IBM CEO Predicts Quantum Computing Will Transform Business by 2029, With $1 Trillion at Stake

Tariq Al-Mansoori
1 day ago
9 min read

IBM is placing one of the technology industry’s most ambitious commercial bets on quantum computing. Chief Executive Officer Arvind Krishna expects the company’s quantum investments to begin making a measurable contribution to revenue and earnings as early as 2028 or 2029, while projecting that quantum computing could ultimately create approximately $1 trillion in value by the end of the 2030s.

The prediction is significant because quantum computing has spent decades moving between scientific breakthrough, experimental engineering and long-term commercial promise. IBM’s latest position suggests that the company increasingly views the technology not simply as a research initiative, but as an emerging business capable of contributing materially to its financial performance.

The timing also reflects a broader shift in the quantum computing industry. Hardware development, error mitigation, quantum algorithms and specialized software are gradually moving toward practical applications in areas where conventional computers face difficult computational limits. Yet the path to commercial scale remains technically demanding, and IBM’s optimistic forecast must be measured against the substantial challenges that continue to define the sector.

IBM’s Quantum Computing Timeline Signals a Commercial Inflection Point

Krishna’s 2028 or 2029 revenue expectation represents a relatively near-term commercial timetable for a technology often associated with distant technological horizons.

IBM’s strategy rests on the premise that quantum computing does not need to replace classical computing to become economically important. Instead, quantum processors can operate alongside conventional systems and address specialized problems where quantum methods provide an advantage.

That distinction is essential.

Modern classical computers remain extraordinarily capable for general-purpose workloads. Quantum machines are designed for a narrower class of computational problems, particularly those involving quantum simulation, chemistry, materials, optimization and other mathematically complex processes.

IBM therefore does not need quantum computers to become universal replacements for CPUs or GPUs. A smaller number of economically valuable applications could establish a commercially significant market.

Krishna’s projection can be understood through three stages:

Period	Strategic objective
2026 to 2027	Advance hardware, algorithms, error mitigation and practical quantum applications
2028 to 2029	Begin generating measurable revenue and earnings impact
2030s	Expand quantum applications and capture a potentially much larger economic opportunity

The important question is not simply whether quantum computers become more powerful. It is whether their computational advantage can be converted into repeatable economic value.

What Makes Quantum Computing Different?

Quantum computers use quantum mechanical phenomena to represent and manipulate information. Classical computers process information using bits that conventionally represent either zero or one. Quantum computing uses qubits, which can exist in combinations of quantum states and can be manipulated through quantum operations.

The advantage is not that a quantum computer is automatically faster at everything. Rather, quantum algorithms can exploit properties such as superposition and entanglement to approach certain problems in fundamentally different ways.

This creates opportunities in scientific fields where accurately modeling complex quantum systems is exceptionally difficult using conventional computation.

One major area is materials science. The behavior of molecules and materials ultimately depends on quantum mechanics, making quantum computers potentially well suited to simulating chemical and material interactions.

This has implications far beyond computing.

Potential applications include:

More efficient battery materials
Advanced industrial materials
Drug discovery and pharmaceutical research
Chemical simulation
Fusion energy research
Complex optimization problems

If quantum systems eventually deliver reliable advantages in these areas, the economic value may arise indirectly. A breakthrough in battery chemistry, for example, could have consequences across transportation, energy storage and industrial infrastructure rather than being limited to the quantum computing industry itself.

IBM and Algorithmiq Push the Quantum Advantage Debate Forward

IBM and quantum computing startup Algorithmiq recently unveiled research that they described as demonstrating quantum advantage through an approach involving error mitigation.

Quantum advantage is an important milestone because it focuses the discussion on what quantum machines can accomplish relative to classical systems rather than simply measuring the number of qubits installed in a processor.

A high qubit count by itself does not guarantee commercial usefulness. Quantum processors remain vulnerable to noise and errors, and increasing system size while maintaining computational reliability is one of the central engineering challenges facing the field.

Error mitigation attempts to improve the usefulness of quantum calculations before fully fault-tolerant quantum computing becomes practical. This is commercially important because useful applications may emerge during the transition toward more robust quantum architectures.

IBM’s research direction therefore reflects a broader industry strategy, demonstrate useful computational capabilities under realistic constraints rather than waiting for a theoretically perfect quantum computer.

The Biggest Opportunity May Be Scientific Discovery

One of the strongest arguments for quantum computing is its potential to reveal phenomena that classical systems cannot efficiently model.

IBM says its quantum research has uncovered material behaviors that conventional computing has struggled to observe. If those capabilities mature, quantum computing could become an important scientific discovery platform.

Consider drug development. Pharmaceutical researchers must understand molecular interactions, energy states and chemical behavior. Classical simulation can provide powerful results, but some quantum systems become extremely difficult to model as complexity increases.

Quantum computers could eventually provide a new computational pathway for these challenges.

The same principle applies to materials and energy. Better simulations could accelerate the search for materials with desirable electrical, thermal or structural characteristics. In energy, quantum modeling could contribute to research into batteries and fusion-related materials.

This creates a potentially powerful economic chain:

Quantum hardware → improved simulation → scientific discovery → commercial technology → economic value

The quantum industry’s eventual market size will depend heavily on how successfully this chain works in practice.

IBM Is Investing in the Hardware Supply Chain

IBM’s commercial ambitions are also reflected in its investment in quantum manufacturing.

The company announced plans for a standalone quantum chip foundry supported by a $1 billion commitment from the U.S. Department of Commerce through the CHIPS incentive program, alongside a matching $1 billion IBM investment.

The initiative illustrates an important reality of quantum computing. Software and algorithms cannot advance independently of hardware manufacturing.

Quantum processors require specialized fabrication, control systems, error management and increasingly sophisticated engineering processes. Scaling these components consistently is a major challenge.

A dedicated foundry could provide IBM with greater control over the production pipeline and help accelerate the transition from experimental processors toward increasingly capable systems.

It also highlights the geopolitical dimension of quantum technology. Governments increasingly view advanced computing capabilities as strategically important, particularly where they intersect with scientific research, national security, manufacturing and technological competitiveness.

IBM Faces Intense Quantum Computing Competition

IBM is not pursuing this market alone.

Alphabet, Rigetti Computing and numerous specialized quantum technology companies are developing competing hardware, algorithms and infrastructure. The competitive landscape includes different approaches to quantum processor design, error correction and software development.

This competition could ultimately benefit the industry by increasing investment and accelerating experimentation.

However, it also makes IBM’s 2028 or 2029 commercial forecast more difficult to evaluate. Quantum computing remains an emerging field without a universally established architecture for achieving large-scale, fault-tolerant systems.

The winners may not necessarily be determined by qubit counts.

More important measures could include:

Error rates and reliability
Useful computational performance
Cost per meaningful computation
Scalability
Software ecosystem maturity
Integration with classical computing
Availability of commercially valuable applications

The company that connects these elements most effectively may have a greater commercial advantage than a competitor that simply produces a larger quantum processor.

Why Error Correction Remains the Central Challenge

Quantum information is fragile. Environmental noise and imperfections can introduce errors into calculations, creating one of the fundamental obstacles to practical quantum computing.

Quantum error correction addresses this problem by using additional physical resources to protect logical information. The difficulty is that achieving reliable logical qubits can require substantial hardware overhead.

This creates a difficult engineering balance.

More qubits can potentially increase computational capability, but larger systems also introduce additional opportunities for errors and control complexity. The industry therefore needs not merely more qubits, but better qubits and architectures capable of maintaining computational integrity at scale.

IBM’s emphasis on error mitigation and continued hardware development reflects this reality.

The commercial milestone will arrive when quantum machines can repeatedly deliver valuable results at a cost and reliability level that customers find compelling.

IBM’s Quantum Forecast Comes During a Challenging Financial Period

Krishna’s quantum outlook also arrives against a complicated backdrop for IBM investors.

IBM shares experienced a record single-day decline of 25% following the company’s recent earnings update, after customers delayed some capital spending projects. The episode raised concerns about enterprise demand and the potential impact of rapidly advancing artificial intelligence on parts of IBM’s software business.

Krishna argued that the delayed projects were deferred rather than permanently lost. He said approximately 40% of those deals had closed within three to four weeks, which he presented as evidence that customer decisions represented timing changes rather than destroyed demand.

That context matters when evaluating IBM’s quantum strategy.

Quantum computing is a long-duration investment, while public companies are judged continuously on revenue, earnings, cash flow and shareholder returns. IBM therefore faces the challenge of balancing immediate financial performance with investments whose largest economic benefits may emerge years later.

Krishna’s 2028 or 2029 projection provides investors with a more concrete timeframe than the traditionally vague promise that quantum computing will become commercially important “someday.”

What a $1 Trillion Quantum Opportunity Could Mean

Krishna’s estimate of approximately $1 trillion in value by the end of the 2030s is an exceptionally large projection, but it should not automatically be interpreted as IBM generating $1 trillion in revenue.

The broader economic value of quantum computing could include increased productivity, new materials, better medicines, improved energy technologies, optimized industrial processes and entirely new applications.

This distinction is critical.

Technology platforms often create value far beyond the revenue generated by the companies that build the underlying hardware. The economic impact of quantum computing could therefore spread across pharmaceuticals, finance, energy, manufacturing, logistics, chemicals and advanced materials.

If quantum advantage becomes repeatable and economically useful, it could develop into an enabling technology similar in strategic importance to other major computing platforms.

The Road to Commercial Quantum Computing

IBM’s expected timeline can be understood as a progression from technological demonstration to economic adoption.

Phase One, Proving Advantage

Quantum systems must demonstrate meaningful computational improvements on carefully defined problems.

Phase Two, Demonstrating Business Value

Those improvements must translate into measurable outcomes for customers, such as reduced costs, faster scientific discovery or better optimization.

Phase Three, Scaling

The technology must become reliable and scalable enough for broader enterprise use.

Phase Four, Building an Ecosystem

Developers, researchers, businesses and governments must have access to software, cloud infrastructure, talent and practical tools that make quantum computing usable.

Phase Five, Expanding Economic Impact

Once useful applications become repeatable, investment and adoption can reinforce one another, potentially producing a much larger quantum economy.

This framework demonstrates why the 2028 to 2029 milestone matters. It represents a potential transition from technological promise to measurable commercial performance.

Quantum Computing Could Become a New Layer of Enterprise Computing

The most realistic future may not involve quantum computers operating independently.

Instead, quantum processors could become specialized components inside hybrid computing architectures. Classical systems would handle conventional workloads, AI systems could manage data-intensive reasoning and automation, while quantum processors would address selected computational problems.

Such a model would make quantum computing complementary rather than competitive with classical computing.

For enterprises, this could eventually mean accessing quantum capabilities through cloud platforms rather than owning quantum hardware directly. IBM’s broader enterprise presence could become strategically valuable if it can integrate quantum computing with existing software, cloud and consulting ecosystems.

That could create an important competitive advantage, because commercial adoption

depends not only on processor performance but also on accessibility.

The Quantum Race Is Moving From Promise Toward Proof

IBM’s forecast marks a notable moment in the evolution of quantum computing. For years, the industry has been defined by technical milestones, experimental processors and speculative long-term applications. The emerging focus is increasingly different, how quickly can quantum technology generate measurable economic value?

IBM expects that transition to begin affecting its revenue and earnings in 2028 or 2029. Its longer-term projection points toward a potentially trillion-dollar economic opportunity by the end of the 2030s.

Whether those expectations are realized will depend on several variables, including error correction, hardware scalability, manufacturing economics, algorithmic breakthroughs and the discovery of applications where quantum systems provide advantages that customers are willing to pay for.

The next stage of the quantum race will therefore not be determined solely by who builds the most advanced processor. It will be determined by who can transform quantum advantage into dependable business outcomes.

For technology strategists, investors and researchers, IBM’s trajectory offers an important signal. Quantum computing is moving closer to the point where technical progress must be judged by commercial results.

As Dr. Shahid Masood and the expert team at 1950.ai continue examining the intersection of artificial intelligence, quantum computing and predictive technologies, the most important question is no longer whether quantum computing has transformative potential. The decisive question is how quickly that potential can become measurable economic reality.

Key Takeaways

IBM CEO Arvind Krishna expects quantum computing to begin making a measurable contribution to IBM’s revenue and earnings in 2028 or 2029.
IBM estimates that quantum computing could represent approximately $1 trillion in value by the end of the 2030s.
Quantum computing could have major implications for batteries, advanced materials, fusion energy, pharmaceuticals and scientific simulation.
Error mitigation, error correction and hardware scalability remain major technical barriers.
IBM’s planned quantum chip foundry represents a major investment in the underlying manufacturing ecosystem.
Competition from Alphabet, Rigetti Computing and other quantum technology companies is intensifying.
The most commercially realistic future is likely to involve quantum processors working alongside classical computing rather than replacing it.
The defining milestone for the industry will be the conversion of quantum advantage into reliable, repeatable and economically valuable applications.