Unleashing potential: The business benefits of AI-first software engineering
In a fast-moving, AI-driven world, many engineering organizations find themselves at a crossroads. Despite their teams working harder than ever, companies often face increased delivery times, rising costs and challenges retaining top talent. Our data suggests that up to 70 percent of engineering time can be wasted, potentially leading to losses of at least $15M annually per 1,000 developers.
This is where the power of AI-first software engineering transformation comes into play. By transforming engineering organizations through removing friction points, establishing clear visibility via insights dashboards and implementing AI-powered best practices, significant improvements are possible.
How an AI-first approach can transform your business
AI-first software engineering transformation optimizes and accelerates all the phases of software delivery lifecycle — across product definition, requirements gathering, design, code generation, testing and deployment.
Through intelligent automation, metrics and measurement framework and continuous feedback loops, teams can generate business value incrementally using short cycles. The most successful implementations use a business lens for iterative value generation, enabled by creating the right guardrails of AI governance and good engineering practices.
Embracing this approach can deliver extraordinary business value:
- Accelerated delivery cycles: AI-powered workflows can rapidly transform ideas into production. Instead of cycles taking weeks, delivery can move to hours, providing consistent, measurable value across the software lifecycle. This can also mean improving deployment cadences from weekly to daily.
- Enhanced innovation focus: By freeing software engineering teams from manual processes, they can concentrate on high-value, creative problem-solving. This shift allows teams to drive strategic business impact, supported by AI-embedded tools.
- Optimized developer experience: Streamlined self-service platforms and unified workflows can reduce complexity. This enables teams to work faster, onboard quickly and collaborate effectively, fostering a future-ready software engineering culture.
- Increased efficiency gains: Data-driven insights, deployment automation and operationalized AI help eliminate inefficiencies. This ensures seamless operations and sustained improvements, contributing to lasting organizational growth and agility. Overall, this can lead to optimizing engineering costs by 20–35 percent while increasing output.
Real-world impact: Client success stories
These benefits are not just theoretical. Here’s how taking a strategic approach to engineering effectiveness and AI-enabled practices has helped us drive remarkable outcomes for our clients:
TBC Bank: Embedding engineering effectiveness
Georgia’s leading financial institution, TBC Bank, sought to accelerate processes and continuously improve across its technology and delivery teams. By engaging with Thoughtworks and focusing on embedding engineering effectiveness, they identified bottlenecks and mapped workflows, particularly centering on testing. Using a “vertical thin slice” approach with pilot squads, they implemented a transformation process involving baselining, structured learning, pairing and handover.
The results for the pilot squads were significant:
- A 50 percent reduction in cycle time.
- A 90 percent decrease in production bugs for one banking product.
- API test feedback times falling from three minutes to just 15 seconds.
- Overall test times decreased from 25 minutes to just 10 minutes.
These improvements fostered a “shift left” mindset and a culture of continuous improvement, empowering teams to sustainably enhance efficiency, quality and collaboration. This initial success built confidence to scale these changes across the wider organization.
Top 10 US bank: Adopting AI-enabled software engineering
A top 10 US bank aimed to maintain its competitive edge through continuous innovation. Recognizing the complexity of adopting new technologies at scale within a large organization and strict regulatory requirements, they sought recommendations for DevEx and Developer Productivity initiatives, specifically exploring the potential of high-value genAI tools.
The engagement focused on adopting AI-enabled software engineering for internal developers and identifying valuable use cases. GenAI’s potential was recognized for offering significant improvements to engineering effectiveness, including decreasing complexity, increasing quality and reducing the cycle time of software delivery and experimentation.
Thoughtworks delivered a comprehensive report and a configurable roadmap for genAI initiatives, which would enable:
This strategic foundation is now being executed by the bank to inform their genAI tooling adoption decisions.
NEO: Award-winning engineering portal reimagines developer experience
Thoughtworks developed NEO, an internal engineering portal, to address developer inefficiencies. The platform streamlined workflows, cutting down development time from months to days. NEO provides self-service capabilities, core asset discovery and standardized processes, resulting in:
By automating routine tasks and introducing an “Internal Open Source” model, it reduced frustration and improved developer effectiveness. As a result, 90 percent of developers felt more effective, leading to higher engagement. NEO won a CIO 100 award, recognizing its innovation and technical excellence. The platform has become the default for new product development at Thoughtworks.
The path forward
As these client stories demonstrate, embracing AI-first software engineering is not just about adopting new tools; it’s about a fundamental transformation of engineering organizations. By focusing on removing friction, enhancing visibility and implementing AI-powered practices, organizations can achieve accelerated delivery, enhanced innovation, optimized developer experience and significant efficiency gains.
Originally published at https://www.thoughtworks.com.
