://www.computerweekly.com/feature/Forrester-Managing-supply-chain-volatility-with-agentic-AI - ChinAI #366: Most Companion Robots Die by Day 30
Greetings from a world where…
- AI memory explained: How smarter digital assistants reshape privacy debate
AI assistants are beginning to remember users' conversations, preferences and digital context. Here's how AI memory works, why companies are adopting it, and what it means for privacy
- MeitY launches NIDAR 2.0 to develop drones powered by Indian-made chips
The Ministry of Electronics and Information Technology (MeitY), in collaboration with the Drone Federation India (DFI), on Monday launched the second edition of the National Innovation Challenge for Drone Application and Research (NIDAR 2.0), challenging students to build autonomous drones and indigenous flight controllers powered by India's homegrown VEGA processor.
- Lawyer rebuked for misusing AI again in Roc Nation lawsuit
Lawyer rebuked for misusing AI again in Roc Nation lawsuit Reuters
Score: 50🌐 MovesJul 13, 2026https://www.reuters.com/legal/litigation/lawyer-rebuked-misusing-ai-again-roc-nation-lawsuit-2026-07-13/ - LG Electronics, GS E&C partner on AI homes
LG Electronics said Monday it has signed a memorandum of understanding with GS E&C to jointly develop next-generation artificial intelligence home solutions. Under the agreement, LG Electronics will integrate its AI home hub, ThinQ ON, with GS E&C's Xi apartment platform to build a more connected smart home ecosystem. The companies plan to connect home appliances, Internet of Things devices and residential services through a single platform. Residents will be able to control lighting, heating, v