Agentic AI is Reshaping the Software Engineering Sector
AI Is Accelerating Demand and Redefining Roles
Agentic AI is transforming the software engineering landscape in ways that are both exciting and complex. Contrary to the common narrative that AI will reduce the need for human developers, we believe it will increase demand for engineers who can build and manage intelligent, context-aware applications.
Enterprise customers are already expecting measurable productivity gains from tech services vendors. As a result, routine tasks—such as commoditized quality engineering services currently performed by low-skilled engineers—may be fully automated soon.
Yet, despite AI’s growing role, the ability to deeply understand complex problems and deliver innovative solutions remains uniquely human. Tools like GitHub Copilot, Cursor, and ZedAI are powerful, but they require significant contextualization based on each client’s business logic and technology infrastructure. Human oversight is still essential to ensure quality, relevance, and alignment with business goals.
From Augmentation to Autonomy: What’s Next?
In the short term, agentic systems will continue to augment developers by streamlining tasks and improving efficiency. Over time, these systems will become more autonomous—capable of executing entire workflows with minimal human intervention.
However, adoption will vary across industries. Regulated sectors like financial services and healthcare, with complex IT environments, will likely move more cautiously. In contrast, agile verticals such as retail and consumer goods are already embracing these advancements.
In this context, data engineering is becoming increasingly critical. Clean, AI-ready data is now a strategic asset. Most current infrastructures lack the intelligence and contextual awareness needed to fully leverage it, driving the need to modernize architecture for faster development cycles, reduced overhead, and improved customer experience.
A New Operating Model for Services Firms
We’re witnessing a fundamental shift in how enterprise technology is structured. AI is becoming the operating system of the modern enterprise—embedded across infrastructure, productivity tools, governance frameworks, and creative processes.
This transformation challenges the traditional services model, where growth was tied to headcount. For example, Persistent and Coforge added 3% and 4% employees respectively last quarter, while achieving 4% and 9% revenue growth. This demonstrates that the firms leading in this new era are those building data-to-agent operating models, rather than optimizing legacy, people-based approaches.
As technology budgets begin to expand and discretionary spending returns, services firms are restructuring delivery models to accommodate AI. The push for efficiency gains is driving a shift toward outcome-based engagements and shared accountability.
For investors and acquirers, this signals a new benchmark for asset selection and valuation. Companies with scalable AI infrastructure, proprietary data assets, and real-world automation use cases are commanding greater interest and higher multiples.
The Takeaway
Services firms that move quickly to embed AI into the core of their business will not only lead the next wave of enterprise transformation, but they will also define what it means to be valuable in the age of intelligence.
Contact the Author
Managing Director, Clearsight Advisors
New York, NY
Sources: Gartner, U.S. Bureau of Labor Statistics (April 2025), Company Websites, Gartner Applied Sciences Journal: Saklamaeva and Pavlic
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