AI has long promised to unlock widespread operational efficiencies, automate workflows and generate key business insights for software development teams.
Although the technology is now sophisticated enough to deliver on these fronts, most organizations today are finding implementation a major challenge. In fact, its potential is being curtailed by legacy digital infrastructure, with enterprises buckling under the weight of accumulated technical debt.
Fragmented toolchains, brittle CI/CD pipelines, and sprawling architectures have turned software delivery into a slow, risk-laden process.
As a result, tools like AI copilots can only deliver surface-level automations that fail to deliver transformative results. Meanwhile, every new software release adds friction rather than momentum.
Let’s take a closer look at the application challenges plaguing AI adoption in the enterprise and the solutions on offer.
There has been widespread demand for AI copilots over the past year, but the first wave of adoption has highlighted notable shortcomings when it comes to enterprise-level software development.
Most AI tools operate in isolation. This can be helpful in narrow tasks, but disconnected from the broader engineering system. They accelerate individual steps while ignoring the architectural, governance, and workflow constraints that actually determine delivery performance at scale.
To illustrate, the 2024 DevOps Research and Assessment (DORA) report from Google offers a sobering reality check. While GenAI tools delivered moderate improvements in documentation quality, code quality, and code review speed, enterprises experienced declines in overall delivery throughput and delivery stability. Even more telling: 39% of respondents reported low trust in AI-generated code.
In short, copilots assist developers. Enterprises need something bigger.
To make AI truly useful as a development tool and address the challenges associated with fragmented digital infrastructures, the technology needs to work across all layers and not in silo.
What organizations truly need is engineering with intelligence where AI is embedded directly into architecture, workflows, governance, and code, not bolted on as an afterthought. Intelligence must be systemic, not episodic.
Ness Digital Engineering (Ness) specializes in AI, cloud-powered solutions, and product engineering to drive innovation, modernize systems, and deliver measurable business outcomes.
The company has built a custom workbench, known as ATONIS, that weaves intelligence across the entire Software Development Lifecycle (SDLC), transforming how software is planned, built, tested, delivered, and evolved.
Now, the reach of this powerful tool is set to accelerate globally as Vikas Basra takes the helm as the Chief Technology Officer (CTO) for ATONIS by Ness.
In his role as CTO, Vikas Basra brings leadership and a forward-thinking technology roadmap to ATONIS, propelling the company toward transformative AI-driven solutions, enhanced enterprise value, and sustained global growth. His expertise is set to strengthen innovation, operational efficiency, and market leadership across the organization.
Before joining Ness Digital Engineering, Vikas Basra held senior leadership roles at a number of global technology firms, driving large-scale AI, GenAI, Agentic AI, and modernization transformations.
His career is marked by pioneering enterprise AI platforms, building high-performance engineering teams, and generating measurable business impact across Fortune 500 and PE-backed organizations. Vikas has consistently delivered productivity gains, cost optimization, and operational excellence at scale. Now, Vikas will bring this wealth of experience to support the technical roadmap for the company and the ATONIS initiative.
Designed as a full-lifecycle AI workbench, ATONIS amplifies human productivity from ideation to deployment and beyond. By combining automation, GenAI, and data-driven insights, it eliminates inefficiencies that traditionally slow teams down while improving quality and predictability.
Unlike traditional tools that operate in silos, ATONIS delivers real-time visibility into speed, quality, and risk across the engineering lifecycle. By integrating best-of-breed partnerships with proprietary accelerators, ATONIS helps organizations achieve tangible results.
These gains aren’t about replacing engineers—they’re about removing friction so teams can focus on higher-value work. AI copilots are a starting point—but they are not the destination. The future belongs to organizations that embed intelligence into the very fabric of how software is engineered.
The solution enables that future by turning AI from a collection of tools into a cohesive, enterprise-grade engineering system—one that restores trust, accelerates delivery, and scales modernization with confidence.
According to Ness, engineering with intelligence isn’t optional anymore. It’s the way forward.
Article’s featured photo of Vikas Basra
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