To understand why IBM matters again today, we first have to look at the S-curve it missed, highlighting the IMB trends.
Reach out to discuss this topic in depth.
The missed S-curve that reshaped IBM
In the 1980s, IBM lost its pole position in enterprise tech because the basis of enterprise computing shifted under its feet. The mainframe era rewarded vertical integration: IBM’s ability to bundle hardware, proprietary software, and services into one lock-tight system was its moat.
The personal computer era represented a new S-curve. Standardized chips and operating systems became the leverage points, because they allowed software ecosystems to explode across machines built by many manufacturers. Applications, not hardware, became the enterprise value driver, and Microsoft, sitting at the Open Systems (OS) layer, controlled the gateway to that ecosystem.
IBM, with its focus on integrated systems and contractual control, had effectively turned itself into a channel for platforms it didn’t own. The S-curve had moved, and IBM, still massive, still trusted, found itself structurally on the wrong side of the new value equation.
IBM didn’t vanish after missing the PC wave. In the 1990s, under Lou Gerstner, it reinvented itself once already, pivoting hard into services and enterprise integration, shedding businesses like PCs and printers, and becoming the trusted outsourcer to the Global 2000. That move kept IBM relevant and profitable, but it also set its trajectory: a company defined less by technology platforms and more by services and contracts.
By the 2000s, as cloud and software platforms rose, IBM’s position was increasingly defensive.
Over the decades that followed, IBM remained important but no longer central. Its brand still carried weight, but growth had stalled, and by the 2010s it looked more like a company struggling with its past than one defining the future.
Why this matters?
For most of the 2010s, IBM looked like a relic, stock flatlined, portfolio bloated, and no real seat at the hyperscale cloud table.
Then came 2020. Arvind Krishna took the helm, spun out Kyndryl, doubled down on Red Hat, repositioned IBM Consulting, and reframed IBM as a hybrid cloud and enterprise Artificial Intelligence (AI) company.
The chart tells the story: a decade of stagnation, then a clear upward bend post-2020. Investors, analysts, Chief Information Officers (CIOs), and executives are asking again: Is IBM back? The only way to answer that is to interrogate IBM’s real assets and what they mean for the next S-curves.
IBM’s assets ranked by leverage
The seven questions that matter
These assets form the backbone of IBM’s second act. But assets alone don’t tell the story, the real test is how they play against the strategic questions investors, analysts, CIOs, and executives engaging with IBM are already asking right now. These seven questions are shaping whether IBM’s resurgence is a temporary rebound or a durable reinvention.
1. Is Red Hat still IBM’s crown jewel? Yes — but the clock is ticking. Red Hat gives IBM its hybrid cloud wedge, but it must maintain open-source credibility. If enterprises begin to see Red Hat as “just IBM middleware,” its differentiation erodes. The test: can IBM keep Red Hat vibrant while still using it to pull the larger flywheel?
2. Has Watson’s early failure become an AI advantage? Ironically, yes. Watson in healthcare was a public stumble, but the scars gave IBM realism. Watsonx is governance-first, workflow-centric, the opposite of hype. At a time when regulators are circling, that pragmatism is a differentiator.
3. Will IBM pace quantum better than it paced Watson? This is IBM’s biggest optionality bet. Unlike Watson, quantum is being built with public roadmaps, customer ecosystems, and realistic milestones. If it times commercialization right, IBM could own the picks-and-shovels of the next wave. If not, it risks another “ahead of its time” flop.
4. Can IBM Consulting be the AI integrator for enterprises? Post-Kyndryl, yes. Consulting is no longer an anchor but a growth driver, embedding AI into industry workflows. The open question is margins: can IBM Consulting scale like Accenture while retaining differentiation through its tech stack?
5. What businesses are still dead weight? Legacy middleware, some international services operations, and even slices of on-prem support. These aren’t strategic to the next S-curve and could be streamlined or sold. The stock will reward discipline if IBM prunes further.
6. Is “enterprise AI + hybrid cloud” a big enough wedge vs. hyperscalers? It doesn’t have to be bigger — it has to be different. IBM’s bet is that sovereign compute, regulated industries, and workflow depth create moats the hyperscalers don’t want to touch. The risk: if those niches don’t scale, IBM’s wedge could become a cul-de-sac.
7. Does IBM have the leadership depth to sustain this reinvention? Arvind Krishna is the architect of the pivot, but the execution now rests on a strong bench. Rob Thomas runs the software business and global go-to-market, giving IBM a unified story on Data, AI, and Automation. Mohamad Ali leads IBM Consulting, repositioning it as the enterprise AI integrator post-Kyndryl. Dinesh Nirmal drives IBM’s software products, including watsonx and data/AI platforms. The risk is not whether IBM has the talent, it clearly does, but whether the company can sustain speed and agility inside its century-old culture.
The vulnerabilities that really matter
IBM’s resurgence is real, but the durability of this second act depends on risks that go far deeper than the clichés. The true vulnerabilities are structural:
- Can Red Hat remain neutral while inside IBM? Its strength is being the Switzerland of hybrid cloud; if neutrality is compromised, its crown jewel advantage erodes fast
- Can IBM win developer mindshare? CIOs trust IBM, but the future of AI and cloud adoption will be won with developers and architects. IBM has never been the default here
- Can Consulting scale margin with differentiation? Becoming the AI integrator is attractive, but without proprietary leverage it risks becoming another commodity SI
- Is quantum a hedge or a trap? The upside is enormous, but if IBM mis-times commercialization it risks burning another decade
- Will IBM cut fast enough? The biggest execution risk is hesitation, failing to prune low-margin or non-core businesses quickly enough to free capital and focus
Net-net: the real question is whether IBM can operate with the urgency of a growth company while carrying the weight of a century-old incumbent. If it can, IBM becomes an indispensable enterprise counterweight in AI and hybrid cloud. If it can’t, the story risks devolving into yet another false dawn.
If you enjoyed reading this blog, check out IBM Think 2025 – View From The Front Row | Blog – Everest Group, which delves deeper into other topics regarding IBM.
Reach out to Abhishek Singh ([email protected]), to discuss more in depth about our insights and offerings at Everest Group.
