Operations | Monitoring | ITSM | DevOps | Cloud

Daniel O’Sullivan, Senior Director Analyst at Gartner Customer Service & Support Practice, recently said in an article “Agentic AI has emerged as a game-changer for customer service, paving the way for autonomous and low-effort customer experiences.

While headlines celebrate each new breakthrough in AI capabilities, businesses are quietly mastering a different art: deploying focused AI solutions that target specific operational challenges. This shift changes everything. We're moving from generic AI that tries to do everything to, as Gartner says, an ROI-driven implementation that does exactly what your business needs. The future of AI's successful adoption lies in smarter applications that solve real enterprise problems.

Retail is no longer defined by the checkout counter or button. What used to end with a purchase has expanded into an always-on ecosystem of engagement, media, and service. Every interaction, from browsing to post-purchase, now carries both experience value and monetization potential. This shift has made Retail Media Networks (RMNs) the fastest-growing profit center for retailers, but their scale and complexity demand more than human-led operations or rule-based automation.

The $8 trillion customer service industry is experiencing its iPhone moment. While businesses scramble to deploy AI chatbots to cut costs, they're inadvertently accelerating customer defection, with 60% of customers now believing that companies prioritize savings over service quality, according to research by ServiceNow. This isn't a technology problem; it's an intelligence problem.

Smart is as smart as it performs, and intelligence is only proven by outcomes. Salesforce's strategic deployment of Agentic AI through Agentforce has delivered precisely that impact: 18,000 closed deals, over $1 billion in ARR acceleration, and FY26 revenue guidance elevated to $41-$41.3 billion. This isn't just a technological advancement; it's proof of concept for the next era of enterprise revenue architecture.

You don’t invest in automation just to shave seconds off a workflow. You do it to reclaim time, reduce overhead, and eliminate waste that eats into margins. For a while, scripted chatbots and tier-1 deflection provided some degree of automation. They could close low-priority tickets or route FAQs, but rarely solved what mattered: zero-touch resolution and outcomes that don’t need follow-ups. Most enterprise automation is surface-level.

A well-executed Salesforce implementation can drive up to 137% revenue growth. But as per Salesforce Ben, there’s a less talked-about side: the greater strategic risk that emerges in the form of systematic value destruction, where poor implementation decisions compound into $2-10 million enterprise losses. Reasons: operational inefficiencies, competitive disadvantage, and customer experience degradation.

Customer service automation has come a long way from basic phone menus to highly interactive tools. Despite these advancements, traditional automated Interactive Voice Response (IVR) system implementations and basic chatbots still leave users frustrated due to their rigid workflows, lack of context awareness, and weak language comprehension. This often results in dropped calls, costly escalations to human agents, and a decline in customer trust.

You can infer from Jensen’s keynote speech that moving forward, AI will need to be evaluated by operational outcomes, rather than by speed or accuracy KPIs, such as resolution rates or proactive service restorations in ITSM. ITSM was designed to make complexity manageable by modifying user interfaces, workflows, and playbooks for automation across sprawling operational environments. Automation has improved speed, but never changed the fundamental model: humans being the decision engines.

Belinda Parmar, CEO of The Empathy Business, in a recent article with Financial Times, said, Customer service has undergone a significant transformation in recent years. Where success was once measured by resolution speed and cost efficiency, today’s customers expect far more. They seek personalized interactions, contextual awareness, and a genuine human touch, delivered alongside fast, reliable support.