In a world increasingly powered by artificial intelligence, fears about technology replacing human workers have surged—especially among software developers. Yet IBM’s leadership offers a refreshingly nuanced perspective that challenges popular doom narratives while acknowledging AI’s transformative potential in programming.
During a packed keynote at SXSW, IBM Chairman and CEO Arvind Krishna addressed these concerns head-on, presenting a vision where AI serves as a powerful collaborator rather than a replacement for human programmers.
Challenging the 90% Replacement Narrative
Krishna directly challenged recent predictions from Anthropic CEO Dario Amodei suggesting that 90% of code might be written by AI within three to six months.
“I think the number is going to be more like 20-30% of the code could get written by AI—not 90%,” Krishna stated. “Are there some really simple use cases? Yes, but there’s an equally complicated number of ones where it’s going to be zero.”
This assessment draws a more realistic boundary around AI’s capabilities in programming contexts, particularly for complex software systems that require deep domain knowledge and architectural understanding.
Productivity Amplification, Not Job Elimination
Rather than viewing AI as a job killer, Krishna frames the technology as a productivity multiplier that will transform how developers work while potentially expanding opportunities in the field.
“If you can do 30% more code with the same number of people, are you going to get more code written or less?” he asked rhetorically. “Because history has shown that the most productive company gains market share, and then you can produce more products, which lets you get more market share.”
This perspective aligns with historical patterns seen when new tools entered the programming ecosystem. Consider how modern IDEs with features like code completion and automated testing didn’t eliminate developers—they enabled them to build increasingly complex applications more efficiently.
IBM CEO at SXSW 2025. Image credit: IBM
AI as an Evolutionary Tool, Not a Revolutionary Force
Krishna contextualizes today’s AI coding tools by comparing them to past technological innovations that were once feared but ultimately became standard productivity tools.
“It’s a tool,” Krishna said of AI. “If the quality that everybody produces becomes better using these tools, then even for the consumer, now you’re consuming better-quality [products].”
He drew parallels to the introduction of calculators and digital design software like Photoshop, which didn’t eliminate mathematicians or artists but rather transformed how they worked and what they could accomplish.
The Knowledge Boundary: What AI Cannot (Yet) Do
One of Krishna’s most thought-provoking assertions challenges the idea that current AI systems will lead to artificial general intelligence or generate genuinely new knowledge.
“AI is learning from already-produced knowledge, literature, graphics, and so on,” Krishna explained. “It is not trying to figure out what is going to come… I am one who does not believe that the current generation of AI is going to get us towards what is called artificial general intelligence.”
This stands in stark contrast to claims from figures like OpenAI’s Sam Altman, who has predicted “superintelligent” AI within years that could drastically accelerate innovation.
Instead, Krishna suggests that quantum computing—another field where IBM maintains significant investments—will play a crucial role in discovering genuinely new knowledge beyond what AI can derive from existing data.
The Quantum Connection: Beyond AI’s Capabilities
During his SXSW appearance, Krishna emphasized the complementary nature of AI and quantum computing: “AI learns from what we know. Quantum can help us unlock how nature behaves.”
This distinction is vital for understanding IBM’s strategic vision. While AI can help programmers build better software more efficiently based on existing knowledge, quantum computing may enable entirely new classes of solutions to problems that current approaches cannot address.
Krishna boldly predicted that quantum computing would deliver surprising capabilities before the decade ends, potentially transforming fields like:
- Carbon sequestration
- Materials discovery
- Financial pricing models
- Nutrition science
- Business optimization
The International Talent Imperative
Krishna’s vision for technology advancement extends beyond tools to the people who build them. He emphasized the importance of maintaining global talent flows, particularly in technical fields.
“We want people to come here and bring their talent with them and apply that talent,” Krishna said. “And we want to develop our own talent as well, but you can’t develop it as well if you’re not bringing the best people from across the world for our people to learn from too.”
This global talent perspective aligns with his broader belief in international cooperation and trade as engines of growth and innovation.
Practical Applications Today
IBM isn’t just theorizing about AI’s role in programming—the company is actively developing and deploying systems that demonstrate these principles. At SXSW, IBM showcased several practical applications of their AI technologies:
The company demonstrated computer vision systems that could analyze foosball gameplay to generate personality traits and provide English-language breakdowns of playing styles and strategic recommendations—the same technology being used by professional soccer clubs.
IBM Quantum researchers also presented examples of quantum and classical computers working together to simulate iron sulfide, often called the “cradle of life molecule,” showcasing how these complementary technologies can tackle problems beyond either system’s individual capabilities.
The Future: Hybrid Intelligence Rather Than Replacement
The core of IBM’s perspective centers on complementary capabilities rather than substitution. As AI coding tools become more powerful and accessible, the role of human programmers won’t disappear but will evolve to focus more on:
- Problem definition and requirements gathering
- Architecture design and system planning
- Ethical considerations and guardrails
- Testing and validation of AI-generated code
- Integration of components into cohesive systems
Conclusion: Accelerating Innovation Through Collaboration
IBM’s vision for the future of programming embraces AI as a transformative but non-threatening force—a collaborator that can handle routine tasks while enabling human developers to work at higher levels of abstraction.
As Krishna summarized: “If the quality that everybody produces becomes better using these tools, then even for the consumer, now you’re consuming better-quality [products].”
This balanced perspective acknowledges both the significant changes ahead and the enduring value of human creativity, judgment, and oversight in software development—suggesting a future where AI and human programmers evolve together rather than competing for relevance.
The coming years will likely prove Krishna correct that AI won’t replace 90% of programming jobs—but it may fundamentally transform how those jobs are performed and what they can accomplish. In IBM’s view, that’s not a threat but an opportunity for unprecedented innovation and growth.
If you are interested in this topic, we suggest you check our articles:
- AI Coding Assistants: New Generation of Programming Tools That Make Wonders
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Sources: IBM, TechCrunch
Written by Alius Noreika
