Is AI the end of IT as we know it?

R.E.M.’s song “It’s the End of the World as We Know It (and I Feel Fine),” released in 1987, was about the chaos of the modern world. The song covered themes of information overload and anxiety over cultural and political chaos.

Many CIOs are pondering a similar question about AI and how it will change IT’s mission and operating model. Is AI the next catalyst that will change everything we know about running IT departments, investing in technology platforms, and digitally transforming businesses?

Ask this question in a room of CIOs and CISOs, and responses will cover the gamut, from agentic AIs running IT autonomously, to doomsayers declaring how ungoverned and rogue AI agents can spell disaster.

Does AI spell the end of the CIO?

We discussed the topic of AI’s impact on IT’s charter at a recent Coffee With Digital Trailblazers. “If you’re a CEO and you’re seeing all this AI generating code, you’ve got to be thinking to yourself, Why do I need a CIO anymore?” asked Martin Davis, CIO and managing partner at Dunelm Associates.

Davis answered his own question: “We’ve seen this in the past with outsourcing and other cycles, and we find that we do need IT, but the role of IT does change and evolve.”

Joanne Friedman, PhD and CEO of Connektedminds, offered a promising outlook for CIOs who embrace AI transformation. “AI is a catalyst for the IT organization to become what it has needed for a long time, to go well beyond having a seat at the table and become a business unit strategically important to the organization. And this is also what will take the CIO to a CEO role.”

CIOs have always been challenged by the time, skills, and complexities involved in running IT operations. Cloud computing, low-code development platforms, and many DevOps practices helped IT teams move “up stack,” away from the ones and zeros, to higher-level tasks. Now the question is whether AI will free CIOs and IT to focus more on where AI can deliver business value, instead of developing and supporting the underlying technologies.

The paradigm shift suggests that CIOs should run a more product-based IT organization that focuses on improving customer experiences and leveraging AI to drive profitability. CIOs should also expect significant pressure from boards to reduce IT’s spend by automating more operations, leveraging service providers, and aggressively reducing technical debt.

Does AI spell the end of software development?

Boris Cherny, member of the technical staff at Anthropic, recently claimed that Claude is writing nearly 80% of Anthropic’s code, with a lot of human code review, acknowledging that some of the code still needs to be handwritten. Satya Nadella, CEO of Microsoft, estimates AI writes 20-30% of the company’s code.

If you don’t trust the major AI providers about the impact of gen AI on coding, then consider these reports:

• In the 2025 Stack Overflow Developer Survey, 84% of respondents are using or planning to use AI tools in their development process.
• DORA’s Impact of Generative AI in Software Development reports that 75% of respondents reported positive impacts of gen AI on their productivity, but 39% of developers trust the quality of gen AI output only “a little” or “not at all.”
• In Qodo’s 2025 State of AI Code Quality, 70% of development teams claiming improved productivity also report improved code quality.

Software developers are using gen AI to write, refactor, test, and document code. But questions remain whether developers are ready for emerging agentic AI software development, including agent-to-agent orchestration, AI-generated data visualizations, and using AI to reduce technical debt.

Joe Puglisi, growth strategist and fractional CIO at 10xnewco, offered this pragmatic advice: “I think back to the days when you wrote an assembly and it took a lot of time. We introduced compilers, higher-level languages, and now we have AI that can write code. This is a natural progression of capabilities and not the end of programming.”

The paradigm shift suggests CIOs will have to revisit their software development lifecycles for significant shifts in skills, practices, and tools.

“AI won’t replace agile or DevOps — it’ll supercharge them with standups becoming data-driven, CI/CD pipelines self-optimizing, and QA leaning on AI for test creation and coverage,” says Dominik Angerer, CEO of Storyblok. “Developers shift from coding to curating, business users will describe ideas in natural language, and AI will build functional prototypes instantly. This democratization of development brings more voices into the software process while pushing IT to focus on oversight, scalability, and compliance.”

Does AI spell the end of IT operations?

What will AI’s impact be on IT operations, ITSM, and end-user computing? Will data centers go dark, like some of the dark factories in China? Will IT service management become completely self-service and fully automated, leaving a non-existent tier-one support and significantly fewer people in tiers two and three? Will devices come with installed AI agents, minimizing the work required to configure and patch them?

“As AI takes over more tasks, the company’s internal and external operations will increasingly rely on software agents,” says Nikhil Mungel, head of AI engineering at Cribl. “For IT, this means shifting focus from managing physical endpoints like laptops to ensuring virtual agents running in the cloud stay compliant and secure.”

It may be hard to envision a zero-human IT service desk, but a combination of automation and AI capabilities will likely shift responsibilities and skillsets. The service desk will likely shift from responding to tickets to providing oversight on how AI agents respond to them.

“The overhead of ITSM tickets and rigid approval flows won’t survive much longer,” says Jimmy Mesta, co-founder and CTO of RAD Security. “AI systems will auto-triage alerts, generate risk assessments, and suggest or implement remediations directly, and infrastructure will become more self-healing, especially in the cloud.”

CIOs should prepare for AI agents in IT Ops, but it’s unlikely to spell the end of its role. The main barrier for IT Ops in adopting AI agents will be legacy systems, integration gaps, undocumented workflows, and other technical debt.

“ITSM will shift to predictive self-service, cloud infrastructure will become increasingly autonomous, and end-user computing will center on conversational interfaces that make traditional apps feel outdated,” says Jonathan Zaleski, director of technical architecture at HappyFunCorp. “As applications evolve into intelligent, adaptive agents, IT’s role will expand to include AI governance, ethical oversight, and strategic orchestration. Managing systems won’t be enough, and security models will need rethinking, as AI agents interface directly with systems and users.”

We can also look to the past to project the future. Cloud computing was supposed to end IT Ops, but over a decade of transformation, the cloud has increased the scope, scale, security, and risks of running IT systems. CIOs will need AI to help manage increased complexity, and there will be new responsibilities to manage the operations around AI agents. But a fully automated IT Ops seems less likely in the near term.

How will AI transform the digital workforce?

CIOs can also look at how low-code development and citizen data science have evolved to help forecast gen AI’s impact in their organizations. Both transformations help shift what was IT-exclusive work in building applications and data visualizations into development capabilities accessible by tech-savvy business users. But CIOs quickly realized the required supportive IT functions of a center of excellence in governance, integration, technical support, and quality assurance.

Liav Caspi, CTO of Legit Security, says, “Low-code will evolve into AI systems that generate apps from prompts, replacing drag-and-drop with iterative prompt-review cycles.”

CIOs should plan for how AI is expanding technical capabilities by shifting them left into business functions. The transformation will create new opportunities for delivering AI capabilities, but will also require IT to take on new responsibilities.

“Generative AI is redefining virtually every function within organizations by shifting the role of the workforce from creation to curation, and this includes IT,” says Marcus Torres, chief product officer of Quickbase. “AI is empowering teams across the business to deliver outcomes faster than ever imagined, but with that acceleration comes new complexity of custom, unstandardized solutions built outside governance models.”

Many CIOs updated their data governance functions to support new areas of AI governance. Similarly, the techniques used for turning shadow IT into a competitive edge must be expanded to avoid rogue AI and govern the expanding agentic AI ecosystem.

“Simplifying complexity and managing chaos has always been part of the IT charter, and that’s not going to go away with the adoption of AI agents,” says Rishi Bhargava, co-founder of Descope. “If anything, the shadow AI agent problem will lead to new IT and security responsibilities to ensure AI adoption doesn’t come at the expense of an increased risk surface and compliance challenges.”

So, will AI end IT as we know it?

A glass half empty points to a major paradigm shift that will erode many IT jobs, while a half full one suggests how IT must step up to new opportunities and responsibilities.

There’s no doubt that CIOs must prepare to staff emerging gen AI roles such as AI change agents, gen AI business analysts, and workplace futurists. CIOs will also need to rethink their digital transformation strategies for the gen AI era. But CIOs who stagnate and manage IT to pre-AI expectations may find that it’s the end of IT as they know it.