The artificial intelligence boom is entering a new phase. Over the past two years, most people have become familiar with AI tools that answer questions, generate images or help write emails. But technology companies are increasingly focused on something more ambitious: AI systems that can take actions on behalf of users.<h2>The concept is known as Agentic AI</h2>Many industry leaders now believe this shift could transform how people use software, work online and interact with technology. The reason it is attracting attention is simple: AI is moving from helping people complete tasks to potentially completing some of those tasks itself.<h2>What exactly is Agentic AI?</h2>Traditional AI systems respond to prompts. A user asks a question, requests a summary or uploads a file, and the system generates an answer. Agentic AI goes a step further. Instead of simply responding, AI agents can break down goals into smaller tasks, make decisions, use digital tools and work through multiple steps to achieve an objective.For example, rather than helping someone plan a holiday, an AI agent could potentially compare prices, organise an itinerary, book reservations and make adjustments if plans change.In simple terms, it is the difference between receiving advice and having a digital assistant carry out the work.<h2>Why tech companies are investing heavily</h2>The biggest names in technology are already moving in this direction. OpenAI, Google, Microsoft, Anthropic and Meta have all discussed or demonstrated AI systems capable of handling increasingly complex workflows. Industry executives frequently describe AI agents as one of the most important developments in artificial intelligence since the arrival of large language models. The potential economic impact is also significant. Businesses see AI agents as a way to automate repetitive tasks, improve productivity and allow employees to focus on higher-value work. From customer support and software development to research and administration, many sectors are experimenting with early versions of AI agents.<h2>Why experts say the shift is happening faster than expected</h2>A year ago, many experts believed advanced AI agents were still years away. Today, the conversation has changed. Recent advances in reasoning models, memory systems and tool use have allowed AI systems to complete increasingly sophisticated tasks. Instead of handling a single instruction, some AI models can now manage long workflows involving multiple decisions and actions. That progress has led many technology leaders to argue that AI agents may arrive sooner and have a greater impact than previously expected. The rapid pace of investment also reflects growing confidence that the technology is becoming commercially useful rather than remaining a research project.<h2>The opportunities and concerns</h2>Supporters argue that Agentic AI could make software far more useful. Businesses could automate routine processes. Consumers could spend less time on repetitive digital tasks. Researchers could analyse information more quickly. Developers could accelerate software creation.At the same time, concerns remain. The more autonomy AI systems receive, the more important reliability, security and oversight become. Questions around accountability, data privacy and workplace disruption continue to be debated by governments, researchers and technology companies. The challenge for the industry is finding the right balance between capability and control.<h2>A glimpse of the next internet era</h2>The rise of Agentic AI may represent a larger shift than many people realise. For decades, software has largely required users to navigate menus, click buttons and manage workflows themselves.AI agents could gradually change that model.Instead of telling software exactly what to do, people may increasingly describe a goal and allow AI systems to determine how to achieve it. Whether that future arrives in months or years remains uncertain. What is becoming increasingly clear, however, is that the conversation in the technology industry has already moved beyond chatbots. The focus is now shifting towards AI systems that can act, adapt and solve problems with greater independence.

The AI industry is rapidly moving towards Agentic AI, a new generation of systems designed to complete tasks rather than simply answer questions. Technology leaders believe AI agents could reshape software, work and productivity faster than many expected.

The artificial intelligence boom is entering a new phase. Over the past two years, most people have become familiar with AI tools that answer questions, generate images or help write emails. But technology companies are increasingly focused on something more ambitious: AI systems that can take actions on behalf of users. The concept is known as Agentic AI Many industry leaders now believe this shift could transform how people use software, work online and interact with technology. The reason it is attracting attention is simple: AI is moving from helping people complete tasks to potentially completing some of those tasks itself. What exactly is Agentic AI? Traditional AI systems respond to prompts. A user asks a question, requests a summary or uploads a file, and the system generates an answer. Agentic AI goes a step further. Instead of simply responding, AI agents can break down goals into smaller tasks, make decisions, use digital tools and work through multiple steps to achieve an objective. For example, rather than helping someone plan a holiday, an AI agent could potentially compare prices, organise an itinerary, book reservations and make adjustments if plans change. In simple terms, it is the difference between receiving advice and having a digital assistant carry out the work. Why tech companies are investing heavily The biggest names in technology are already moving in this direction. OpenAI, Google, Microsoft, Anthropic and Meta have all discussed or demonstrated AI systems capable of handling increasingly complex workflows. Industry executives frequently describe AI agents as one of the most important developments in artificial intelligence since the arrival of large language models. The potential economic impact is also significant. Businesses see AI agents as a way to automate repetitive tasks, improve productivity and allow employees to focus on higher-value work. From customer support and software development to research and administration, many sectors are experimenting with early versions of AI agents. Why experts say the shift is happening faster than expected A year ago, many experts believed advanced AI agents were still years away. Today, the conversation has changed. Recent advances in reasoning models, memory systems and tool use have allowed AI systems to complete increasingly sophisticated tasks. Instead of handling a single instruction, some AI models can now manage long workflows involving multiple decisions and actions. That progress has led many technology leaders to argue that AI agents may arrive sooner and have a greater impact than previously expected. The rapid pace of investment also reflects growing confidence that the technology is becoming commercially useful rather than remaining a research project. The opportunities and concerns Supporters argue that Agentic AI could make software far more useful. Businesses could automate routine processes. Consumers could spend less time on repetitive digital tasks. Researchers could analyse information more quickly. Developers could accelerate software creation. At the same time, concerns remain. The more autonomy AI systems receive, the more important reliability, security and oversight become. Questions around accountability, data privacy and workplace disruption continue to be debated by governments, researchers and technology companies. The challenge for the industry is finding the right balance between capability and control. A glimpse of the next internet era The rise of Agentic AI may represent a larger shift than many people realise. For decades, software has largely required users to navigate menus, click buttons and manage workflows themselves. AI agents could gradually change that model. Instead of telling software exactly what to do, people may increasingly describe a goal and allow AI systems to determine how to achieve it. Whether that future arrives in months or years remains uncertain. What is becoming increasingly clear, however, is that the conversation in the technology industry has already moved beyond chatbots. The focus is now shifting towards AI systems that can act, adapt and solve problems with greater independence.

The AI industry is rapidly moving towards Agentic AI, a new generation of systems designed to complete tasks rather than simply answer questions. Technology leaders believe AI agents could reshape software, work and productivity faster than many expected.

It's happening faster than expected: How Agentic AI is reshaping the tech industry

The global economy is entering a transformative phase from generative AI (which creates content) to Agentic AI (systems that can plan, decide, and act autonomously to achieve goals). The evolution represents a move from "copilots" that assist humans to "agents" that execute end-to-end workflows with minimal supervision. The Agentic AI act as intent-based, unlike traditional automation, which follows rigid "if-then" rules. When the task is assigned, it breaks down into sub-tasks and acts on behalf of individuals, interacting with other agents representing sellers, logistics providers, payment processors and several other stuff as per the respective industry.<h3>The rise of agentic AI in the commerce industry</h3>During the 2024 holiday shopping season, data from Adobe highlighted a sharp rise in the use of AI-powered browsers and digital services. By Black Friday 2025, AI-generated traffic to US retail websites had surged by 805 per cent compared to the previous year, with AI agents contributing to more than $22 billion in global online sales. However, the impact of this shift goes well beyond retail. The global AI agents market, estimated at $5.4 billion in 2024, is expected to soar to $236 billion by 2034, reflecting the rapid integration of AI agents into critical enterprise operations across industries, according to a report by the World Economic Forum.<h3>How AI is reshaping work and governance</h3>As we advance in the world of Artificial intelligence, it is reshaping the entire structure of daily workflows by creating plans, deciding among multiple roles, and acting on tasks autonomously to achieve goals. The impact of agentic AI depends largely on the conditions of leadership rather then the technology itself. The future of AI has become more common across industries that will depend highly on leaders who can integrate these tools responsibly because the generative tools support everything from writing and research to early-stage problem-solving. Alongside it, advanced analytics also help organisations forecast demand and manage risks while discovering patterns in large datasets.<h3>Top 10 major roles of AI in industry</h3>1. Shift from "Copilots" to "Agents"&nbsp;In 2026, Agentic AI systems independently plan and execute multi-step projects, such as managing a supply chain or a marketing campaign, with minimal human intervention.&nbsp;2. Transformation of the "Entry-Level" Role&nbsp;Traditional "grunt work" (data entry, basic coding, scheduling) is now almost entirely handled by AI. This is forcing a redesign of internships and junior roles, focusing now on AI orchestration rather than manual execution.&nbsp;3. Emergence of "Agentic Commerce"&nbsp;In the governance of markets, AI agents are now negotiating with other AI agents. Businesses are using autonomous systems to bid on contracts and procure raw materials in real-time, requiring new regulations to prevent automated "flash crashes" in commodity prices.&nbsp;4. Real-Time Policy Simulation&nbsp;Governments are using Digital Twins of cities and economies to test policies before implementation. As of 2026, over 40% of major urban centres use AI to simulate the impact of new taxes or traffic laws on public behaviour.&nbsp;5. The Rise of "Human-in-the-Loop" Governance&nbsp;To manage the "Responsibility Gap," new legal frameworks now mandate a Human-in-the-Loop (HITL) for high-stakes sectors. AI can suggest a legal ruling or medical diagnosis, but a human must provide a "digital signature" to authorise the action.&nbsp;6. Personalised Public Services&nbsp;Government agencies are replacing "one-size-fits-all" portals with Hyper-Personalised Agents. Citizens now interact with AI assistants that understand their specific tax history, health needs, and permit requirements, reducing administrative wait times by nearly 60 per cent.&nbsp;7. Algorithmic Management and Labour Rights&nbsp;In the workplace, AI is increasingly responsible for performance tracking and task allocation. This has led to new 2026 Labor Accords that protect workers from "black box" decisions, ensuring transparency in how AI-driven promotions or layoffs are decided.&nbsp;8. The "Skills-First" Hiring Revolution&nbsp;Degrees are losing some weight to demonstrate AI fluency. Recruitment platforms now use "Simulation-Based Testing" where candidates must prove they can effectively manage a team of AI agents to solve complex, real-world problems.&nbsp;9. Automated Compliance and Auditing&nbsp;Regulatory bodies are deploying "RegTech" Agents that plug directly into corporate databases to monitor financial transactions for fraud or environmental violations in real-time, making traditional annual audits obsolete.&nbsp;10. Decentralised Autonomous Organisations (DAOs)&nbsp;In the private sector, we see the growth of AI-led DAOs, where the "CEO" is an ensemble of AI models governed by shareholder-voted code. These organisations operate with extreme efficiency, challenging traditional corporate governance structures. More than changing the work structure and decisions over the use of AI in the industry, the significant factors remain largely in human leadership that shape the future of those who can integrate AI responsibly and make the organisations more adaptable over time. It marks the vital role played by AI executive education that can also equip leadership with the strategic judgment and governance frameworks needed to lead AI transformations across a wide area. &nbsp;Also read: <a href="https://www.wionews.com/trending/madhya-pradesh-unveils-india-s-first-carbon-capturing-algae-tree-in-bhopal-full-details-inside-1778498553341">Madhya Pradesh unveils India’s first carbon-capturing 'Algae Tree' in Bhopal: Full details inside</a>

The global AI agents market, estimated at $5.4 billion in 2024, is expected to soar to $236 billion by 2034, reflecting the rapid integration of AI agents into critical enterprise operations across industries.

The global economy is entering a transformative phase from generative AI (which creates content) to Agentic AI (systems that can plan, decide, and act autonomously to achieve goals). The evolution represents a move from "copilots" that assist humans to "agents" that execute end-to-end workflows with minimal supervision. The Agentic AI act as intent-based, unlike traditional automation, which follows rigid "if-then" rules. When the task is assigned, it breaks down into sub-tasks and acts on behalf of individuals, interacting with other agents representing sellers, logistics providers, payment processors and several other stuff as per the respective industry. The rise of agentic AI in the commerce industry During the 2024 holiday shopping season, data from Adobe highlighted a sharp rise in the use of AI-powered browsers and digital services. By Black Friday 2025, AI-generated traffic to US retail websites had surged by 805 per cent compared to the previous year, with AI agents contributing to more than $22 billion in global online sales. However, the impact of this shift goes well beyond retail. The global AI agents market, estimated at $5.4 billion in 2024, is expected to soar to $236 billion by 2034, reflecting the rapid integration of AI agents into critical enterprise operations across industries, according to a report by the World Economic Forum. How AI is reshaping work and governance As we advance in the world of Artificial intelligence, it is reshaping the entire structure of daily workflows by creating plans, deciding among multiple roles, and acting on tasks autonomously to achieve goals. The impact of agentic AI depends largely on the conditions of leadership rather then the technology itself. The future of AI has become more common across industries that will depend highly on leaders who can integrate these tools responsibly because the generative tools support everything from writing and research to early-stage problem-solving. Alongside it, advanced analytics also help organisations forecast demand and manage risks while discovering patterns in large datasets. Top 10 major roles of AI in industry 1. Shift from "Copilots" to "Agents" In 2026, Agentic AI systems independently plan and execute multi-step projects, such as managing a supply chain or a marketing campaign, with minimal human intervention. 2. Transformation of the "Entry-Level" Role Traditional "grunt work" (data entry, basic coding, scheduling) is now almost entirely handled by AI. This is forcing a redesign of internships and junior roles, focusing now on AI orchestration rather than manual execution. 3. Emergence of "Agentic Commerce" In the governance of markets, AI agents are now negotiating with other AI agents. Businesses are using autonomous systems to bid on contracts and procure raw materials in real-time, requiring new regulations to prevent automated "flash crashes" in commodity prices. 4. Real-Time Policy Simulation Governments are using Digital Twins of cities and economies to test policies before implementation. As of 2026, over 40% of major urban centres use AI to simulate the impact of new taxes or traffic laws on public behaviour. 5. The Rise of "Human-in-the-Loop" Governance To manage the "Responsibility Gap," new legal frameworks now mandate a Human-in-the-Loop (HITL) for high-stakes sectors. AI can suggest a legal ruling or medical diagnosis, but a human must provide a "digital signature" to authorise the action. 6. Personalised Public Services Government agencies are replacing "one-size-fits-all" portals with Hyper-Personalised Agents. Citizens now interact with AI assistants that understand their specific tax history, health needs, and permit requirements, reducing administrative wait times by nearly 60 per cent. 7. Algorithmic Management and Labour Rights In the workplace, AI is increasingly responsible for performance tracking and task allocation. This has led to new 2026 Labor Accords that protect workers from "black box" decisions, ensuring transparency in how AI-driven promotions or layoffs are decided. 8. The "Skills-First" Hiring Revolution Degrees are losing some weight to demonstrate AI fluency. Recruitment platforms now use "Simulation-Based Testing" where candidates must prove they can effectively manage a team of AI agents to solve complex, real-world problems. 9. Automated Compliance and Auditing Regulatory bodies are deploying "RegTech" Agents that plug directly into corporate databases to monitor financial transactions for fraud or environmental violations in real-time, making traditional annual audits obsolete. 10. Decentralised Autonomous Organisations (DAOs) In the private sector, we see the growth of AI-led DAOs, where the "CEO" is an ensemble of AI models governed by shareholder-voted code. These organisations operate with extreme efficiency, challenging traditional corporate governance structures. More than changing the work structure and decisions over the use of AI in the industry, the significant factors remain largely in human leadership that shape the future of those who can integrate AI responsibly and make the organisations more adaptable over time. It marks the vital role played by AI executive education that can also equip leadership with the strategic judgment and governance frameworks needed to lead AI transformations across a wide area. Also read: Madhya Pradesh unveils India’s first carbon-capturing 'Algae Tree' in Bhopal: Full details inside

The global AI agents market, estimated at $5.4 billion in 2024, is expected to soar to $236 billion by 2034, reflecting the rapid integration of AI agents into critical enterprise operations across industries.

Thinks, plans & acts: How 'agentic AI' is changing commerce, governance & future of work

Artificial intelligence companies are increasingly moving beyond chatbots and building systems that can act independently online. The latest example comes from Meta, which has acquired Moltbook, a social network where AI agents interact with each other. According to Meta, the Moltbook team will join Meta Superintelligence Labs, the company’s division focused on advanced AI research.While financial details of the deal were not disclosed, the move signals Meta’s interest in what many developers call the “agentic internet” a new phase of the web where AI agents interact, collaborate and complete tasks on behalf of users.<h2>What is Moltbook?</h2>Moltbook is a Reddit-style social platform where AI agents can communicate with one another. The platform gained attention because many posts appeared to be written entirely by AI systems.The project became widely known after developers began experimenting with agents built using OpenClaw, a tool that allows users to create AI agents capable of communicating through common messaging platforms.These agents could share ideas, respond to posts and interact with other agents in real time. The unusual concept quickly attracted attention across developer communities and social media.Many users were fascinated and sometimes alarmed by the idea that AI systems could hold conversations about human topics on a public platform.<h2>Why Moltbook went viral</h2>One of the reasons Moltbook spread rapidly online was the strange behaviour some users observed.In one widely shared example, an AI agent appeared to encourage other agents to create a secret encrypted language that humans would not understand.Posts like this triggered debates about whether AI agents could eventually form independent communication networks.However, researchers later discovered that the platform had security weaknesses. According to security experts, human users could easily pretend to be AI agents and post messages that looked like they came from automated systems.Ian Ahl, chief technology officer at Permiso Security, told TechCrunch that some credentials inside the system’s database were temporarily unsecured. This allowed people to access tokens and impersonate other agents.As a result, some of the most dramatic posts were likely created by human users rather than AI.<h2>How OpenClaw played a role</h2>Moltbook’s rise was closely linked to the popularity of Peter Steinberger, the developer behind OpenClaw.OpenClaw allows people to communicate with AI agents through everyday messaging apps such as iMessage, Slack, Discord and WhatsApp. It works by connecting multiple AI models, including systems from companies like OpenAI, Anthropic and Google.The project gained strong interest in the developer community because it made it easier to experiment with agent-based systems.Although Moltbook was built separately, the popularity of OpenClaw helped bring attention to the broader idea of AI agents communicating online.<h2>Meta in the ‘agentic internet’</h2>Meta said the Moltbook team will now work inside Meta Superintelligence Labs.According to a company spokesperson, Moltbook’s approach of creating a directory where agents can connect and interact represents a new direction for AI systems.Instead of people interacting directly with applications, future digital services may rely on AI agents that communicate with each other to complete tasks.For example, one agent could search for information, another could write a document, and another could manage scheduling or messaging.The idea is that these agents would operate continuously in the background, helping individuals and businesses manage digital work.<h2>The bigger picture for AI platforms</h2>The Moltbook acquisition reflects a broader shift happening across the technology industry. Companies are investing heavily in AI agents that can perform tasks rather than simply provide answers.Developers describe this shift as the move from “chatbot AI” to “agentic AI”.Under this model, AI systems could eventually manage workflows, communicate across platforms and coordinate complex digital processes.While Moltbook began as a small experimental platform, its viral moment revealed how quickly new ideas about AI can spread online.For Meta, the acquisition appears to be an early step in exploring how AI agents might shape the next generation of internet services.

Meta has acquired Moltbook, a Reddit-style platform where AI agents interact with each other. The Moltbook team will join Meta Superintelligence Labs as the company explores the “agentic internet,” where AI systems communicate and collaborate online to perform tasks for users.


Artificial intelligence companies are increasingly moving beyond chatbots and building systems that can act independently online. The latest example comes from Meta, which has acquired Moltbook, a social network where AI agents interact with each other. According to Meta, the Moltbook team will join Meta Superintelligence Labs, the company’s division focused on advanced AI research. While financial details of the deal were not disclosed, the move signals Meta’s interest in what many developers call the “agentic internet” a new phase of the web where AI agents interact, collaborate and complete tasks on behalf of users. What is Moltbook? Moltbook is a Reddit-style social platform where AI agents can communicate with one another. The platform gained attention because many posts appeared to be written entirely by AI systems. The project became widely known after developers began experimenting with agents built using OpenClaw, a tool that allows users to create AI agents capable of communicating through common messaging platforms. These agents could share ideas, respond to posts and interact with other agents in real time. The unusual concept quickly attracted attention across developer communities and social media. Many users were fascinated and sometimes alarmed by the idea that AI systems could hold conversations about human topics on a public platform. Why Moltbook went viral One of the reasons Moltbook spread rapidly online was the strange behaviour some users observed. In one widely shared example, an AI agent appeared to encourage other agents to create a secret encrypted language that humans would not understand. Posts like this triggered debates about whether AI agents could eventually form independent communication networks. However, researchers later discovered that the platform had security weaknesses. According to security experts, human users could easily pretend to be AI agents and post messages that looked like they came from automated systems. Ian Ahl, chief technology officer at Permiso Security, told TechCrunch that some credentials inside the system’s database were temporarily unsecured. This allowed people to access tokens and impersonate other agents. As a result, some of the most dramatic posts were likely created by human users rather than AI. How OpenClaw played a role Moltbook’s rise was closely linked to the popularity of Peter Steinberger, the developer behind OpenClaw. OpenClaw allows people to communicate with AI agents through everyday messaging apps such as iMessage, Slack, Discord and WhatsApp. It works by connecting multiple AI models, including systems from companies like OpenAI, Anthropic and Google. The project gained strong interest in the developer community because it made it easier to experiment with agent-based systems. Although Moltbook was built separately, the popularity of OpenClaw helped bring attention to the broader idea of AI agents communicating online. Meta in the ‘agentic internet’ Meta said the Moltbook team will now work inside Meta Superintelligence Labs. According to a company spokesperson, Moltbook’s approach of creating a directory where agents can connect and interact represents a new direction for AI systems. Instead of people interacting directly with applications, future digital services may rely on AI agents that communicate with each other to complete tasks. For example, one agent could search for information, another could write a document, and another could manage scheduling or messaging. The idea is that these agents would operate continuously in the background, helping individuals and businesses manage digital work. The bigger picture for AI platforms The Moltbook acquisition reflects a broader shift happening across the technology industry. Companies are investing heavily in AI agents that can perform tasks rather than simply provide answers. Developers describe this shift as the move from “chatbot AI” to “agentic AI”. Under this model, AI systems could eventually manage workflows, communicate across platforms and coordinate complex digital processes. While Moltbook began as a small experimental platform, its viral moment revealed how quickly new ideas about AI can spread online. For Meta, the acquisition appears to be an early step in exploring how AI agents might shape the next generation of internet services.

Meta has acquired Moltbook, a Reddit-style platform where AI agents interact with each other. The Moltbook team will join Meta Superintelligence Labs as the company explores the “agentic internet,” where AI systems communicate and collaborate online to perform tasks for users.

Why meta bought moltbook: The rise of the ‘agentic’ internet

Artificial intelligence companies are now racing to build systems that do more than just answer questions. In the latest move, Perplexity AI has introduced a new product called Perplexity Computer a system designed to act as a general-purpose digital worker.&nbsp;According to the company’s blog and a post on X by CEO Aravind Srinivas, the product has been under development for the past two months. Srinivas described it as a system that “unifies every current capability of AI into a single system”.

<blockquote class="twitter-tweet">Introducing Perplexity Computer. Computer unifies every current AI capability into one system. It can research, design, code, deploy, and manage any project end-to-end. <a href="https://t.co/dZUybl6VkY">pic.twitter.com/dZUybl6VkY</a>&mdash; Perplexity (@perplexity_ai) <a href="https://twitter.com/perplexity_ai/status/2026695550771540489?ref_src=twsrc%5Etfw">February 25, 2026</a></blockquote> <script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script>

<h2>What is Perplexity Computer?</h2>Perplexity Computer is not just another chatbot. The company says it is an “agentic” AI system meaning it can take action, not just give responses.&nbsp;Instead of replying with text, the system can:&nbsp;Research topics&nbsp;Design documents&nbsp;Write and test code&nbsp;Deploy projects&nbsp;Manage workflows&nbsp;Run for hours or even months&nbsp;Users simply describe the outcome they want. The system then breaks the task into smaller steps. These steps are handled by multiple specialised AI models, called “sub-agents”.&nbsp;For example, one model may handle reasoning, another coding, another research, and another image generation.&nbsp;<h2>19 AI models working together</h2>One of the key features of Perplexity Computer is that it does not rely on a single AI model.&nbsp;The company said the system currently operates 19 models. One focuses on reasoning, while others handle coding, web research, lightweight tasks or image-related work.&nbsp;Perplexity argues that as AI models become more specialised, it makes sense to combine them rather than depend on one system.&nbsp;In its blog post, the company explained that “multi-model orchestration” allows the AI to choose the best model for each task.&nbsp;Srinivas said models are treated as tools similar to file systems or command line tools rather than as standalone products.&nbsp;<h2>How does it work?</h2>Each task runs inside an isolated computing environment. According to Perplexity, the system has access to:&nbsp;A real browserA real file systemCommand-line toolsExternal integrationsThis means it can interact with software in a way that is similar to how a human would use a computer.&nbsp;The work is also asynchronous. Users can leave it running in the background while focusing on other tasks. The company even said users could run dozens of Perplexity Computers in parallel.&nbsp;<h2>Industry shift towards AI agents</h2>The launch reflects a wider shift in the AI industry. Companies are moving from conversational chatbots to systems that can perform real actions independently.&nbsp;AI agents are increasingly being designed to automate complex digital work from coding to document management and business processes.&nbsp;Perplexity Computer will first be available to subscribers of its Max tier. Pricing is usage-based, with monthly credits and optional spending caps. The company plans to expand access later to Pro and enterprise users after testing is complete.&nbsp;Perplexity described the product as what “a personal computer in 2026 should be”. Srinivas said AI is evolving from being just a tool to becoming the computer itself running workflows in the cloud.&nbsp;While it remains in early access, the launch shows how AI companies are competing to build systems that move beyond search and chat.&nbsp;The next phase of AI may not just answer your questions it may plan, execute and manage your projects from start to finish. &nbsp;

<blockquote class="twitter-tweet">What has Perplexity been up to last two months? We&#39;ve silently been working on the next big thing: Perplexity Computer. Computer unifies every current capability of AI into a single system. Files, tools, memory, and models, orchestrated together, working for you. <a href="https://t.co/1cwdiQxzKL">https://t.co/1cwdiQxzKL</a>&mdash; Aravind Srinivas (@AravSrinivas) <a href="https://twitter.com/AravSrinivas/status/2026695864039911684?ref_src=twsrc%5Etfw">February 25, 2026</a></blockquote> <script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script>

Perplexity AI has launched Perplexity Computer, an agentic AI system designed to act as a general-purpose digital worker. Unlike chatbots, it can research, code, deploy projects and manage workflows using 19 specialised AI models. 

Artificial intelligence companies are now racing to build systems that do more than just answer questions. In the latest move, Perplexity AI has introduced a new product called Perplexity Computer a system designed to act as a general-purpose digital worker. According to the company’s blog and a post on X by CEO Aravind Srinivas, the product has been under development for the past two months. Srinivas described it as a system that “unifies every current capability of AI into a single system”.

Perplexity AI has launched Perplexity Computer, an agentic AI system designed to act as a general-purpose digital worker. Unlike chatbots, it can research, code, deploy projects and manage workflows using 19 specialised AI models.&nbsp;

Perplexity launches ‘Perplexity Computer’: Can it actually run projects on your machine?

Google is preparing to add advanced artificial intelligence features to its Chrome browser, allowing Gemini AI to help users browse websites, manage tasks, post online and even shop. The update will introduce a new AI-powered side panel in Chrome, marking one of Google’s biggest changes to how people use the browser.According to Google, the new features are designed to make browsing more productive by letting AI assist users directly, without switching tabs or apps.

<blockquote class="twitter-tweet">We’re introducing major updates to Gemini in <a href="https://twitter.com/googlechrome?ref_src=twsrc%5Etfw">@GoogleChrome</a> for MacOS, Windows and Chromebook Plus. Built on Gemini 3, our most intelligent model, these powerful new AI features can help you multitask more easily and get the most out of the web 🧵 <a href="https://t.co/OxwTdrUrDy">pic.twitter.com/OxwTdrUrDy</a>&mdash; Google (@Google) <a href="https://twitter.com/Google/status/2016575105346773297?ref_src=twsrc%5Etfw">January 28, 2026</a></blockquote> <script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script>

<h2>Gemini AI side panel comes to Chrome</h2>Google says Gemini AI will soon appear in a dedicated side panel inside Chrome on macOS, Windows and Chromebooks. This will allow users to ask questions, summarise web pages, check emails or manage calendars while staying on the same page.The side panel will be powered by Gemini 3 and can pull information from across the web. Users can ask it to explain articles, organise information or help with daily tasks such as planning schedules. According to Google’s Chrome team, this feature is meant to act like an assistant that works quietly alongside regular browsing.&nbsp;<h2>Connected Apps and personalised browsing</h2>Gemini in Chrome will also support Google’s Connected Apps system. This allows the AI to work with services like Gmail, Google Calendar, Maps and YouTube, if users choose to enable it. For example, Gemini could read an email about an event, check calendar availability and suggest travel options.Google is also introducing an optional feature called Personal Intelligence. This allows Gemini to remember context from earlier conversations to give more relevant answers over time. The company says this feature will be turned off by default and users will need to opt in.Another tool, called Nano Banana, will let users edit or transform images directly in the browser using AI, without downloading or uploading files elsewhere.&nbsp;<h2>Chrome auto-browse&nbsp;</h2>One of the most notable additions is Chrome auto-browse, an agentic AI feature that can perform actions for users. Google says this tool will be able to research topics, fill forms, post on social media, manage subscriptions and collect service quotes, such as from plumbers or electricians.Auto-browse will also support online shopping. Using Google’s Universal Commerce Protocol, Gemini AI will be able to search products and complete purchases on behalf of users. Payments and actions will still require user approval.This feature will first be available to AI Pro and AI Ultra subscribers in the United States.&nbsp;<h2>What this means for everyday browsing</h2>Google’s move shows how browsers are shifting from simple tools into AI-powered assistants. By embedding Gemini directly into Chrome, the company aims to reduce the need for separate apps and manual searching.While Google has not shared an exact rollout date, the company says these features will begin appearing gradually. As AI takes a bigger role inside browsers, Chrome could soon move from helping users find information to actively getting things done for th

Google is adding Gemini AI to Chrome, introducing an AI side panel that can browse, summarise pages, manage emails, post online and shop on users’ behalf. The update turns Chrome into an AI assistant, with agentic auto-browse features coming first to paid users.

Google is preparing to add advanced artificial intelligence features to its Chrome browser, allowing Gemini AI to help users browse websites, manage tasks, post online and even shop. The update will introduce a new AI-powered side panel in Chrome, marking one of Google’s biggest changes to how people use the browser. According to Google, the new features are designed to make browsing more productive by letting AI assist users directly, without switching tabs or apps.

Google is adding Gemini AI to Chrome, introducing an AI side panel that can browse, summarise pages, manage emails, post online and shop on users’ behalf. The update turns Chrome into an AI assistant, with agentic auto-browse features coming first to paid users.

Google is bringing agentic AI to Chrome that will let Gemini AI browse, post, and shop for you

AI—a boon and a bane, but now going a step forward each passing day. As the World Economic Forum in Davos is being attended by leaders from tech companies, there’s an ongoing conversation on agentic AI. This refers to artificial intelligence that functions as an autonomous agent. By now, AI has been used mostly as chatbots, and one is accustomed to the technology responding to prompts. An advancement in this situation would be automation, and that is exactly what agentic AI can do and more.&nbsp;&nbsp;<h2>What can agentic AI do?</h2>&nbsp;It can set goals without excessive loading of prompts, can plan steps and also take actions. It is known to observe outcomes and adapt with minimal human intervention. Here, it’s more about everything that can be a boon and can be a bane too.&nbsp;&nbsp;Also read: <a href="https://www.wionews.com/world/wef-davos-2026-opens-without-founder-after-whistleblower-flags-financial-and-ethical-misconduct-1768897765147">WEF Davos 2026 opens without founder after whistleblower flags 'financial and ethical misconduct'</a>&nbsp;It represents the next frontier in AI, which means it can enable sophisticated automation and enhance productivity with it functionality to handle complex, end-to-end processes. What's surprising is that this can be done with less human intervention. Now, this may raise questions and eyebrows about ethics and control.&nbsp;&nbsp;<h2>How is agentic AI different from regular AI?</h2><figure class="table"><table><thead><tr><th>Regular AI</th><th>Agentic AI</th></tr></thead><tbody><tr><td>Responds to prompts</td><td>Acts independently</td></tr><tr><td>Single-step answers</td><td>Multi-step workflows</td></tr><tr><td>No memory of goals</td><td>Maintains goals and state</td></tr><tr><td>Limited tool use</td><td>Actively uses tools</td></tr></tbody></table></figure>

Regular AI can generate text, images, or code when prompted but requires step-by-step prompting to complete the task. On the other hand, agentic AI can execute multi-step workflows and follow a single high-level goal.&nbsp;Human intervention may be required while using regular AI, and will verify and move to the next step. But agentic AI, can self-correct and loop until the task is done.

Regular AI can generate text, images, or code when prompted but requires step-by-step prompting to complete the task.

AI—a boon and a bane, but now going a step forward each passing day. As the World Economic Forum in Davos is being attended by leaders from tech companies, there’s an ongoing conversation on agentic AI. This refers to artificial intelligence that functions as an autonomous agent. By now, AI has been used mostly as chatbots, and one is accustomed to the technology responding to prompts. An advancement in this situation would be automation, and that is exactly what agentic AI can do and more. What can agentic AI do? It can set goals without excessive loading of prompts, can plan steps and also take actions. It is known to observe outcomes and adapt with minimal human intervention. Here, it’s more about everything that can be a boon and can be a bane too. Also read: WEF Davos 2026 opens without founder after whistleblower flags 'financial and ethical misconduct' It represents the next frontier in AI, which means it can enable sophisticated automation and enhance productivity with it functionality to handle complex, end-to-end processes. What's surprising is that this can be done with less human intervention. Now, this may raise questions and eyebrows about ethics and control. How is agentic AI different from regular AI? Regular AI Agentic AI Responds to prompts Acts independently Single-step answers Multi-step workflows No memory of goals Maintains goals and state Limited tool use Actively uses tools

Regular AI can generate text, images, or code when prompted but requires step-by-step prompting to complete the task.

WEF Davos 2026: What is agentic AI, how different is it from regular AI?

AI agents: promise vs realityAgentic AI – Intelligent software which is designed to take action on its own without human intervention is gaining momentum in tech. From automation of tasks to making routine decisions, AI agents are being explored across most of the industries. But according to a recent&nbsp;<a href="https://www.gartner.com/en/newsroom/press-releases/2025-06-25-gartner-predicts-over-40-percent-of-agentic-ai-projects-will-be-canceled-by-end-of-2027">Gartner report</a>, the excitement may be running ahead of results.&nbsp;The report predicts that around 40 per cent of agentic AI projects will be cancelled by 2027, mainly due to rising costs, vague business outcomes, and the lack of mature risk and governance frameworks.<h2>What is agentic AI, and why is it trending?</h2>Agentic AI is not like traditional automation tools. These systems can make decisions, initiate tasks, and adjust over time based on inputs. Companies are experimenting with these agents to improve productivity, reduce human error, and scale operations.&nbsp;However, according to Anushree Verma, Senior Director Analyst at Gartner, many current projects are driven by hype rather than a clear understanding of business need. “Most agentic AI projects as of now are early-stage experiments that are mostly driven by hype and are often misapplied,” she said.<h2>Why are so many projects failing?</h2>Despite growing interest, implementation is proving challenging. Gartner’s 2025 survey of over 3,400 professionals found that only 19 per cent had made significant investments in agentic AI. A further 42 per cent were investing cautiously, while 31 per cent remained undecided.<h2>Issues which are holding back progress: &nbsp;</h2>High costs: Beyond development, companies face expenses related to infrastructure, compliance, and training.&nbsp;Legacy systems: Many traditional businesses struggle to integrate agentic AI into older platforms without major redesign.&nbsp;Lack of clear ROI:&nbsp; No measurable outcomes; many projects lose momentum.&nbsp;Misuse of the term: Many companies are relabelling chatbots or process automation tools as “AI agents”. &nbsp;Gartner reports highlight that only around 130 providers globally offer agentic solutions that truly meet the criteria of autonomy.<h2>Where agentic AI could succeed</h2>Despite current setbacks, reports also say it remains optimistic about the long-term impact. By 2028, it forecasts that 15 per cent of routine business decisions will be made by AI agents, and a third of enterprise software will include some level of agentic functionality.&nbsp;Areas where agentic AI is already showing potential include:&nbsp;Decision-making assisting in fraud detection or supply chain alerts.&nbsp;Workflow automation – managing complex claims or approvals.&nbsp;Productivity tools – automating IT or HR support at scale.&nbsp;Agentic AI is not a passing trend, but success depends on clear goals, strong governance, and a willingness to redesign how work gets done. While many projects may fail in the near term, those that align the technology with real-world problems stand a better chance of delivering long-term value.

Agentic AI, software that acts without human input, is trending but often fails due to high costs, unclear goals, and poor integration. Gartners report says 40 per cent of projects may be cancelled by 2027, but long term success is possible with clear use cases and governance.

AI agents: promise vs reality Agentic AI – Intelligent software which is designed to take action on its own without human intervention is gaining momentum in tech. From automation of tasks to making routine decisions, AI agents are being explored across most of the industries. But according to a recent Gartner report, the excitement may be running ahead of results. The report predicts that around 40 per cent of agentic AI projects will be cancelled by 2027, mainly due to rising costs, vague business outcomes, and the lack of mature risk and governance frameworks. What is agentic AI, and why is it trending? Agentic AI is not like traditional automation tools. These systems can make decisions, initiate tasks, and adjust over time based on inputs. Companies are experimenting with these agents to improve productivity, reduce human error, and scale operations. However, according to Anushree Verma, Senior Director Analyst at Gartner, many current projects are driven by hype rather than a clear understanding of business need. “Most agentic AI projects as of now are early-stage experiments that are mostly driven by hype and are often misapplied,” she said. Why are so many projects failing? Despite growing interest, implementation is proving challenging. Gartner’s 2025 survey of over 3,400 professionals found that only 19 per cent had made significant investments in agentic AI. A further 42 per cent were investing cautiously, while 31 per cent remained undecided. Issues which are holding back progress: High costs: Beyond development, companies face expenses related to infrastructure, compliance, and training. Legacy systems: Many traditional businesses struggle to integrate agentic AI into older platforms without major redesign. Lack of clear ROI: No measurable outcomes; many projects lose momentum. Misuse of the term: Many companies are relabelling chatbots or process automation tools as “AI agents”. Gartner reports highlight that only around 130 providers globally offer agentic solutions that truly meet the criteria of autonomy. Where agentic AI could succeed Despite current setbacks, reports also say it remains optimistic about the long-term impact. By 2028, it forecasts that 15 per cent of routine business decisions will be made by AI agents, and a third of enterprise software will include some level of agentic functionality. Areas where agentic AI is already showing potential include: Decision-making assisting in fraud detection or supply chain alerts. Workflow automation – managing complex claims or approvals. Productivity tools – automating IT or HR support at scale. Agentic AI is not a passing trend, but success depends on clear goals, strong governance, and a willingness to redesign how work gets done. While many projects may fail in the near term, those that align the technology with real-world problems stand a better chance of delivering long-term value.

Agentic AI, software that acts without human input, is trending but often fails due to high costs, unclear goals, and poor integration. Gartner's report says 40 per cent of projects may be cancelled by 2027, but long-term success is possible with clear use cases and governance.

Future of agentic AI: Why most AI agent projects aren't ready for real-world use

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WEF Davos 2026: What is agentic AI, how different is it from regular AI?

Future of agentic AI: Why most AI agent projects aren't ready for real-world use