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AI is already unlocking significant financial and productivity gains for companies in the technology and telecommunications sectors. Those that are furthest along in their AI deployment are reporting productivity improvements of 15% to 25%, with some approaching 30% uplift in EBITDA, by fundamentally reimagining how work gets done—and these benefits will likely continue to grow.
AI transformations are resetting expectations for CIOs and IT organizations. Business stakeholders are demanding more, while AI-native vendor solutions require deeper integration across a broad range of data sources and network components. Many CIOs recognize they lack the capital, infrastructure, and data foundations needed to scale AI.
Technology leaders face a tough reality. AI is now critical for progress but also creating a much higher bar for CIOs and IT organizations. It requires serious investment in modern platforms, data foundations, and governance. Competitors are investing in AI to speed up R&D, boost productivity, and transform their business models. The gap is widening for those who hesitate or can’t afford to keep up.
The CIO’s mandate: Reinvent IT as a critical partner in AI transformation
Bain & Company believes CIOs play the linchpin role in the long-term success of AI transformation. At companies that have turned IT into an accelerator, CIOs focus on five key priorities.
Rethink AI product ownership, data, and platform governance. Legacy IT and data approval processes are too slow and rigid to keep pace. CIOs need to modernize their governance and compliance, streamlining decisions while balancing risk with speed.
Accelerate execution to match the pace of AI. Business stakeholders expect progress at the pace of AI innovation, which is now reaching a weekly cadence. IT must respond, shifting to rapid, agile deployment models that reduce reliance on long roadmaps and RFP cycles.
Free up investment capacity for high-impact AI
Reduce technical debt, consolidate internal software, and rationalize spending on vendors to lower ongoing costs. Redirect those savings toward the IT investments needed to capture AI’s productivity benefits while maintaining disciplined cost control.
Invest in foundational systems and data to enable AI. Deploying AI without fixing underlying data and technology foundation issues leaves gaps in architecture and data quality that can quickly become a bottleneck.
Building the foundation for full potential AI
The tech platforms that today’s systems sit on were not designed to support AI and its collaborative agents. Companies will need to redesign their technology architectures to enable the AI and agent future that’s now upon us.
Three principles in particular stand out as being critical for the success of this type of transformation.
- Modernize the core platform. Organizations will need tech foundations that make core business capabilities easy for agents to discover and use in real time. Legacy, batch-based systems need to evolve into modular, API-enabled platforms that can respond to real-time events.
- Scale data access. Scalable access to structured and unstructured data is essential. Most organizations still lack the required ingestion pipelines for unstructured sources such as documents, emails, voice recordings, images, videos, and call transcripts. These data sources hold the information that agents need, particularly in manual or exception-driven processes where necessary knowledge often resides outside core systems of record or even outside the organization.
- Ensure interoperability of agentic services. As agents roll out across the tech stack, consistent interoperability standards, such as the Model Context Protocol (MCP), and frictionless integrations will be critical for breaking down silos and capturing the full value of agentic AI.
In technology and telecommunications companies, AI isn’t an overlay on yesterday’s stack. It’s a stress test of your architecture, data, and operating model. The companies pulling ahead didn’t just find a better pilot. They fund modern IT at higher levels, then translate their spending into reusable platforms, cleaner data, and faster deployment.
Bain & Company sees the decision for CEOs and their technology leaders isn’t whether they can afford to modernize. It’s whether they can afford to fall further behind while competitors industrialize AI. The mandate is to reallocate, simplify, and invest. If you don’t, the organization will remain trapped in a legacy stack that can’t support what’s coming.