Tag: customer service

How AI Is Revolutionizing Business Operations in 2026: Automation, Insights, and Strategy
AI Becomes an Everyday Business Tool

By 2026, artificial intelligence has moved far beyond experimental projects and into the core of daily business operations. Companies across industries are embedding AI into workflows to automate repetitive tasks, analyze vast datasets, improve customer interactions, and support faster, more informed decision-making. Rather than a standalone technology, AI now functions as an integrated capability that augments human effort.

Automation and Operational Efficiency

One of the most visible impacts of AI is automation. Routine activities such as data entry, scheduling, paperwork, and handling common customer inquiries are increasingly handled by AI systems without direct human involvement. This frees employees to focus on higher-value work that requires judgment, creativity, and interpersonal skills. Machine learning algorithms also analyze operational data to uncover patterns that might escape human notice, helping teams optimize processes and reduce inefficiencies.

Transforming Customer Service

Customer support has been reshaped by AI-powered chatbots and virtual assistants that provide round-the-clock assistance. These tools handle high-volume, repetitive queries, while more complex issues are escalated to human representatives. Generative AI further empowers support teams by drafting responses, summarizing conversations, and quickly retrieving relevant information, enabling faster resolution and improved customer satisfaction.

Data-Driven Decision-Making

AI-driven analytics platforms turn raw operational, financial, and customer data into actionable insights. Predictive analytics help businesses forecast demand, identify risks, and optimize supply chains through inventory tracking and threat detection. While AI enhances decision-making with richer information, human judgment remains essential for evaluating options and making strategic choices.

Generative AI in the Workplace

Generative AI tools have expanded the range of tasks that can be accelerated or automated. Employees use them to draft emails, compile reports, brainstorm ideas, and support research. Software developers leverage AI for code generation and documentation, while marketing teams create campaign content more efficiently. However, AI-generated outputs require human review to ensure accuracy and relevance, as errors or misleading information can occur.

Evolving Workforce Roles

Rather than replacing jobs, AI is transforming roles by taking over routine components. Employees now need new skills such as data literacy, critical thinking, AI tool management, and validation of machine-generated outputs. Organizations are rethinking workforce planning to determine which tasks remain human-led and which can be automated, balancing efficiency with the need for human oversight.

Challenges and Considerations

The widespread adoption of AI brings significant challenges. Data privacy, cybersecurity, accuracy, transparency, and responsible use are top concerns. Companies must establish clear policies on what data can be fed into AI systems and how to protect sensitive information. Employee training and ongoing human oversight are critical to mitigate risks and ensure ethical deployment.

AI as a Strategic Capability

By 2026, leading organizations view AI not merely as a technology but as a core business capability that influences automation, customer service, data processing, content creation, and personnel management. Success depends not only on adopting AI but on integrating it thoughtfully into processes while preserving human decision-making and education. The result is a partnership where AI handles routine tasks and people focus on strategic, creative, and relational work.

Frequently Asked Questions
- How is AI changing business operations in 2026? AI automates repetitive tasks, analyzes data, improves customer service, and supports faster, informed operational decisions across departments.
- Which business functions are using AI? AI is deployed in customer service, finance, marketing, human resources, supply chains, and other operational areas.
- How does AI improve customer service? AI-powered chatbots handle routine queries around the clock, allowing human representatives to focus on complex issues.
- Can AI replace human employees completely? No. AI primarily supports employees by automating repetitive work, while human judgment, creativity, and decision-making remain essential.
- What challenges do businesses face when adopting AI? Key challenges include data privacy, cybersecurity, accuracy, transparency, responsible usage, employee training, and maintaining human oversight.
November 3, 2026
Building PayPal’s Invisible Support Layer: An Interview with Senior Engineer Nishanthi Yuvaraj on Agentic AI

When a customer opens a chat window and their issue resolves before they finish typing, there’s a complex invisible layer making that possible. Nishanthi Yuvaraj, a Senior Software Engineer at PayPal, has spent over a decade building and scaling the contact channels that power that seamless experience. From her early days as an intern in 2013 to earning multiple patents and delivering a keynote on autonomous customer service, Yuvaraj’s career is a masterclass in infrastructure, innovation, and governed autonomy.

The Evolution of Customer Servicing at PayPal

Yuvaraj began at PayPal as an intern and has since worked on nearly every customer contact channel: call support, secure messaging, live chat, bot-driven systems using IBM Watson and Google Dialogflow, and the omnichannel layer that recognizes intent across all of them. She notes that the domain has transformed completely—from disconnected, single-channel support to an integrated system where a customer’s history is treated as one continuous conversation.

Key Platforms: Message Hub, Nudge Hub, and the Customer Journey Platform

Message Hub serves as the system of record for conversations with over 230 million customers. Nudge Hub uses real-time event streaming to proactively reach out before a customer asks for help. Together with the Customer Journey platform, these systems enable PayPal to treat a customer’s history as a continuous thread. The challenge, Yuvaraj explains, is operating at a scale where downtime is unacceptable—and the redesign of Message Hub alone significantly increased abatement rates without customers noticing the transition.

Patents and Research: From Proactive Error Resolution to Agentic Systems

Yuvaraj holds three granted U.S. patents, with two more pending. Her first patent covers proactive error resolution—recognizing failures before the customer does and routing them to help automatically. Another family of patents focuses on making shared transaction data useful by using machine learning to surface relevant offers. Her pending applications include a multimodal agentic resolution framework, which aligns with her current research on self-healing customer experience systems. She has also authored a dozen peer-reviewed papers on data governance, AI-driven customer experience, and agentic systems.

The Research Instinct: From Undergrad to International Recognition

Yuvaraj’s research instinct dates back to her bachelor’s degree at College of Engineering Guindy, Anna University, where she built an e-learning platform for visually impaired students. That project taught her to design for users who are often overlooked—a lesson that has stuck with her. At Cognizant, she worked on localizing PayPal.com for India and created “PayPal Parivar,” a family-based payment concept that emerged from observing how Indian families manage money jointly. That experience reinforced her belief that the best innovations come from understanding user behavior, not starting with technology.

Infrastructure Work That Unlocks Innovation

Early in her PayPal career, Yuvaraj built an automated end-to-end testing framework that cut the regression cycle from five days to two. While unglamorous, that infrastructure work enabled faster, safer shipping and gave the team room to experiment. She emphasizes that innovation often sits at the seams between technologies, and being well-versed across languages and platforms is crucial.

Writing to Fill a Gap

Yuvaraj began publishing peer-reviewed papers because she saw a gap in the literature around the connective tissue between data governance and AI-driven customer experience. She writes about preparing enterprise data for LLM-assisted issue analysis and governed autonomous systems. Her advice to engineers: “Stay hungry, stay foolish—publish your work before you feel like enough of an expert.”

The Future: Zero-Touch Customer Experience with Governed Autonomy

Yuvaraj’s recent work focuses on agentic AI for zero-touch customer experience. She envisions systems that resolve issues and heal themselves without human intervention, but can explain every decision to a compliance reviewer. In her KalingaConf keynote, she presented a closed-loop framework combining autonomous agents, predictive analytics, event-driven orchestration, and reinforcement learning. The system detects problems before the customer does, diagnoses root causes, remediates automatically, and learns from outcomes—escalating only when risk is high. This approach improved customer satisfaction and reduced mean time to recovery while maintaining compliance.

Leadership and Mentorship

As a woman in backend engineering, Yuvaraj believes reliability earns leadership opportunities. She mentors students and colleagues by giving them real ownership of hard technical problems early. Her philosophy during production incidents: “Fix first, understand second, blame never.” She views 2 a.m. calls as learning opportunities that reveal how systems behave under real conditions.

Advice for Aspiring Engineers

Yuvaraj encourages engineers to stay curious about every layer of the stack, including unglamorous areas like data governance. She advises building end-to-end systems and publishing work even when you don’t feel ready. “The moment you stop being curious about the layer just below or just above the one you’re comfortable in is the moment you stop growing.”

October 7, 2026
How PayPal Engineer Nishanthi Yuvaraj Is Building Proactive, AI-Driven Customer Support

Nishanthi Yuvaraj, a Senior Software Engineer at PayPal with over a decade of experience, has been the driving force behind the company’s customer contact channels. Her work spans call, email, live chat, bot-driven support, and asynchronous messaging, all integrated into an omnichannel system that recognizes customer intent across platforms. Now, she is pushing the boundaries with agentic AI—systems that resolve issues before customers even have to ask.

In a recent interview, Yuvaraj reflected on her journey from intern to innovator, the patents she holds, and her vision for self-healing customer experiences. Below are highlights from the conversation.

From Intern to Architect of Customer Service

Yuvaraj joined PayPal as an intern in 2013 and has since built or contributed to nearly every customer contact channel. Early projects included an expense-management app for the Florida Department of Transportation during her master’s at the University of South Florida. At PayPal, she worked on Message Hub—the system of record for over 230 million customers’ conversations—and Proactive Nudge Hub, which uses real-time event streaming to reach out to customers before they need help. Together with the Customer Journey platform, these systems treat a customer’s history as one continuous conversation.

Patents and Research

Yuvaraj is a named inventor on three granted U.S. patents and two pending applications. One patent covers proactive error resolution—automatically routing customers to help when a failure is detected. Another family of patents uses machine learning to surface relevant offers from shared transaction data. Her pending work includes a multimodal agentic resolution framework. She has also published a dozen peer-reviewed papers on data governance, AI-driven customer experience, and agentic systems, often generalizing solutions she built at PayPal.

Agentic AI: The Next Frontier

Yuvaraj’s recent research focuses on “zero-touch” customer experience—systems that self-heal without human intervention but maintain a full audit trail for compliance. In a keynote at the Kalinga Conference on Communication & Computing (KalingaConf) in 2026, she presented a framework combining autonomous AI agents, predictive analytics, event-driven orchestration, and reinforcement learning. The closed-loop approach detects problems before the customer does, diagnoses root causes, remediates automatically, and escalates only when risk is high. In evaluations, it improved customer satisfaction and reduced mean time to recovery while cutting compliance violations.

Infrastructure and Leadership

Early in her career, Yuvaraj built an automated end-to-end testing framework that cut PayPal’s regression cycle from five days to two. She emphasizes that unglamorous infrastructure work often unlocks innovation. Her leadership philosophy: fix first, understand second, blame never. She mentors women in engineering by giving them real ownership of hard technical problems early, building their confidence through reliable execution.

Yuvaraj holds a master’s in Management Information Systems from the University of South Florida and a bachelor’s in Computer Science and Engineering from College of Engineering Guindy, Anna University. She received the International Universal Innovator Leadership Award in 2026.

October 5, 2026
Agentic AI in Action: Real-World Use Cases and Industry Lessons
Agentic AI goes far beyond simple chat responses: it plans, acts, and executes tasks across systems, marking a shift from generative content creation to operational authority. While adoption is accelerating, most enterprise projects still fail to scale—not because the technology is weak, but because success hinges on setting clear boundaries for autonomous action.

Gartner projects that 40% of enterprise applications will incorporate task-specific AI agents by the end of 2026, up from under 5% in 2025. Yet McKinsey reports fewer than 10% of companies have scaled agents to deliver real value. Gartner also warns that over 40% of agentic AI projects will be canceled by 2027. The critical question for businesses is: where should AI be allowed to act without human intervention?

Where Agents Move Fastest

Customer service illustrates both the promise and the pitfalls. Klarna’s OpenAI-powered assistant handled 2.3 million conversations in its first month, cutting average resolution time from 11 minutes to under two and matching the output of roughly 700 full-time agents. However, by 2025, Klarna’s leadership acknowledged that automation had gone too far on service quality and began rehiring staff for escalated cases. This reversal underscores a key lesson: the boundary of what an agent should handle alone shifts as organizations learn where trust breaks down.

Software engineering is another area where agents are thriving. Tools like Claude Code, GitHub Copilot’s agent mode, and Cursor now read codebases, write fixes across files, run tests, and open pull requests with minimal manual input. Developers increasingly review diffs rather than writing every line themselves. This sector leads in scaled agent use because the humans supervising the output can quickly catch mistakes.

Where Risk Slows the Rollout

Finance and healthcare move more deliberately. Banks use agents to trace fraud patterns and draft suspicious-activity reports, but any action touching customer funds requires direct human approval. Healthcare systems employ ambient tools like Abridge and Nuance’s DAX Copilot to draft clinical notes and flag coding gaps, while leaving diagnosis and treatment fully in human hands. Insurance follows the same pattern: claims intake, document checks, and fraud screening run through agents, but settlement decisions sit behind an approval gate.

Manufacturing and Retail Emerging Patterns

In manufacturing, a vision system spots a recurring defect, and an agent traces it back to a specific supplier’s batch, then opens a corrective-action ticket automatically—a chain that once took a quality engineer days to reconstruct. Retailers use agents to track demand, generate purchase orders, and set delivery windows, stepping in only when a variance crosses a set threshold. What makes these scenarios truly agentic is the orchestration across systems, not just a single automated task.

The Real Determining Factor

Across industries, one pattern holds: adoption speed moves inversely to the cost of a wrong autonomous action. Customer service and coding advance quickly because mistakes are cheap to catch. Finance, insurance, and healthcare are cautious because a wrong action carries financial, legal, or clinical weight. These sectors are not rejecting agentic AI—they are gating it. Successful deployments share three habits:
- Give the agent a scoped job, not an open mandate.
- Map its permissions to the actual risk of each action, not a blanket setting.
- Define in advance exactly when a human takes over.
Projects that skip these steps tend to be canceled quietly. The ones that succeed are not the boldest deployments—they are the best governed ones.

Final Thought

The next phase of enterprise AI will not be measured by how many agents a company switches on. It will be measured by how precisely each one knows the edge of its own authority—and how quickly a business notices when that edge has been crossed.
September 22, 2026
How COOs Are Using AI Agents to Build Truly Autonomous Operations
Modern Chief Operating Officers (COOs) are moving beyond traditional automation by integrating AI agents into core business processes. These intelligent software systems can analyze data, make decisions, and execute multi-step tasks across supply chains, finance, customer service, and IT operations—all with minimal human intervention. The shift from simple automation to autonomous workflows is redefining how enterprises operate, enabling faster decisions, stronger governance, and more resilient business models.

From Automation to Autonomous Workflows

Traditional automation tools follow fixed instructions. AI agents, by contrast, process data in real time, determine the next best action, and execute tasks across different enterprise systems. For example, in supply chain management, an AI agent can monitor inventory, forecast demand, detect shortages, place orders, and only alert managers when approval is needed. This integrated approach streamlines processes that were previously handled in silos.

Where Companies Are Deploying AI Agents

Organizations are already applying AI agents in several high-impact areas:
- Supply Chain: AI agents track stock levels, predict demand, flag supplier issues, and recommend purchases—responding faster than humans and reducing waste.
- Finance: Departments use agents for invoice processing, account reconciliation, anomaly detection, and report generation, cutting manual steps while maintaining control.
- Customer Service: Agents handle routine inquiries, categorize tickets, and escalate complex issues, freeing human teams for higher-value interactions.
- IT Operations: Technology teams deploy agents to monitor networks, detect failures, and even prevent outages before they affect customers.
The Evolving Role of the COO

As AI becomes integral to daily operations, COOs are shifting focus from pure efficiency to designing a collaborative human-AI operating model. This requires investments in data quality, governance, cybersecurity, and employee training. The key question is no longer which tasks to automate, but which business processes can run autonomously with sufficient human oversight. Successful adoption demands an enterprise-wide approach rather than isolated departmental implementations.

Building Autonomous Operations: A Phased Approach

Most organizations take a step-by-step path:
1. Identify repetitive, high-volume workflows with clear business value.
2. Improve data quality and establish governance policies.
3. Define when human intervention is required.
4. Ensure AI agents can integrate with existing enterprise applications, cloud platforms, and databases.
Companies that treat AI as a strategic, enterprise-level initiative are more likely to succeed than those deploying it in silos.

Why This Matters

The shift to autonomous operations is revolutionizing how businesses manage daily workflows. COOs who combine AI-driven processes with strong governance, reliable data, and human oversight will gain competitive advantages in efficiency and adaptability.

The Challenges Ahead

Despite the promise, risks remain. Poor data quality, outdated IT infrastructure, and siloed architecture can undermine even sophisticated AI agents. Governance is critical—especially for decisions involving finance or customer interactions. Firms must develop transparent methods to explain AI-driven decisions, or they risk compounding problems rather than solving them.

Frequently Asked Questions

What are AI agents in business operations?

AI agents are intelligent software systems that analyze data, make decisions, and execute multi-step tasks with minimal human intervention.

How do AI agents help COOs?

They automate routine workflows, improve operational efficiency, support faster decisions, and allow COOs to focus on strategic priorities.

Which departments benefit most from AI agents?

Supply chain, finance, customer service, procurement, and IT operations are among the earliest and biggest adopters.

Can AI agents replace human employees?

No. They handle repetitive tasks, while humans continue overseeing critical decisions, governance, compliance, and complex problem-solving.

What is the biggest challenge in adopting AI agents?

Ensuring high-quality data, strong governance, cybersecurity, and seamless integration with existing enterprise systems remains the biggest challenge.
September 11, 2026
Apple Tests AI-Powered Live Notes to Automatically Transcribe Genius Bar Sessions

Apple is piloting a new artificial intelligence feature called Live Notes at select Apple Stores. The tool is designed to automatically record and transcribe conversations during Genius Bar support appointments, reducing the need for employees to take manual notes, according to a report from 9to5Mac citing Bloomberg’s Mark Gurman.

The feature transcribes customer conversations in real time, generates a summary, and saves the record to Apple’s internal Genius Bar system after the session ends. Apple has emphasized that the feature is optional and requires explicit consent from both the customer and the employee before recording begins.

To address privacy concerns, Apple has informed employees that voice recordings are not stored on any server, managers will not have access to the raw transcripts, and employees retain the ability to edit both the transcript and the generated summary before submission. Despite these assurances, some staff members have expressed concerns that the transcripts could be used in performance evaluations.

Currently, Live Notes is being tested in only a limited number of Apple retail locations. The company has not announced plans to expand the trial or make the feature mandatory.

This move highlights Apple’s continued investment in AI to enhance customer service experiences while navigating privacy and employee relations challenges.

July 21, 2026
Essential Help Desk Software for Small Businesses and Startups in 2025

Small businesses and startups need efficient customer support without breaking the bank. The right help desk tool streamlines ticket management, automates workflows, and keeps your team responsive across channels. Below are nine top-rated solutions that balance affordability, scalability, and powerful features.

Zendesk

Zendesk offers scalable ticket management, automation, omnichannel support, and analytics, helping businesses deliver faster customer service with minimal operational complexity.

Freshdesk

Freshdesk simplifies customer support through AI-powered automation, shared inboxes, self-service portals, and affordable pricing tailored for growing startups and businesses.

Zoho Desk

Zoho Desk integrates seamlessly with business applications while providing contextual support, workflow automation, and performance insights for efficient customer service operations.

Help Scout

Help Scout delivers email-based support, knowledge bases, collaboration tools, and personalized customer experiences designed specifically for small teams and growing organizations.

Jira Service Management

Jira Service Management combines IT service management, incident tracking, automation, and developer collaboration, making it ideal for technology-focused startups and businesses.

LiveAgent

LiveAgent supports live chat, ticketing, call center features, and social media integration within one affordable platform for responsive customer support management.

HubSpot Service Hub

HubSpot Service Hub connects customer service with CRM capabilities, enabling ticket automation, feedback collection, knowledge management, and personalized customer engagement effortlessly.

HappyFox

HappyFox provides multi-channel ticketing, automation, reporting, and workflow customization, helping businesses improve support efficiency and customer satisfaction across communication channels.

Spiceworks Help Desk

Spiceworks Help Desk offers free IT help desk capabilities including ticket management, asset tracking, reporting, and community support for budget-conscious organizations worldwide.

July 18, 2026
Croma Taps Onsitego’s Qdigi to Elevate After-Sales Service for Own-Label Appliances Across India

Mumbai, July 8, 2026 — Croma, India’s leading omni-channel electronics retailer under the Tata Group, has appointed Qdigi, a subsidiary of Onsitego, as its exclusive Authorized Service Partner nationwide. The strategic collaboration covers installation, repairs, maintenance, and spare parts management for Croma’s rapidly expanding Own Label product portfolio.

Backed by deep technology integration and a pan-India service network, the partnership aims to deliver a best-in-class ownership experience for millions of Croma customers. Support spans categories including air conditioners, refrigerators, washing machines, televisions, and small domestic appliances.

Following a successful operational transition over the past six months, Qdigi now oversees the entire after-sales service ecosystem for Croma’s Own Label products. The service framework is built on four key pillars:

Expanded Nationwide Reach

A service network spanning over 550 centers improves accessibility for customers across the country.

Faster Turnaround Times

Centralized spare parts warehousing, optimized logistics, and partnerships with leading spare-part distribution networks accelerate fulfillment, improve first-time resolution, and reduce repair turnaround times.

Technology-Led Service Delivery

Deep integration between Croma’s CRM platform and Onsitego’s proprietary technology enables intelligent service allocation, real-time tracking, and complete visibility throughout the service lifecycle.

“Our commitment to our customers extends far beyond the point of sale; it encompasses the entire ownership journey,” said Shibashish Roy, CEO & Managing Director of Infiniti Retail Ltd. “As our Own Label portfolio continues to grow, investing in a robust service ecosystem is paramount. This partnership with Qdigi is a significant step in that direction. By combining their expansive network and technical expertise with our customer-first approach, we are creating a service experience that is not just reliable and accessible, but also transparent and efficient.”

Kunal Mahipal, Founder and CEO of Onsitego, added, “At Onsitego, we believe after-sales service is a critical driver of customer trust and brand loyalty. We are delighted to partner with Croma to build one of India’s most advanced and customer-centric service ecosystems for private-label appliances.”

The partnership reflects Croma’s broader strategy of treating after-sales service as a core part of its customer proposition, not an add-on. With over 560 stores across 200+ cities, Croma continues to invest in initiatives that enhance its overall customer experience.

July 10, 2026