Technology, Media, and Telecom (TMT) companies have always been the backbone of digital transformation. SaaS technology companies power the apps we rely on. Media shapes how we consume and interact with information. And telecom provides the invisible infrastructure that connects it all.
Today a new era is unfolding—the Agentic Age—that promises to reshape these industries more profoundly than cloud or mobile ever did. In this new era, TMT is both the enabler and the testbed of agentic AI. Ironically, it’s TMT’s role as the engine behind global AI adoption that puts it most at risk for global AI disruption.
What’s really at stake for TMT in the agentic age?
And what makes waiting such a strategic misstep?
Why the Agentic Age Matters
For decades, automation was about scripts, bots, and workflows designed to make human-driven processes faster. Generative AI shifted that narrative, enabling content creation, summarization, and copilots. Now, we’re entering a world where autonomous and semi-autonomous AI agents act, decide, and orchestrate on behalf of humans.
This shift isn’t incremental. It’s structural. As a result:
1. SaaS providers face pressure to embed agents into their products, not as add-ons but as core features. Customers expect intelligent copilots, self-optimizing workflows, and agent-driven insights out of the box.
Handled correctly, this shift can pay significant dividends. One SaaS provider we work with went from offering a basic chatbot to launching a fully agent-driven onboarding assistant that handles 80% of customer setup autonomously. Within three months, churn dropped by 12% and NPS rose significantly.
2. Media companies face disruption as agents generate and personalize content at scale. The challenge isn’t creating more; it’s maintaining authenticity and trust while sustaining monetization.
Again, there’s tremendous opportunity here. When a global media house tested agentic personalization—i.e., tailoring video recommendations in real time based on micro-behavioral signals—they saw a 25% increase in watch-time without additional production spend.
3. Telecom operators face equal parts opportunity and risk. Autonomous agents can monitor, optimize, and even fix networks in real time, but legacy infrastructure and risk-averse cultures slow adoption.
One notable telco ran an experiment where AI agents monitored and self-healed parts of the network during peak hours. What previously required 20+ engineers was handled by AI agents, reducing downtime incidents by 40%.
In short: TMT doesn’t just consume AI—it enables it. TMT companies provide the infrastructure layer that makes AI possible at scale, namely:
- Connectivity: telecom networks that carry AI traffic
- Platforms: SaaS applications where AI agents operate
- Content: media that AI systems analyze and generate from
TMT companies face a true paradox: they must transform themselves using technology they're simultaneously enabling for everyone else. They're both the foundation and the beneficiary of the agentic-age revolution.
This alone raises the stakes significantly.
The Risks of Standing Still
In the Agentic Age, standing still means failing to adapt with adequate urgency. A retailer might get away with the slow adoption of AI tools, but a SaaS that doesn’t embed AI agents risks customer exodus to competitors who do. Today, 46% of business buyers say they would work with an AI agent for faster service.
The understandable temptation is to experiment with AI in isolated pockets. Think: pilots, proofs-of-concept, and add-ons. But this narrow focus leads to:
- Tool sprawl: Dozens of disconnected AI experiments across teams.
- Rising costs: Compute and licensing bills balloon without clear ROI.
- Talent mismatch: Teams remain optimized for workflows built for humans, not agents.
- Strategic drift: Competitors redefine customer expectations while you optimize yesterday’s processes.
We’ve seen companies run 20+ AI pilots in parallel, only to discover that none scaled past a single department. By the time leadership stepped in, the compute bills had doubled year-on-year, with no enterprise-wide ROI to show for it.
The problem is widespread, with only half of telco CEOs reporting that they’ve captured value from AI. More broadly, 74% of enterprises lack the foundational capabilities required to move beyond proof-of-concept to production-scale AI solutions.
Hardly a recipe for scalability in the Agentic Age.
The Framework for Agentic-Age Evolution
So how do TMT leaders move from pilot purgatory to sustained transformation? It requires a deliberate rethink across three dimensions:
- People: How do we prepare our workforce to collaborate with agents, not compete with them? Upskilling, role redesign, co-working with agents and building trust in AI outcomes are essential.
- Process: How do we stop bolting AI onto old workflows and instead redesign and build agent-first processes? Prioritization, governance, and product thinking are the differentiators.
- Technology: How do we design scalable, cost-conscious, and secure tech and infrastructure stacks that can adapt as models and tools evolve? Optionality is the only antidote to lock-in.
Look at what happens when a media-tech company uses this framework to focus their AI investments. Instead of spreading budget thinly across 15 experiments, they concentrate on retraining editorial staff (People), productizing ad-targeting agents (Process), and adopting a hybrid cloud AI stack (Tech). Within a year, they’ll likely see measurable ROI in both revenue uplift and cost avoidance.
Perhaps most importantly, adopting this framework positions the TMT enterprise for the next iterations of the Agentic Age. It lays the groundwork for scalable AI-native operations capable of buttressing the new AI economy.
The Leadership Imperative
The Agentic Age won’t wait for decision makers to get comfortable. Customers are already experiencing agent-driven features in consumer apps, setting new expectations for enterprise and industry experiences. Regulators are asking questions about transparency and governance. Investors are scrutinizing AI readiness as a proxy for resilience.
For TMT leaders, this isn’t about experimenting with what’s possible. It’s about rearchitecting how your organization works, delivers, and grows. We’ve seen forward-thinking SaaS players already branding themselves as “agent-first platforms” to investors. That positioning alone boosts market confidence and valuations, signaling that readiness for the Agentic Age is now a proxy for long-term resilience.
Because it’s one thing to deploy an agentic AI use case that delivers flash-in-the-pan productivity gains; it’s another thing to create an AI-first culture and infrastructure capable of sustaining and scaling those very gains.
That means greater emphasis on cross-team communication and democratization. It means attending to the infrastructure needs prerequisite to delivering AI impact at scale. Most fundamentally, it requires synchronized transformation across three dimensions: People, Process, and Technology.
Over the next three posts in this series, I’ll dive deeper into each dimension, with practical insights on how TMT companies can evolve to not just survive but thrive in the Agentic Age.
The choice is clear: you can shape the Agentic Age, or you can be reshaped by it.
