EM360Tech Impact Index Apex Winner: Observe.AI

Observe.AI has been named the Q3 2026 Apex Award winner in the EM360Tech Impact Index, recognised for the performance of its Tech Transformed podcast episode, CX Is Now AI's Proving Ground. The Apex Award recognises the strongest-performing individual podcast of the quarter, looking at audience engagement, reach and commercial impact. 

For Observe.AI, that recognition comes from a conversation about a challenge many enterprises are now facing: they've invested in AI, but how do they know whether it's actually working? Customer experience (CX) offers an interesting place to explore that question. 

Every interaction has an outcome, and businesses need to understand whether introducing AI improves that outcome or simply changes how it's delivered. It's a subject that goes well beyond the technology itself, particularly as organisations face growing pressure to justify their AI investments.

The Conversation Behind the Performance

In the winning episode, host Ravit Jain speaks with Sneha Iyer, who leads AI value delivery and analytics at Observe.AI, about the growing role of agentic AI in customer experience. Agentic AI refers to systems that can take action towards a goal, rather than simply analysing information or generating responses. 

In customer service, that could mean an AI agent handling an appointment booking or processing a routine request without needing someone to complete each step manually. Iyer explains that this changes how businesses need to think about their existing technology. 

Many contact centres already use several different systems for handling calls, analysing conversations and supporting customer service teams. She calls this collection of disconnected tools a "Frankenstein stack", which becomes particularly troublesome when AI agents need information from more than one system to complete a task. 

Think about a customer who's already explained their problem to an AI agent, only to be transferred to a human who has no record of the conversation. The customer has to start again, and whatever time the AI saved is quickly lost. 

The discussion moves into the decisions behind making these systems work, including whether businesses should build their own AI solutions, how they should test them and what happens when an automated interaction needs human judgement. There's plenty of technical ground covered, but the conversation keeps coming back to the customer and the business outcome.

Why the Topic Drove Engagement

By Q3 2026, customer service leaders were dealing with an increasingly uncomfortable gap between what businesses were spending on AI and what they could demonstrate in return. In August, Gartner published research on customer service AI spending showing that AI spending among 199 surveyed service and support leaders had increased by 38 per cent, even though their overall departmental budgets had grown by just two per cent. 

The financial results were another concern. According to Gartner's July 2026 customer service research, only 24 per cent of service and support leaders in a separate survey had demonstrated positive financial returns across their AI use cases. Those findings put Observe.AI's podcast into context. 

The conversation wasn't taking place in a market where businesses were simply wondering whether AI might be useful. Many were already spending money on it, and they needed to work out what they were getting for that investment. Iyer's discussion of fragmented systems, performance measurement and the division of work between AI and human agents speaks directly to those concerns. 

There's also the customer's perspective to consider. In Gartner's August 2026 findings on human support, 87 per cent of surveyed customers said access to a human agent was essential when companies used generative AI for customer service. Businesses therefore had more to consider than how much work AI could automate. 

They also needed to make sure customers could still get the help they wanted.

Performance Signals That Stood Out

Observe.AI's episode earned the Q3 Apex Award for its performance across the engagement, reach and commercial impact measures used by the EM360Tech Impact Index. Apex is specifically concerned with how an individual podcast performs. 

A compelling subject or an interesting expert perspective might help explain why a conversation deserves attention, but neither is enough on its own to determine the winner. For Observe.AI, the recognition is particularly interesting when considered alongside the subject of the episode. 

Jain and Iyer were discussing a technology that businesses were actively investing in, while exploring the problems that could prevent those investments from delivering the expected results. The conversation also moved comfortably between the technical and commercial sides of AI adoption. 

Decisions about system integration, vendor selection and evaluation were discussed in terms of their effect on customers and business performance. That combination helps explain the episode's relevance, while the Apex result confirms its standing among the quarter's eligible podcasts.

What This Level of Performance Indicates

There's something worth considering about the kind of conversation Observe.AI brought to the Tech Transformed audience. Agentic AI has applications across the enterprise, but its value can be difficult to judge when the discussion stays at the level of capabilities and future possibilities. Customer service gives people something more concrete to work with. 

A customer either gets their issue resolved or they don't. An AI agent might complete a task successfully, but if the customer has to repeat everything when they reach a human, the overall experience may still be poor. Those outcomes give businesses a clearer way to examine whether their technology is helping. 

Iyer also makes an important distinction between an AI system working in a controlled demonstration and one performing reliably during real customer interactions. Her discussion of simulation testing, ongoing evaluation and governance reflects the responsibilities businesses take on when they allow AI to act on their behalf. 

Observe.AI's award-winning performance suggests that this kind of discussion has a place with enterprise audiences. It brings the conversation closer to the decisions organisations have to make, where the consequences of getting something wrong are much easier to understand.

The Enterprise Takeaway

For enterprise technology organisations, one of the useful things about Observe.AI's podcast is the way it handles a subject that could easily become an extended discussion about AI capabilities. The episode gives those capabilities a purpose by connecting them to familiar customer service problems. 

Iyer's example of disconnected systems is particularly effective because it explains a technical issue through something most people have experienced themselves. It also leaves room for the difficult decisions. Building an AI solution internally might offer greater control, but businesses then have to maintain it as models and requirements change. 

Buying a platform introduces a different set of questions about the vendor, integration and governance. Neither choice can be assessed properly without understanding what the organisation needs the system to do. These are the kinds of details that help an expert conversation become genuinely useful. 

They give people something to consider when making their own decisions, even if their circumstances are different from those being discussed. For vendors, marketers and content teams, there's a lesson in understanding the questions their audience is already trying to answer. 

A technical topic can attract interest, but the discussion becomes much more useful when it helps people understand the choices in front of them. Observe.AI's episode offers a good example of how to make that connection without losing the technical substance.

Final Thoughts: The Role of the Apex Award in the Impact Index

The EM360Tech Impact Index recognises different kinds of achievement across enterprise technology content. Vanguard focuses on the quality of thinking, Catalyst on coordinated campaign performance, and Authority on expert credibility and influence. Apex has a different role. 

It recognises the individual podcast that delivers the strongest audience response through engagement, reach and commercial impact. Each quarter brings different subjects, speakers and enterprise challenges, so there isn't one formula for creating a successful conversation. 

Observe.AI's Q3 2026 win is a useful reminder of what expert-led technology content can offer when it gets close to the problems businesses are trying to solve. As organisations continue working out how to make AI deliver on its promises, those practical conversations have an important role to play.