Agentic AI

Enterprise AI is shifting towards agentic systems, moving beyond chatbots to independently execute complex workflows. This evolution is driven by ‘Supervisor Agents’ orchestrating specialized sub-agents. The surge in AI-driven database creation and the adoption of multi-model strategies highlight a move towards flexibility and risk mitigation. While futuristic agents grab headlines, current value lies in automating routine tasks, with governance acting as a key accelerator for production deployments. The focus is now on engineering rigor and interoperable platforms for sustained competitive advantage.

Shopify’s Winter ’26 “Renaissance” update introduces agentic AI to automate workflows and expand sales beyond traditional storefronts. “Agentic Storefronts” enable purchases directly within AI interfaces like ChatGPT, shifting focus from driving traffic to product discoverability. The AI assistant “Sidekick” is enhanced to manage operational tasks and empower non-technical staff. New tools like “SimGym” and “Rollouts” allow for AI-driven testing of storefront changes. The update also streamlines infrastructure and developer tools, accelerating application development in this new era of commerce.

Agentic AI requires massive memory stores, outstripping current hardware. NVIDIA’s new ICMS platform introduces a dedicated “G3.5” storage tier, bridging the gap between expensive GPU memory and slower storage. This purpose-built layer manages AI’s volatile “KV cache,” significantly improving performance and energy efficiency for long-context workloads. This architectural shift redefines data center design for scalable AI.

PubMatic’s AgenticOS introduces agentic AI into programmatic advertising, moving it from experimental to systemic. This impacts marketing executives by accelerating decisions and reallocating human resources. AgenticOS aims to manage and optimize campaigns within human-set goals, reducing operational complexity and costs. It promises enhanced decision quality at scale and improved governance, with projections indicating agentic AI will become a standard execution layer, leading to more streamlined marketing operations and clearer ROI from integrated platforms.

AI Era Corp. is transforming into an Agentic AI media company, focusing on its proprietary Ufilm AI for rapid script generation. The company reported significant revenue and net income growth in FY2025 and projects substantial increases for FY2026, driven by its short drama library, AI training data licensing, and Uflix platform. A streamlined capital structure and a dual B2C/B2B business model aim to enhance shareholder value and establish recurring revenue streams.

India’s top IT firms – Cognizant, TCS, Infosys, and Wipro – are spearheading enterprise AI adoption with over 200,000 Microsoft Copilot licenses. This massive deployment aims to integrate AI as an “enterprise default” across critical functions, enhancing productivity and positioning these companies as leading AI advisors. The move signifies a global trend towards agentic AI, with businesses leveraging integrated AI tools for efficiency and to redefine workflows, solidifying India’s role as a hub for AI talent and cloud infrastructure.

Amazon is rapidly adopting agentic AI, which plans and executes multi-step tasks, seeing it as a foundational platform rather than just a feature. This shift aims to optimize high-volume workflows across retail, logistics, and customer service. While routine tasks will be automated, potentially impacting hiring and job roles, new opportunities in AI development, governance, and security will emerge. Amazon’s Rufus assistant and Bedrock AgentCore exemplify this move towards autonomous AI, aiming to streamline customer experiences and establish AWS as a key infrastructure provider for enterprise agents.

Perplexity’s analysis of hundreds of millions of agent interactions shows AI “agents” are already boosting enterprise productivity. Adoption is concentrated among high‑value knowledge workers—especially in digital technology, finance, academia, marketing and entrepreneurship—who use agents for cognitive tasks (57% of activity). The dominant use cases are “Productivity & Workflow” (36%) and “Learning & Research” (21%), with agents acting as autonomous thinking partners that gather, synthesize, and act on data in core apps like Google Docs and LinkedIn. Adoption is higher in nations with greater GDP and education. Firms should audit workflow friction, upskill staff to manage AI collaborators, and strengthen security controls as the market expands from $8 bn (2025) to $199 bn (2034).

summary.ByteDance’s Dec 2 launch of the ZTE Nubia M153, powered by Doubao’s agentic AI, sparked consumer enthusiasm but triggered privacy backlash that forced capability cuts. The prototype showcases how OS‑level AI agents could boost enterprise productivity in fields such as manufacturing, healthcare and finance, yet corporate adoption demands robust governance, auditability, role‑based controls and on‑device processing. China’s strong software‑hardware integration gives ByteDance leverage with OEMs lacking AI expertise, while global rivals focus on tight hardware‑software bundles. Successful rollout will hinge on security‑first design, phased pilots, and scalable compliance frameworks.

Manufacturers are earmarking nearly half of modernization spend for AI, expecting it to boost operating margins by 5‑10 % within two years. While 88 % anticipate margin gains, only 21 % feel data‑ready, and legacy integration, security and trust gaps hinder deployment. Companies favor multi‑platform, agentic AI that can autonomously handle routine decisions, yet still rely on safety stock and manual safeguards. To unlock profit, leaders must prioritize data cleanup, phased autonomy and avoid single‑vendor lock‑in, turning AI investment into reliable, scalable performance.