By Inga Țîgai, Head of CEE Tax and Legal Technology, Partner KPMG in Romania.

This perspective emerges from two recent KPMG reports: the KPMG Global tech report 2026 Telecommunications , and the KPMG Global tech report 2026 Technology. The reports suggest that technology and telecom organizations are moving beyond experimentation and into what is described as the “Intelligence Age,” in which competitive advantage is increasingly determined not by innovation alone, but by the ability to execute at scale.

After years of massive investments, AI pilots, and ambitious digital transformation programs, many organizations are entering a new phase of the technology journey. The debate has moved on from being about whether to adopt artificial intelligence. The main question now is whether organizations can consistently translate technology investments into measurable business value.

What makes this shift particularly interesting is that confidence remains remarkably high. In the technology sector, 95% of leaders expect revenue growth over the next two years, while 89% of telecommunications executives share the same expectations. At the same time, investment in AI, cloud, data platforms, and digital transformation continues at pace across both sectors.

Yet a closer look reveals a more nuanced reality. The widespread narrative that AI has yet to deliver value is not entirely accurate. In fact, most organizations are already generating substantial returns from digital technologies. In telecommunications, 74% of organizations report realizing at least US$50 million in value from digital technologies over the past year, while AI and intelligent technologies are contributing a meaningful share of that value. Hence value is clearly being created, but the challenge now is whether that value can be repeated, governed, and scaled across the enterprise.

This is where the gap begins to emerge. While AI adoption is becoming mainstream, only around 10% of technology firms report achieving AI-driven ROI at scale. In telecommunications, 54% of organizations say they are strategically investing in AI and creating value from specific use cases, yet only 22% have succeeded in scaling deployments and generating consistent returns across multiple processes and business functions. So, the challenge remains execution.

Older systems can impede progress and technology risks cause concern

Many organizations continue to operate with complex environments, fragmented systems, and operating models that were designed for a very different era. Even as AI capabilities advance rapidly, older technology estates often prevent organizations from realizing the full benefits of their investments. The KPMG reports cite legacy complexity, technical debt, and organizational barriers as factors which continue to erode returns and slow progress.

However, despite the abovementioned disadvantages, at KPMG Tax and Legal CEE, we believe that the differentiation increasingly comes from the ability to operationalize innovation, as well as to integrate capabilities across the enterprise and with external collaborators. As the saying goes: “break the silos, build a tribe”.

The KPMG reports also suggest that technology leaders are becoming more realistic about the risks accompanying this transformation. For example, in the teleco industry, 58% of organizations now view technology as a greater source of risk than resilience. Similar concerns are emerging across other sectors. According to the Thomson Reuters Future of Professionals Report 2026, 34% of professionals use AI tools that have not been sanctioned by their organizations, creating new governance and data protection challenges. Similar themes are emerging in financial services, where recent research from the 2026 Global AI in Financial Services Report highlights that AI adoption is becoming widespread across the industry, while the pace of technological change risks outstripping organizational readiness and governance capabilities. Cybersecurity threats, rising costs, regulatory pressures, and the complexity of large-scale transformation initiatives are becoming increasingly significant concerns. As AI, automation, and interconnected digital platforms become deeply embedded in operations, the consequences of failure grow accordingly.

Human input is generally being redefined not replaced

At the same time, workforce transformation is accelerating. The telecom report shows that 91% of organizations are investing in agentic AI to support a hybrid human-digital workforce. Meanwhile, 83% are already incorporating AI-native roles into their talent strategies, and 58% report hiring people primarily for work that cannot be carried out by AI.

These figures do not necessarily mean the disappearance of human work. Rather, they suggest a redefinition of where human value is created. In such cases organizations are thinking about “delayering”. As intelligent systems take on more routine and repeatable activities, competitive advantage will increasingly depend on human capabilities. Judgment, creativity, critical thinking, relationship building, as well as decision-making in complex environments are the skills of the present and of the future for the roles that will not face delayering and will just be transformed.

Execution in practice across CEE

We see this shift in practice across KPMG in CEE, where technology is increasingly embedded into the delivery of Tax & Legal services rather than treated as a stand-alone experiment. KPMG’s Digital Gateway provides a secure environment in which clients and KPMG teams can collaborate, exchange information, access dashboards, and manage service workflows. GenAI capabilities are being applied to activities such as document analysis, information extraction, drafting, translation, and research, supported by professional judgment and human review. In parallel, solutions such as the Risk & Controversy Hub bring tax audits, requests from public authorities, deadlines, documents, and responsibilities into a structured workflow, while regional approaches to e-invoicing and SAF-T combine reusable technology with local regulatory expertise. Together, these examples show that value comes from technology as a first layer and secondly from integrating it into real processes along with the other main ingredients, such as consistent governance, clear ownership, as well as ability to scale across countries and services.

Conclusions: Effective deployment of AI is key

The key message from the KPMG reports is that the lesson has been learned that quantity is good, but quality is even better. The large number of pilots, experimentation projects, assignment of champions (or tech ninjas as some may call them) is just a phase, a basis. Then comes the question of scale. Jump and how high?

That means evaluating the options in the following areas:

• Investment in platform-based architecture or in disconnected point solutions.
• Prioritizing interoperability so data, applications, and AI systems can work smoothly together or trying to enhance legacy systems.
• Strengthening governance frameworks that balance innovation with trust, security, and compliance. This assessment is particularly sensitive for some industries in the context of the EU AI Act.
• Identifying metrics to measure the costs of technology and the correlations to demonstrable business outcomes.

The era of AI experimentation is gradually giving way to the era of AI execution. Keeping pace with change now depends on turning strategic choices into sustained enterprise impact.

Inga Țîgai, Head of CEE Tax and Legal Technology, Partner KPMG in Romania

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