CIOs forecast all IT work will involve AI-human collaboration by 2030

Chief Information Officers anticipate that all IT work will involve artificial intelligence by the end of the decade, with a significant shift towards human-AI collaboration and autonomous AI operations.

Findings from a survey conducted in July 2025, involving over 700 CIOs, indicate that by 2030, none of the IT workload will be performed solely by humans, with 75% of tasks undertaken by humans assisted by AI, and the remaining 25% executed by AI independently.

The report underscores the need for organisations to balance two key factors: AI readiness and human readiness. Both elements are seen as crucial for uncovering, leveraging, and maintaining value from AI-based technologies.

"While not all AI is ready to deliver value, humans are even less ready to capture value," said Alicia Mullery, VP Analyst at Gartner. "AI readiness means AI can help you find value and effectively meet the needs of specific use cases. Human readiness is about whether you have the right workforce and organisation to capture and sustain AI value."

According to Gartner's analysis, the impact of AI on global employment is expected to remain neutral through 2026. However, the proliferation of AI-augmented or AI-driven tasks is forecast to generate more than 500 million net new human jobs globally by 2036, as new roles and support functions emerge to manage and advance AI initiatives.

"AI is not about job loss - it's about workforce transformation," said Daryl Plummer, VP, Distinguished Analyst, Gartner Fellow and Chief of AI Research for the Gartner High Tech Leaders and Providers practice. "CIOs should start transforming their workforces by restraining new hiring, especially for roles involving low-complexity tasks, and by repositioning talent to new business areas that generate revenue."

The recommendation to slow recruitment for low-complexity positions is aimed at improving productivity and managing expenses, but the report stresses that this alone is insufficient. For organisations to fully capture new value from AI, team members need to adapt to working with AI in fundamentally different ways, as the nature of relevant skills will evolve rapidly.

"AI will make some skills less important, such as summarisation, information retrieval and translation, as AI is ready to automate or augment these tasks," said Mullery. "But AI also creates a need for entirely new skills. These AI skills are fundamentally different from most skills. Where skills were traditionally about doing tasks better, AI skills are about making you better - a better motivator, better thinker and better communicator."

The development of these new competencies requires more than simply retraining for updated technical knowledge. Gartner recommends that organisations periodically test employees to ensure they retain critical core skills, warning against overdependence on AI tools, which could lead to the deterioration of key abilities needed in essential roles.

Evaluating AI readiness

The survey also points to the importance of comprehensive assessments of AI readiness, taking into account direct and indirect costs, technical capabilities, and vendor selection.

On financial considerations, a separate Gartner survey from May 2025 highlighted that 72% of CIOs believe their organisations are either breaking even or incurring losses from AI investments. For every deployed AI tool, companies should factor in ten additional hidden costs, alongside the expenditures required for training and managing organisational change. Gartner recommends thorough cost analyses to determine which investments to prioritise and fund.

From a technical perspective, certain AI capabilities - including search, content generation, and summarisation - are already mature, while areas such as AI accuracy and the deployment of autonomous agents require further development. Gartner analysts suggest that value delivery will remain uncertain if organisations fail to address the reliability and effectiveness of these emerging technologies. They call for building robust AI accuracy processes and piloting autonomous, multiagent AI systems tailored to business processes and revenue generation.

Vendor selection is another crucial aspect. The choice depends on the scale and purpose of AI deployments. Hyperscale providers can support extensive rollouts due to their infrastructure scale. Industry-focused start-ups are considered suitable for domain-specific applications, bringing deep expertise to immediate challenges. Research and development-led companies offer advanced AI features but may lack the scale for large enterprises. Gartner also highlights that every AI procurement decision has implications for sovereignty, and organisations are advised to consider this when making technology choices.

The report concludes that organisations looking to extract value from AI must address both technological and human factors in parallel, building technical capabilities while transforming their workforce to adapt to an AI-centric future.