AI Investment Is No Longer the Challenge—Enterprise Infrastructure Is

Artificial intelligence has moved beyond experimentation to become a strategic imperative for enterprises worldwide. However, new research suggests that while organizations are accelerating AI investments, many lack the foundational infrastructure required to support AI at scale.

According to Building Durable AI Advantage, a global study sponsored by Tata Communications and developed in partnership with Bloomberg Media Studios, 77% of enterprise leaders now consider AI a board-level priority. Yet nearly two-thirds (65%) continue to operate on legacy or only partially modernized infrastructure that was not designed for the intensive data processing, connectivity and integration demands of modern AI workloads.

The findings point to a growing disconnect between AI ambition and organizational readiness. Only 29% of respondents believe their current infrastructure can scale effectively with evolving business requirements. As AI deployments expand across functions and environments, enterprises are discovering that performance bottlenecks often emerge in foundational systems rather than the AI applications themselves.

The study surveyed 501 senior executives across North America, Europe and Asia from organizations generating more than $500 million in annual revenue. Its central conclusion is that sustainable AI success depends on the alignment of five interconnected operational areas: infrastructure foundation, system integration, workforce skills, governance and return on investment (ROI).

Researchers describe these areas as reinforcing "loops" that collectively determine whether AI initiatives generate compounding value or stall over time. When all five areas advance together, organizations are more likely to accelerate adoption and business outcomes. When one area lags, constraints can ripple throughout the enterprise.

Infrastructure Remains a Critical Challenge

The research highlights infrastructure modernization as one of the most significant barriers to AI maturity. Fewer than half of surveyed organizations report having fully modernized capabilities in key areas such as network connectivity, hybrid deployment flexibility and data architecture.

The impact is measurable: enterprises with advanced infrastructure are nearly twice as likely to report achieving high business value from AI initiatives compared with organizations relying on legacy environments.

Integration Complexity Slows Progress

As enterprises expand AI deployments, integrating new capabilities with existing systems remains a major obstacle. Twenty-eight percent (28%) of leaders identify integration with legacy platforms as a primary challenge to realizing AI value, while 38% say integration concerns contribute to delays in approval and procurement processes.

At the same time, 67% of respondents view the seamless integration of digital automation and human interactions across channels as essential for successful AI execution.

Skills Gaps Persist

Technology investments alone are not enough. Nearly one-third (30%) of organizations cite shortages of specialized AI talent and skills as a major barrier to achieving desired outcomes.

The challenge becomes even more pronounced among larger enterprises. Forty-five percent (45%) of organizations with annual revenues exceeding $5 billion report skills shortages as a significant concern, highlighting the growing competition for AI expertise.

Governance Must Enable, Not Impede, Scale

Governance frameworks are becoming increasingly important as AI deployments expand, but they can also introduce friction. Security and compliance reviews are cited by 42% of respondents as the largest source of approval delays, followed by integration concerns and procurement complexity, both at 38%.

The report suggests that as more stakeholders become involved in AI investment decisions, governance processes must evolve to maintain oversight without slowing innovation and deployment.

Measuring Value Remains Difficult

While 90% of enterprises report realizing some value from modernization initiatives, more than 60% say they have yet to achieve optimal outcomes. A key challenge is visibility into business impact.

Many organizations continue to evaluate AI, infrastructure and security initiatives separately, making it difficult to understand their combined contribution to enterprise performance. As a result, opportunities for reinvestment and scaling may be overlooked.

Sumeet Walia, President & Chief Revenue Officer, Tata Communications, said: "AI has become one of the defining business priorities of our time, but the real differentiator is no longer AI itself—it's the infrastructure and integration that enable AI to deliver value at scale. Our research shows that while enterprise ambition is accelerating, readiness remains uneven. The organisations that will lead in the years ahead are those investing in the foundations that connect people, systems, data and intelligence across the enterprise."

He adds: "AI is a tightly coupled ecosystem of compute, power, connectivity and platforms, which are no longer independent systems—they are becoming one unified infrastructure."

Source: Tata Communications

Stay Connected with ISE Magazine 

Subscribe to our newsletters and magazine for the latest telecom insights, explore the current issue for in-depth features and strategies, and register for upcoming webinars to learn directly from industry leaders.