Capturing Enterprise AI ROI Without Undermining Developer Value

The enterprise AI revolution is no longer a distant promise but a present-day imperative. As organizations race to harness artificial intelligence for competitive advantage, a critical question emerges: How can enterprises maximize ROI from AI tools while preserving the irreplaceable value of human developers? The answer lies in strategic alignment—embedding AI as a collaborative partner rather than a disruptive force. This approach is exemplified by JetBrains CEO Kirill Skrygan, who envisions a future where AI enhances developer productivity without eroding the dignity of engineering. By integrating agentic AI trends and prioritizing developer upskilling, enterprises can unlock sustainable returns while fostering innovation.

Kirill Skrygan’s Vision: AI as a Collaborative Force

JetBrains’ CEO, Kirill Skrygan, has long advocated for a human-centric approach to AI in software development. According to Skrygan, AI will not replace developers but will instead evolve their roles toward higher-value tasks such as monitoring AI outputs, refining system behavior, and designing complex workflows [1]. This vision is already materializing through JetBrains’ AI Assistant and coding agent, Junie, which are now embedded in its IDEs. These tools offer features like code completion and intelligent suggestions, aiming to improve productivity while maintaining the developer’s central role in the creative process [2].

Skrygan emphasizes that AI tools must be controllable, transparent, and integrated into existing workflows. He challenges the notion that natural language will replace structured programming languages like Kotlin, arguing that industrial-scale software development still requires precision and structure [6]. Instead, JetBrains is evolving Kotlin to serve as a “design document language” that translates into executable code, ensuring that AI remains a tool for amplifying human expertise rather than a standalone solution [4].

Agentic AI: The Next Frontier in Enterprise ROI

Agentic AI, characterized by autonomous decision-making and multi-step workflow execution, is emerging as a pivotal force in enterprise software development. By 2025, agentic AI systems are designed to act independently, adapt in real time, and integrate seamlessly with core systems like CRM and ERP platforms [1]. According to Gartner, agentic AI is the top strategic technology trend for 2025, with adoption expected to grow from less than 1% of enterprise applications in 2024 to 33% by 2028 [5].

The ROI from agentic AI is becoming increasingly tangible. Enterprises report efficiency gains of 25% to 40% in productivity and process optimization, driven by automation of repetitive tasks and proactive decision-making [1]. For instance, agentic AI in enterprise IT has demonstrated measurable outcomes such as reduced mean time to resolution (MTTR) and lower ticket volumes [4]. However, this shift also introduces challenges, including the need for governance frameworks like TRiSM to ensure transparency and accountability [1].

Developer Upskilling: The Human Side of AI Integration

The success of agentic AI hinges on a workforce equipped to design, manage, and oversee autonomous systems. Developer upskilling strategies must focus on AI orchestration, reasoning, and integration with enterprise workflows [1]. This involves retraining developers to work with large language models (LLMs) and tools like Auto-GPT and LangChain, while also fostering cross-functional collaboration to break down silos [3].

Enterprises must invest in frameworks that support scalable AI adoption. For example, agentic AI platforms that enable seamless integration with existing tools and APIs are critical for achieving ROI [3]. Additionally, prioritizing automation of high-volume, repetitive tasks allows developers to focus on strategic innovation, aligning with Skrygan’s vision of AI as a collaborative partner [4].

Strategic Alignment: Balancing AI and Human Value

The path to capturing enterprise AI ROI without undermining developer value lies in strategic alignment. This requires:
1. Ethical AI Integration: Ensuring AI tools are transparent, auditable, and aligned with existing workflows [4].
2. Developer-Centric Innovation: Evolving roles to emphasize oversight, evaluation, and high-level design [1].
3. Agentic AI Governance: Implementing frameworks like TRiSM to manage risks while enabling autonomy [1].
4. Continuous Upskilling: Training developers to work with agentic systems and fostering cross-functional collaboration [3].

By adopting this balanced approach, enterprises can avoid the pitfalls of overhyping AI as a standalone solution while leveraging its potential to drive productivity, innovation, and sustainable growth.

Source:

[1] Agentic AI Trends in 2025: Adoption, Market, and Future [https://www.azilen.com/blog/agentic-ai-trends/]
[2] JetBrains IDEs Go AI: Coding Agent, Smarter Assistance [https://blog.jetbrains.com/blog/2025/04/16/jetbrains-ides-go-ai/]
[3] Agentic AI frameworks for enterprise scale: A 2025 guide [https://akka.io/blog/agentic-ai-frameworks]
[4] ROI of Implementing Agentic AI in Enterprise IT: Metrics ... [https://swish.ai/roi-of-implementing-agentic-ai-in-enterprise-it-metrics-that-matter/]
[5] Gartner's Top 10 Strategic Technology Trends for 2025 [https://www.gartner.com/en/articles/top-technology-trends-2025]
[6] Is English the next programming language? JetBrains' [https://www.techzine.eu/blogs/devops/132499/is-english-the-next-programming-language-jetbrains-ceo-says-no/]