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The year ahead for AI agents and frontier firms

AMX Ventures’ Arun Mohan highlights the need to bridge the ‘agent gap’ and shares practical advice on multi-agent orchestration and hyper-localised voice AI, while discussing the competitive advantage of building for the application layer.

Arun Mohan, General Partner, AMX Ventures on AI agents and agentic AIArun Mohan, General Partner, AMX Ventures

The velocity of the last two years has redefined the concept of long-term planning. In an era where technological shifts occur weekly, making predictions beyond a three-month horizon is a challenge for even the most seasoned observers.

However, as we look toward 2026, the industry is moving past the experimental phase and toward the reality of artificial intelligence (AI) agents and frontier firms.

Frontier firms are organisations that embed AI into every layer of their operational DNA to drive three times higher returns than slow adopters.

To thrive in this new landscape, two critical trends will define the market: Multi-agent orchestration and hyper localised voice AI.

‘‘For builders and investors, the 2026 mandate is clear: Models are becoming a commodity. The real value – and the sustainable competitive advantage – lies in the application layer.’’

Multi-agent orchestration and the three pillars of adoption

The current enterprise landscape is suffering from an ‘agent gap’. While the market is flooded with agents that can write emails or close sales leads, there is a distinct lack of agents capable of self-healing cloud environments or autonomously orchestrating complex DevOps pipelines. This disparity forces IT professionals to remain the manual labour behind the AI revolution.

The transition to a true frontier firm requires a three-tiered agentic framework, which is the foundational strategy behind platforms such as Onepane Pulse, to scale AI adoption across an organisation:

The personal agent: This focuses on the individual engineer, automating routine troubleshooting and data synthesis to reduce ‘alert fatigue’ and cognitive load.

The team agent: These agents act as digital bridges between silos across development, operations and security, ensuring that tribal knowledge is digitised and cross-functional workflows are executed without manual hand-offs.

The enterprise agent: This layer provides leadership with a ‘pulse’ on the entire digital estate, aligning technical performance directly with business outcomes and governance.

By moving from isolated assistants to an orchestrated multi-agent layer, businesses gain built-in resilience: if one agent fails, the network redistributes the load, maintaining continuity in high-stakes environments.

Hyper-localised Voice AI

A decade ago, industry veterans identified Voice as the “million-dollar problem”, the most seamless interface for human-to-information interaction. Today, that potential is being realised through the convergence of natural language processing and agentic capabilities.

The next frontier for Voice AI, led by industry innovators such as Actualize, is hyper-localisation. Future systems will move beyond simple translation to mastering specific dialects and cultural nuances, making AI accessibility truly equitable on a global scale.

In many developing regions, voice has already become the preferred channel for AI access. For enterprises, the shift toward hyper-natural, context-aware voice agents will soon become standard, reducing call handling times and significantly increasing customer satisfaction through empathetic, real-time responses.

Advice to the market: Build for the application layer

For builders and investors, the 2026 mandate is clear: Models are becoming a commodity. The real value – and the sustainable competitive advantage – lies in the application layer. Businesses no longer need experimental pilots; they need solid applications that offer performance, security and accuracy guarantees.

Furthermore, look for the blending of AI model topologies and computing infrastructure. A unified compute environment that automatically maps a specific transformer model to a graphics processing unit (GPU), or an inference workload to a tensor processing unit (TPU) or central processing unit (CPU) based on efficiency will be the backbone of the next generation of performance.

As we move through 2026, those who focus on bridging the ‘agent gap’ and perfecting the interface of voice AI will be the ones to define the frontier.

By Arun Mohan, General Partner, AMX Ventures

the authorAnup Oommen
Anup Oommen is the Editor of Campaign Middle East at Motivate Media Group, a well-reputed moderator, and a multiple award-winning journalist with more than 15 years of experience at some of the most reputable and credible global news organisations, including Reuters, CNN, and Motivate Media Group. As the Editor of Campaign Middle East, Anup heads market-leading coverage of advertising, media, marketing, PR, events and experiential, digital, the wider creative industries, and more, through the brand’s digital, print, events, directories, podcast and video verticals. As such he’s a key stakeholder in the Campaign Global brand, the world’s leading authority for the advertising, marketing and media industries, which was first published in the UK in 1968.