Source Mon, 06 Jul 2026 01:24:31 GMT Read source

Palo Alto bought Portkey, Solo.io gave agentgateway to the Linux Foundation. Agent gateways are consolidating into a category. A CXO read on MCP governance and cost.

A new product category, the "agent gateway," is rapidly emerging in the AI stack, providing a crucial layer between AI agents and the models/tools they access. Companies like Nutanix, Arcade, and Manufact are launching solutions to centralize control over agent traffic. These gateways address growing concerns about ungoverned AI agents directly interacting with production systems, offering vital governance, security, cost management, and observability. They route requests, apply authentication, manage tool permissions, and log activity. The market sees diverse approaches from infrastructure, authorization, and security vendors, alongside consolidation through acquisitions and open-source initiatives. Enterprises are advised to carefully evaluate these solutions based on ownership, cost, and enforcement, as the industry seeks to standardize this critical layer for AI agent deployment.

In the space of a week, two more vendors planted a flag in a part of the AI stack that had no name a year ago. On July 3, Arcade made its agent authorization and tool-execution runtime available through the Microsoft Azure and AWS marketplaces , so enterprises can deploy it inside their own cloud with one click. A day earlier, Manufact opened its MCP hosting cloud to take a Model Context Protocol server from a GitHub push to a monitored production endpoint. Both arrivals point to the same conclusion. The layer that sits between an agent and everything it touches is turning into a product category of its own.

Nutanix gave that category a clear shape in late May. It shipped the Nutanix Agent Gateway as a generally available part of Nutanix Enterprise AI 2.7. The gateway is a centralized control point that manages traffic from agents to large language models and from agents to the business tools they call. For a decision-maker watching agent pilots multiply across departments, this is where cost, access and audit either get governed or get out of hand.

Source Tue, 07 Jul 2026 13:00:00 GMT Read source

Majority report AI-related security incidents or vulnerabilities

Majority report AI-related security incidents or vulnerabilities

The majority of companies that deploy AI systems end up shooting themselves in the foot with security, according to DigiCert.

Seventy-eight percent of enterprises report "experiencing AI-related security incidents or identifying AI-related vulnerabilities," the digital identity biz said in a commissioned survey.

Source Sun, 05 Jul 2026 15:59:07 GMT Read source

Alex Karp, frontier models and the real fight for Enterprise AI - SiliconANGLE

Palantir Technologies Inc. Chief Executive Alex Karp’s recent broadside against the frontier model vendors put a knife to the throat of the central enterprise artificial intelligence debate.

Karp’s argument is that frontier model vendors (he didn’t mention Anthropic and OpenAI by name) intend to suck the knowledge out of enterprises and destroy the “alpha” companies enjoy through their proprietary data, processes and underlying business advantage. In our last Breaking Analysis we called this approach “data communism,” where every firm gains access to the same intelligence.

Our counter to data communism is data capitalism, where proprietary advantage remains exclusive to an organization and its broader ecosystem. The familiar graphic below describes how we see the AI software stack evolving. The most important pieces of this stack in our view are the System of Intelligence or SoI and the System of Engagement, the new user/client surface. We believe competitive advantage accrues to firms that can make these two puzzle pieces interact and learn from the reasoning traces of humans. Critical is how they capture tacit enterprise knowledge to take governed and trusted actions both with and without humans.

Source Tue, 07 Jul 2026 13:02:11 GMT Read source

Collaboration pairs Cognizant's Frontier Certified Engineers, who deploy and scale AI in client environments, with a rollout of Gemini Enterprise and Google Workspace across Cognizant TEANECK,...

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Collaboration pairs Cognizant's Frontier Certified Engineers, who deploy and scale AI in client environments, with a rollout of Gemini Enterprise and Google Workspace across Cognizant

TEANECK, N.J. , July 7, 2026 / PRNewswire / -- Cognizant (Nasdaq: CTSH) announced a significant expansion of its partnership with Google Cloud, broadening how the companies bring Gemini Enterprise to clients and deepening Cognizant's own internal use of the technology.

Source Tue, 07 Jul 2026 16:25:51 GMT Read source

Content access, governance, and platform flexibility are emerging as the dividing lines between AI leaders and laggards, according to the new State of AI in the enterprise report from Box, which surveyed 1,640 IT decision makers across the US, UK, France, and Japan.

Content access, governance, and platform flexibility are emerging as the dividing lines between AI leaders and laggards, according to the new State of AI in the enterprise report from Box, which surveyed 1,640 IT decision makers across the US, UK, France, and Japan. One of the report's major findings is the speed of the shift: the combined share of organizations describing themselves as advanced or leading edge soared from 8% to 64% just over the past year, while the share calling themselves early stage or not yet started collapsed from 53% to just 9%. Eighty percent of organizations reported a notable return on their AI investment, defined in the survey as an improvement of at least 10%, and more than half saw measurable business impact within six months of getting a project approved.

The swing is largely due to how enterprises are now organizing their AI use rather than to any single technical breakthrough, says Olivia Nottebohm, COO of Box.

"We've moved from standalone experimentation that lived at the individual level into systematized, integrated agentic operations, agents that are in production and can be used in a repeatable manner," Nottebohm says. "That's where the impact is coming from."

Source Tue, 07 Jul 2026 19:26:00 GMT Read source

/PRNewswire/ -- Keeper Security, the leading zero-trust and zero-knowledge identity security and Privileged Access Management (PAM) platform, today announces...

For the first time, AI agents on employee workstations and endpoints can be discovered and governed with access policies and elevation controls

CHICAGO , July 7, 2026 /PRNewswire/ -- Keeper Security , the leading zero-trust and zero-knowledge identity security and Privileged Access Management (PAM) platform, today announces agentic AI governance for Keeper Endpoint Privilege Manager, which launched earlier this year. The feature extends policy enforcement to AI agents and establishes Keeper as the governance layer for both human and non-human identities across employee workstations and enterprise endpoints. Keeper Endpoint Privilege Manager delivers agentic AI security at the endpoint, governing every agent action as it happens regardless of whether the agent uses Model Context Protocol (MCP), a direct API, local tool or any other path. Competing approaches govern only at the MCP layer, with all non-MCP actions that agents take falling outside of security policy.

Gartner predicts that by 2028, an average global Fortune 500 enterprise will have more than 150,000 AI agents in use, up from fewer than 15 in 2025. Yet according to IBM's 2025 Cost of a Data Breach report, 63% of organizations lack AI governance policies entirely, and among those that experienced an AI-related breach, 97% lacked proper AI access controls. The governance infrastructure has not kept pace with adoption.

Source Thu, 25 Jun 2026 07:00:00 GMT Read source

James Denford, Gregory Dawson, and Kevin C. Desouza analyze the governance models for federal AI under the Biden and Trump administrations.

Artificial Intelligence Technology Policy & Regulation

Global artificial intelligence (AI) spending is forecasted to reach $2.5 trillion in 2026, according to one estimate , marking a 44% increase year-over-year. In 2027, spending is expected to reach $3.3 trillion, reflecting another 32% increase year-over-year. The majority of this money has funded AI infrastructure, followed by AI services and AI software (representing about 54%, 23%, and 18% of spending, respectively, for 2026).

As discussed in our most recent Brookings report , federal AI spending in the U.S. is also rapidly increasing and at a rate faster than the rest of the world. Our research showed that the value of funds obligated increased by 966% between 2024 and 2026 (from $355 million to $7.2 billion), and the value of potential award increased by 1,912% for the same period (from $4.6 billion to $91.8 billion).

Source Thu, 02 Jul 2026 22:43:24 GMT Read source

Expert from the Georgia RAM consultant team examines how the country can translate AI readiness into action through a phased approach to governance and regulation.

Global AI Ethics and Governance Observatory

Global AI Ethics and Governance Observatory

Georgia’s implementation of UNESCO’s AI Readiness Assessment Methodology (RAM) offered a comprehensive overview of country’s AI governance landscape, identifying existing foundations, emerging opportunities, and areas where further development is needed to enable responsible AI adoption.

Source Tue, 07 Jul 2026 17:43:34 GMT Read source

Illinois is set to become the first state to impose sweeping new regulations on frontier AI development, with the Artificial Intelligence Safety Measures Act (SB 315) passing, which is an imminent shi…

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Illinois is set to become the first state to impose sweeping new regulations on frontier AI development, with the Artificial Intelligence Safety Measures Act (SB 315) passing, which is an imminent shift that will reshape industry standards for transparency, safety, and accountability.

Source Wed, 08 Jul 2026 02:46:46 GMT Read source

In a 6-month randomized trial, we evaluated a digitally enabled “human-in-the-loop” care support model using a predictive artificial intelligence (AI) digital twin to provide personalized daily short message service (SMS) feedback for adults with type 2 diabetes (T2D). The parent study enrolled 40 adults aged ≥18 years with T2D who completed 3 months of baseline observation followed by a 3-month intervention period, generating 6467 longitudinal data points across weight, dietary intake, physical activity, and glucose monitoring (mean follow-up: 174 days). For this ancillary AI intervention, a subset of 19 participants was randomized to receive either AI-generated individualized daily feedback (AI group, n = 10) or no daily feedback (control group, n = 9). The online human-in-the-loop predictive control model incorporated a transfer-learning artificial neural network predictive digital twin trained on participant self-monitoring data, including weight, food logs, physical activity, and glucose values. A particle swarm optimization controller identified personalized behavioral recommendations aligned with glucose and weight goals, and the digital twin was retrained weekly using newly accrued data. The model achieved ≥80% prediction accuracy across all diet-condition subgroups. During the intervention period, participants receiving AI-generated feedback demonstrated trends toward increased daily step counts and improved adherence to caloric and carbohydrate intake targets. The AI intervention group achieved significantly greater weight loss than controls (mean loss 5.87 lbs vs 3.57 lbs; p < 0.012) while maintaining stable glucose levels throughout the study period (p = 0.661). These findings suggest that AI-enabled predictive digital twin models may offer a scalable approach for extending precision diabetes self-management support beyond clinic visits.

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npj Health Systems has APC waivers available that can be allocated upon acceptance on an ad-hoc basis. For additional information, contact the Journal Publisher, Tony Chen .

npj Health Systems volume 3 , Article number: 59 ( 2026 ) Cite this article

Source Mon, 06 Jul 2026 07:30:00 GMT Read source

/PRNewswire/ - Corinex Corp. and Plexigrid S.L. have signed a strategic cooperation agreement to market Corinex Plexigrid Intelligence, a platform for...

VANCOUVER, BC and GIJÓN, Spain , July 6, 2026 /PRNewswire/ - Corinex Corp. and Plexigrid S.L. have signed a strategic cooperation agreement to market Corinex Plexigrid Intelligence, a platform for low-voltage and medium-voltage power grids, built on the most accurate and granular power data.

As power-hungry AI unfolds, the electrification of industry, transport and heating/cooling accelerates, and the penetration of distributed energy resources explode, grid operators are facing the largest technological challenge in decades: planning, operating and orchestrating in real-time a distributed, intermittent and bidirectional electricity system with millions of DERs. Successfully solving this requires the next level of real time visibility, intelligence and control through their mid and low voltage sections of the grid. This strategic cooperation is aimed at delivering exactly that.

Corinex products observe and act on the physical grid, while Plexigrid software models and optimizes it. The partnership brings these complementary capabilities together, connecting real-time field intelligence with digital twin analysis, capacity decisions and flexibility actions.

Source Mon, 06 Jul 2026 12:00:00 GMT Read source

Artificial intelligence (AI) and digital twin technology are increasingly moving from promising concepts to practical engines of industrial transformation.

Artificial intelligence (AI) and digital twin technology are increasingly moving from promising concepts to practical engines of industrial transformation. ARC Advisory Group’s recent research points to a clear trend: industrial AI is accelerating the digital twin software market by improving engineering simulation, product design, asset management, and decision making across the asset lifecycle. This convergence is especially important for manufacturers, infrastructure operators, energy companies, and asset-intensive industries that need to improve uptime, reduce costs, optimize energy use, and respond faster to operational change.

A digital twin is more than a static model. It is a living, data-connected representation of a physical asset, process, plant, product, or system. ARC Advisory Group describes digital twins as tools that can simulate, predict behavior, and optimize products, field assets, infrastructure, plants, and production systems across both process and discrete manufacturing. AI strengthens this value proposition by making the twin more adaptive, predictive, and actionable.

In traditional simulation environments, models are often built for specific engineering or design tasks. When AI is added, digital twins can learn from operational data, detect anomalies, recommend actions, and continuously refine their understanding of asset or process behavior. This turns the digital twin from a visualization or simulation layer into a decision-support system.

Source Wed, 08 Jul 2026 03:58:36 GMT Read source

VAIV Company has unveiled an ontology automation solution designed to automatically build

VAIV Company has unveiled an ontology automation solution designed to automatically build ontology-based knowledge graphs from enterprise documents and deliver evidence-backed AI responses. The solution will be integrated into the company's VAIV Ontology RAG Platform.

Ontology technology structures data around concepts and their relationships, helping reduce hallucinations in generative AI. Most enterprise knowledge assets, including product terms and conditions and user manuals, exist as unstructured documents. Converting those documents into ontologies has traditionally relied on domain experts, making the process both time-consuming and costly while offering limited visibility into the underlying design process.

VAIV Company said the new solution makes the ontology development process transparent and provides an intuitive workflow that enables business users with domain expertise to participate directly. Once documents are uploaded, AI automatically proposes an initial ontology schema, which users can immediately revise and finalize through a conversational text interface. The company said the approach significantly reduces reliance on specialists during the initial data modeling stage.

Source Tue, 24 Mar 2026 07:00:00 GMT Read source

What are context graphs, what are they good for, and why are they dubbed AI’s trillion-dollar opportunity? What does context mean, and how can it be defined?

Got Tech, Data, AI and Media, and not afraid to use them.

Got Tech, Data, AI and Media, and not afraid to use them.

Got Tech, Data, AI and Media, and not afraid to use them.

Source Mon, 25 May 2026 07:00:00 GMT Read source

Discover how to integrate ontologies in Snowflake using Cortex Agents. Learn how Knowledge Graphs and GraphRAG improve AI accuracy and reasoning.

Snowflake is investing in making it easier for AI agents to reason over business concepts and relationships natively. This blog shows what's possible today for teams with existing ontologies. Many industries maintain formal ontologies that provide an additional layer of domain-specific reasoning which can add to semantic reasoning captured over tables, columns and joins. This can help AI agents reason over hierarchy, synonymy and domain-specific concepts that a semantic layer alone may not fully capture.

Using a highly simplified biomedical data set, we compared a baseline semantic-view Cortex Agent with ontology-aware approaches built on knowledge graphs, GraphRAG and targeted terminology mappings. The results in this benchmark suggest that improved structural grounding may improve accuracy and reliability under the evaluated conditions, while also offering a practical blueprint for teams building enterprise AI agents that need to be more precise, explainable and trustworthy.

Enterprise data is full of meaning that never appears explicitly in a schema — inherent domain knowledge that must be captured to power reliable agentic systems.

Source Tue, 07 Jul 2026 17:47:11 GMT Read source

From automated scaffolding planning to smart glasses and robot dogs, new AI-powered tools aim to accelerate construction site workflows and relieve the burden on skilled workers.

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From automated scaffolding planning to smart glasses and robot dogs, new AI-powered tools aim to accelerate construction site workflows and relieve the burden on skilled workers.

Artificial intelligence is beginning to transform one of Europe's least digitalized industries: construction. From AI-powered scaffolding planning to smart glasses and autonomous construction-site monitoring, startups are developing new tools aimed at improving productivity, reducing costs and tackling labor shortages in the construction sector.

Source Tue, 07 Jul 2026 15:43:49 GMT Read source

Agave has raised a $15 million Series A financing led by Accel to accelerate the growth of its AI platform... Read More

Agave has raised a $15 million Series A financing led by Accel to accelerate the growth of its AI platform for construction financial management, expanding a business that has grown rapidly while remaining profitable. Existing investor Y Combinator also participated in the round, bringing the company’s total funding to more than $20 million since its founding in late 2021.

The new capital will be used to expand Agave’s team and scale its portfolio of AI-powered products that automate accounting, financial reporting and back-office workflows for construction companies. Rather than replacing existing enterprise software, the company’s platform integrates with contractors’ current accounting and project management systems to streamline financial operations and improve productivity.

Founded by Tom Reno, John Zucchi and Pooria Azimi , Agave serves more than 500 general and specialty contractors across the United States and Canada, ranging from companies generating $5 million in annual revenue to firms exceeding $5 billion. Its customer base includes commercial, civil and residential builders, as well as contractors specializing in electrical, roofing and concrete work.

Source Mon, 06 Jul 2026 10:39:02 GMT Read source

Artificial intelligence may be reshaping industries across the Canadian economy, but the nation’s construction sector is still in the early stages of its AI journey, a number of reports conclude. Despite the promise, construction continues to lag behind

Click here to see Canada's most comprehensive listing of projects in conceptual and planning stages

Click here to see Canada's most comprehensive listing of projects in conceptual and planning stages

Artificial intelligence may be reshaping industries across the Canadian economy, but the nation’s construction sector is still in the early stages of its AI journey, a number of reports conclude.

Source Tue, 07 Jul 2026 13:00:00 GMT Read source

AI and predictive analytics help insurance companies prevent claims and manage complex global risks, writes Joaquin Barreiro.

Insurance companies have traditionally been in the business of paying claims. Increasingly, however, they are moving into the business of preventing them. The accelerated digitalization of operations, the rise of cyber threats, disruptions in global supply chains, connected mobility, and the increasingly visible effects of climate change are creating risks that are more complex, interconnected, and difficult to anticipate.

In this context, artificial intelligence and advanced data analytics are redefining how organizations identify, assess, and manage risk. The conversation is no longer focused solely on obtaining adequate insurance coverage, but rather on the ability to detect early warning signals that allow companies to act before a threat becomes a financial, operational, or reputational loss.

The insurance industry is uniquely positioned to drive this transformation. Every claim filed, policy renewed, vehicle accident reported, medical consultation covered, or property loss assessed generates valuable information about customer behavior, emerging risks, and patterns of exposure. For decades, much of this data remained fragmented across legacy systems, limiting its potential to create value beyond underwriting and claims management.

Source Tue, 07 Jul 2026 18:26:53 GMT Read source

AI tools work best when you give them assignments instead of asking them dumb questions. How to make this work in your practice.

ATLANTIC CITY, N.J. - A benefits broker can become an “AI whisperer” by giving artificial intelligence tools assignments instead of asking them dumb questions.

Reid Rasmussen, founder and CEO of freshbenies, described how brokers can improve their AI skills during the National Association of Benefits and Insurance Professionals annual convention.

Too many brokers ask simple questions of ChatGPT and other AI tools, only to become disappointed when these tools don’t provide brokers with the “magic” they expected, he said.

Source Mon, 29 Jun 2026 13:00:29 GMT Read source

According to Finextra, the next stage of AI adoption is shifting toward risk automation, with a greater emphasis on underwriting and

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Source Mon, 29 Jun 2026 13:41:13 GMT Read source

What's really happening with artificial intelligence in transportation, warehousing and logistics? Jim Lee, principal with the ZS consultancy, helps us to separate hype from reality.

What's really happening with artificial intelligence in transportation, warehousing and logistics? Jim Lee, principal with the ZS consultancy, helps us to separate hype from reality.

Transportation, warehousing and logistics companies today are expressing multiple concerns that could potentially be addressed by AI, Lee says. Top ones include labor and transportation volatility, along with siloed execution as an “honorable mention.” “That hasn’t been effectively addressed,” he says.

How AI should be applied depends on the type of work involved. When it comes to labor, the technology can take over certain “menial” and repetitive tasks, but other responsibilities are better left to humans, Lee says.

Source Mon, 06 Jul 2026 23:45:16 GMT Read source

Ambi Robotics and Pickle Robot Company have integrated their AI-powered robotic systems to automate one of the most labor-intensive parts of warehouse operations, creating an end-to-end inbound log…

Ambi Robotics and Pickle Robot Company have integrated their AI-powered robotic systems to automate one of the most labor-intensive parts of warehouse operations, creating an end-to-end inbound logistics solution that handles everything from trailer unloading to pallet stacking.

Developed in response to demand from Fortune 500 retailers and logistics providers, the combined system links Pickle Robot’s automated trailer-unloading technology with Ambi Robotics’ AmbiStack robotic palletizing platform, enabling a continuous flow of packages through warehouse receiving operations with minimal human intervention.

The companies say the integrated solution works with existing warehouse infrastructure, allowing operators to automate inbound processes without major facility redesigns.

Source Wed, 01 Apr 2026 07:00:00 GMT Read source

Explore the different ways you can use artificial intelligence (AI) in logistics and what careers you can pursue in this field. Learn about real-world examples of AI applications in logistics and how you can get started.

Explore the different ways you can use artificial intelligence (AI) in logistics and what careers you can pursue in this field. Learn about real-world examples of AI applications in logistics and how you can get started.

AI in logistics involves analyzing vast amounts of data to optimize operations and reduce inefficiencies.

AI technologies can unlock roughly $190 billion in economic value through logistics optimization [ 1 ].

Source Tue, 07 Jul 2026 21:05:51 GMT Read source

Registration is now open for the 2026 Fleet Forward Conference, where IIHS President David Harkey will discuss the organization's expanding commercial vehicle safety research alongside education on...

Registration is now open for the 2026 Fleet Forward Conference, where IIHS President David Harkey will discuss the organization's expanding commercial vehicle safety research alongside education on AI, regulation, and fleet technology.

Registration is now open for the 2026 Fleet Forward Conference. Insurance Institute for Highway Safety (IIHS) President David Harkey will share the organization's latest work as one of the event's keynote speakers, highlighting its expansion of research into commercial vehicle safety.

Registration is now open for the 2026 Fleet Forward Conference (FFC), taking place Oct. 20-22 at the Gaylord National Harbor in Maryland, just outside Washington, D.C.

Source Tue, 07 Jul 2026 11:30:06 GMT Read source

Targa Telematics, an AIoT and connected mobility technology provider, has launched an agentic AI-powered maintenance platform designed to automate fleet operations and improve vehicle availability. The company’s new Maintenance Excellence solution uses agentic AI to transform fleet maintenance from a series of disconnected tasks into a coordinated, data-driven process. The platform combines information from telematics […]

Targa Telematics , an AIoT and connected mobility technology provider, has launched an agentic AI-powered maintenance platform designed to automate fleet operations and improve vehicle availability.

The company’s new Maintenance Excellence solution uses agentic AI to transform fleet maintenance from a series of disconnected tasks into a coordinated, data-driven process. The platform combines information from telematics devices, vehicle manufacturers’ systems and external platforms to create a single view of vehicle health and maintenance activity.

Maintenance Excellence monitors vehicle performance, early signs of wear and potential issues before they develop into larger operational problems. The system can also schedule maintenance activities, coordinate stakeholders and manage approvals, helping fleet operators cut manual processes across the maintenance lifecycle.

Source Tue, 07 Jul 2026 13:29:00 GMT Read source

Wialon ChatGPT App lets fleets query account data in ChatGPT for fleet status, trips, fuel use, notifications, and quick analytics.

Wialon launched the Wialon ChatGPT App to let fleet managers, dispatchers, and executives access Wialon account data through natural-language conversation inside ChatGPT.

The app, now available in the ChatGPT App Marketplace, allows users to ask operational questions instead of navigating menus or building reports. Wialon said the app can return structured answers, summaries, maps, and insights covering fleet status, trips, mileage, fuel consumption, notifications, and quick analytics.

The goal is to give different fleet roles faster access to the information they need for daily decisions. A dispatcher could ask which vehicles are currently at the depot, while a fleet manager could ask what needs attention that day. Executives could use the app to pull a fuel efficiency summary or broader performance overview.

Source Wed, 08 Jul 2026 04:00:00 GMT Read source

/PRNewswire/ -- Bounteous, an AI services firm, has been named among ET Edge's Most Innovative Organisations 2026 in the "Innovation in AI-Led Enterprise...

Award recognizes the company's innovation in delivering enterprise AI solutions through proprietary AI platform Bounteous Arc™

BENGALURU, India , July 8, 2026 /PRNewswire/ -- Bounteous, an AI services firm, has been named among ET Edge's Most Innovative Organisations 2026 in the "Innovation in AI-Led Enterprise Modernization" category. The recognition reflects the company's commitment to helping enterprises achieve AI-led outcomes at scale.

The ET Edge Most Innovative Organisations platform is an initiative of The Times Group, themed "Redefining Excellence Through Innovation, Impact & Transformation." It spotlights enterprises that go beyond incremental change to transform products, processes, and business models. The platform celebrates organizations shaping the future of business and society across areas including AI, deep tech, sustainability, and customer experience.

Source Tue, 07 Jul 2026 14:00:00 GMT Read source

/PRNewswire/ -- As organizations accelerate their investments in artificial intelligence, agentic AI, and autonomous workflows, many are discovering that...

New practice helps organizations move from AI pilots to scaled adoption by aligning people, workflows, governance, and technology.

NAPERVILLE, Ill. , July 7, 2026 /PRNewswire/ -- As organizations accelerate their investments in artificial intelligence, agentic AI, and autonomous workflows, many are discovering that technology deployment is only part of the challenge. Real value depends on redesigning how work gets done, helping teams adopt new AI-enabled ways of working, and measuring impact across the enterprise. To help organizations navigate this shift, Egen today announced the launch of its Agentic Change Enablement Practice.

Egen, a Google Cloud Premier Partner, guides organizations through workflow orchestration, data and platform integration, agent engineering, and change enablement to create a clear path from strategic AI transformation to value. The addition of this practice deepens Egen's alignment with Google Cloud's focus on helping enterprises use agents to transform work and accelerate value.

Source Mon, 06 Jul 2026 09:10:00 GMT Read source

Realizing returns on AI adoption requires strategic investments and organizational change, two new reports found.

Companies have spent the past two years racing to deploy chatbots, coding assistants, and AI agents to their workers. Two new reports, however, suggest that deploying AI tools is the easy part.

Ramp, a financial technology company, and Revelio Labs, a workforce intelligence platform, studied company behavior across nearly 22,000 US firms. They found that companies making sustained, high-intensity AI investments saw greater workforce gains than firms using AI more lightly.

The report defined "high-intensity adopters" as those who spent an average of about $34 a month on AI, compared to those who spent an average of less than $3.

Source Tue, 07 Jul 2026 10:02:50 GMT Read source

As AI quietly takes over thousands of operational decisions, Ensono's Chief AI Officer Jim Piazza tells People Matters why governance, transparency and human accountability will define the next phase of enterprise AI adoption.

As AI quietly takes over thousands of operational decisions, Ensono's Chief AI Officer Jim Piazza tells People Matters why governance, transparency and human accountability will define the next phase of enterprise AI adoption.

Artificial intelligence has become remarkably good at making decisions. The bigger question is whether anyone can still explain them.

Across modern enterprises, AI is already prioritising IT incidents, recommending remediation paths, flagging suspicious transactions, reshuffling customer workflows and deciding where scarce computing resources should go. Most of these decisions happen behind the scenes. Individually, they appear routine. Collectively, they are reshaping how organisations operate.