IBM has always moved to a different rhythm. Where the tech industry sprints from one fashion to the next, chasing visibility and ephemeral hype cycles, IBM does not. It does not flood billboards or airline magazines. It does not bend to quarterly theatrics. It behaves as an institution. Its cadence is intergenerational, measured not in launches or fiscal years but in the architecture it leaves behind. That identity is both its historical constraint, and its advantage in the age of Agentic AI.
I attended IBM Think in Singapore this year as a guest of IBM’s analyst relations program, and the setting itself reinforced the point.
Singapore has just marked sixty years of independence, yet already speaks openly of its centenary. That is the kind of horizon IBM and its clients understand. What looks like slowness from the outside is often intention. So in the context of Agentic AI, which is not a software feature or a service licence but a tectonic shift in enterprise architecture, IBM may deserve the benefit of the doubt.
IBM is not a hyperscaler. Its name does not dominate the cloud league tables. Instead it has built its identity around high performance computing and the custodianship of systems where scale, security, and stability matter more than market agility. In the heat of the cloud era this posture looked out of step, even archaic. But the emergence of Agentic AI does not and will not reward speed alone. It requires the very foundations that IBM has spent decades refining. What once seemed like a disadvantage, you can now read as foresight.
For more than a decade, they have been quietly assembling the components that agentic systems require. Then pivoted to open architectures before that became fashionable. They have invested in AI longer than almost anyone, often ahead of the curve, and sometimes, as with Watson Health, were punished for it. But in a market suddenly gripped by the language of orchestrators, supervisors, and hybrid frameworks, IBM’s methodical architecture-first philosophy begins to look less like legacy and more like inevitability.
The industry is now converging on an unavoidable consensus. Agentic systems will not be monolithic. They will be hybrid by default. There will be multiple agents, multiple models, and multiple contexts running side by side. That reality requires orchestration, governance, and observability at scale. It is less a software problem than an architectural one. And if architecture and scale problems define the playing field, then IBM has a natural advantage.
watsonx Orchestrate, launched three years ago, is not just another assistant. It routes. It supervises. It helps in planning. It runs headless, independent of interface, and it standardises across architectures rather than locking enterprises into a single front end. With Orchestrate, IBM is not positioning itself as the vendor of every agent but as the backbone that can govern them all. That is a more enduring ambition than the sprint to be first to market with yet another copilot.
To many, including myself, it is always striking how little urgency IBM shows in its go-to-market across almost every product and service line. The absence of hyperbolic energy feels intentional, yet it sits uncomfortably against the frenetic internal pace of its high-end sales culture. One no doubt feeds the other. The result is that IBM consistently undersells itself.
Even at Think Singapore, the strategy and substance were there, but the staging told another story. The venue was cramped, with little room to move. Breakout spaces were scarce, and the setting itself felt constrained, spilling into the paths of hotel guests heading to the pool, the tennis courts, or the Orchard Road shopping strip. The marketing wrapper did not match the tremendous weight of the ideas. To me that is clearly an executive decision.
When it comes to technology, the contrast is sharp. Where other Agentic AI vendors push features with the urgency of an ERP sales cycle, IBM positions itself as more measured and deliberate. What remains uncertain is whether IBM aims to lead decisively from the front or whether it intends to arrive later and impose order on a fragmented landscape. Either path would be consistent with its history.
This perspective also explains why IBM sits outside the usual competitive frames. If we accept that the orchestration space will not belong solely to Microsoft, Salesforce, Accenture, ServiceNow, or even Google Cloud, then the question becomes: who will really define it? Certainly not IBM Marketing.
Nor is IBM attempting to dominate CRM, ERP, MRP, or ITSM. Like every major vendor I’ve spoken to, or whose event I have attended in 2025, its ambition is to orchestrate across them. The difference is that, for IBM, this positioning fits naturally with its identity as an architecture-first company.
This is where the contrast between noise and reality becomes clearer. Agentic AI is attracting a tidal wave of investment and marketing spend, but adoption itself is still only a ripple. The demos are polished and the press releases constant, yet proof-of-concepts rarely convert at scale.
Enterprises remain stuck in experimentation rather than shifting operations. That gap between promise and practice may work in IBM’s favour. Lightweight frameworks and quick PoCs risk evaporating before they ever scale, while IBM’s heavier, architecture-anchored approach has the potential to land with greater mass. If adoption proves slow to start but accelerates over time, those who built for weight rather than speed will be better positioned to capture durable share.
IBM also knows the risks of building platforms that are too heavy. Lotus Notes and Domino were once technically rich and deeply integrated, but they proved too inflexible for the agile disruptions that reshaped business models in the 21st century. That history is not lost on the company.
IBM may not have deliberately engineered this moment, but its architectural DNA means it is accidentally in the right place as Agentic AI takes hold. The happenstance is what matters, and whether IBM can seize it.
Either way, the alignment is striking. Agentic is not another software licence to be sold or a SaaS module to be bolted on. It is a structural shift in enterprise architecture. To orchestrate it requires foundations that can endure, not features that can pivot.
That architectural weight is also the counter to what might be called the explosion problem. Enterprises are drowning in systems, applications, and now agents. Every function has its stack, every stack generates data, and the proliferation is accelerating. Self-discipline in this area will fail. It will take an Ozempic for applications, a metabolic reset, before the sprawl consumes itself. IBM’s approach is not just to add yet more assistants but to orchestrate the excess. Architecture ultimately helps to metabolise the system, not contribute to the bloat.
Agentic AI adoption will also not arrive evenly. The digital divide is already visible, not just between organisations but within them. Some functions will mature quickly while others will lag, and orchestration will need to span across both. The unevenness of maturity is a challenge for any vendor pushing a thin solution, but it fits IBM’s argument that architecture and orchestration are the narrow door to real scale.
There is a great line in the bible (St Luke) that functions as a useful frame for moments of real difficulty. Try your best to enter by the narrow door, because many will try and will not succeed. In the context of Agentic AI, the narrow door is architectural integrity. Few vendors are even aiming for it. Most are rushing the wide gate with “plus AI” products that add features without rethinking foundations. But scale does not come from shortcuts. Without solid architecture, they will not endure. IBM’s wager is that by moving slowly and deliberately, it, and its clients, can hold the narrow path.
So what is the endgame? A century-long perspective is useful, but markets live in five-year increments. IBM’s argument is that Agentic AI is not a race to the first billion-dollar assistant but a choreographed relay across decades of enterprise transformation. Rob Thomas frames it against global GDP.
If twenty percent of the world’s one hundred trillion dollar economy is knowledge work, and IBM can influence even ten percent of that, the opportunity is measured in hundreds of billions, if not trillions.
According to Thomas, the value curve to that elusive ROI runs from experimentation to automation, and then into multi-agent orchestration. We are at the early inflection point now.
Whether that is enough depends on whether enterprises finally reward architecture over agility. I think they should. I advocate for it every day. And IBM’s clients, like Singapore’s government agencies, may be patient, and willing to walk through the narrow door.
But markets are less forgiving. So the question is not whether IBM is right about hybrid agentic architectures. It almost certainly is. The question is whether doing it slow and doing it right will once again leave the company with superior technology and inferior market share.
On strategy, I am with IBM. Agentic AI is not a software SKU and it is not a service licence. Vendors who treat it that way will win headlines and lose the future. IBM’s execution still feels unfinished, but the architecture is right. In the end, on the path to Agentic, that is the only door worth walking through.