How Jalasoft is Using AI in offering IT Outsourcing Services? Innovation with Responsibility

There’s no question that AI is changing how software is built. What used to take hours or days can now be done in minutes, and engineering teams have new ways to speed up testing, reduce errors, and operate with fewer delays. But for companies working with an outsourcing partner, as Jalasoft's CEO, Jorge López, puts it: "We should ask ourselves and others in the industry: Are we making informed, thoughtful decisions about AI adoption? Or are we simply following the hype?"

Because the real value isn’t in the buzz — it’s in how AI is actually used.

At Jalasoft, we see AI as a practical tool that supports our engineers. It helps them work faster, understand problems more clearly, and deliver better software, while human judgment stays firmly in the driver’s seat. Responsible use is key, and that’s exactly how we approach it.

Below, we break down how AI fits into our workflows and how it’s helping us deliver more predictable, higher-quality results for our clients.

Why AI Is Becoming Core to Outsourcing Models

AI is now an essential part of scaling engineering organizations. It accelerates work, improves quality, and reduces waste — three things every CTO cares about. As businesses adopt increasingly complex tools, they need partners who can apply AI responsibly and are not just about the hype.

That’s where Jalasoft stands out: we integrate AI directly into engineering workflows while preserving transparency, data protection, and human oversight. This balance is what differentiates mature artificial intelligence outsourcing models from vendors simply “adding AI” to their pitch.

How Jalasoft Uses AI Across the Software Development Lifecycle

We bring AI into the SDLC in ways that make our engineers faster and our clients’ products better. Because our engineers are Jala University graduates, every engineer is trained in AI fundamentals, and roughly 75% actively use AI tools in their day-to-day work — always with full client approval.

A Principle We Don’t Negotiate On: Innovation With Responsibility

For us, AI is a tool for smarter development, as it helps teams think better, not less.

We use AI to automate repetition, catch errors earlier, and reduce time spent on support tasks. But every critical decision, architectural choice, or quality gate remains in human hands: "We believe AI should enhance human potential, not replace it. That’s why we’re committed to training developers with the right mindset and practical skills to grow quickly, adapt confidently, and bridge the gap between academic learning and real-world demands," explained López.

This approach ensures clients benefit from increased efficiency without losing the craftsmanship and accountability that define Jalasoft’s engineering culture.

Where AI Creates Measurable Impact

AI-driven assistants like ChatGPT and GitHub Copilot help our engineers generate boilerplate code, understand unfamiliar libraries, and validate logic before it becomes technical debt. Used responsibly, these tools accelerate early development and improve clarity throughout the codebase. Our internal surveys show clear results: developers complete tasks 66% faster when AI is used appropriately.

Predictive Testing and Quality Assurance

Quality engineering is one of the areas where AI delivers the most visible impact. From pattern recognition to automated test creation, AI allows teams to increase coverage and reduce the time spent maintaining large automation frameworks.

We’ve seen meaningful improvements across our QA projects:

• Test generation supported by AI is 20% faster with 20% more coverage.

• Automated test generation with tools like Playwright and Selenium is 30% faster, especially during troubleshooting.

• AI-supported code generation reduces new test creation time by 20%.

• AI-powered test data generation has increased coverage by more than 40%.

• Self-healing locators (Healnium) cut maintenance time by half.

• Visual testing tools like Applitools and Percy expand multi-browser coverage without extra manual effort.

• Accessibility testing with Axe results in 70% faster defect detection.

• AI models identifying flaky tests reduce regression analysis time by 50%.

Each improvement compounds over time, giving clients faster releases, fewer bugs, and a more stable product.

Better Documentation, Faster Debugging

AI also improves the less glamorous parts of engineering — documentation, ticket triage, and debugging. Engineers use AI to clarify requirements, produce consistent documentation, and identify root causes before issues escalate.

These efficiencies translate to smoother sprints, clearer communication, and fewer rework cycles.

(To learn more about AI and Quality Assurance, read our blog post "Will AI Replace Software Testers?")

The Key Areas Where AI Impacts Outsourcing

Everything we’ve covered so far reflects how AI supports our engineers on a daily basis. But the value extends far beyond the SDLC. The efficiencies, predictability, and quality improvements created by AI also translate into a better outsourcing partnership overall. They influence how teams communicate, how work is delivered, and how quickly companies can move.

Let's review some of them:

Intelligent Document Recognition and Classification

AI can extract, classify, and validate data from large volumes of documents — dramatically reducing manual processing time and helping teams operate more accurately.

Customer Service Outsourcing with AI Chatbots and NLP

AI-enabled chatbots enhance customer support by delivering faster responses, more accurate intent analysis, and multilingual assistance — improving support quality without expanding headcount.

Data Entry and Processing Automation

Repetitive data tasks become significantly more efficient when automated. AI reduces human error, accelerates workflows, and allows teams to focus on higher-value work.

Strategic Roadmap: How Outsourcing Providers Can Thrive

AI adoption is no longer optional for IT outsourcing companies. Those who thrive will be the ones who treat it as a strategic capability rather than a task-level tool.

A sustainable AI roadmap requires:

• Clear AI governance

• Strong data privacy and protection standards

• Transparent communication with clients

• Continuous training for engineering teams

• A healthy balance between human expertise and intelligent automation

Jalasoft’s approach incorporates these pillars, ensuring clients get innovation anchored in responsibility and oversight.

Benefits for Companies That Adopt AI-Driven Outsourcing

Companies that partner with AI outsourcing companies like Jalasoft benefit from:

• Faster time-to-delivery enabled by automation

• Higher product quality due to predictive testing

• Lower costs because repetitive tasks require less manual effort

• Greater scalability as AI reduces operational bottlenecks

• Continued innovation from our internal R&D teams

• Human oversight to ensure AI outputs meet enterprise-level standards

Future Trends in AI Solutions and IT Outsourcing Services

AI will continue to redefine how outsourcing operates, pushing providers to stay ahead of new expectations and technical capabilities. Over the next few years, enterprises will increasingly adopt AI-enabled applications to automate internal workflows, making AI application development services and custom AI development services more essential. We will also see hybrid teams become the norm — engineering talent collaborating with AI agents that handle repetitive or time-intensive tasks. At the same time, clients will demand stronger ethics, observability, and security around AI, prioritizing partners who can explain how models work, how data is handled, and how decisions are validated.

Jalasoft is investing proactively in internal prototypes, training, and R&D initiatives to stay aligned with these expectations and help clients prepare for the next generation of AI-powered outsourcing. As our CEO, Jorge López, explains:

“Our R&D team is actively experimenting with AI tools — but in a controlled, structured environment. We’re not blindly integrating AI into every workflow. Instead, we’re partnering closely with our clients to define when AI makes sense, and how it should be applied.”

This approach ensures that innovation never outpaces responsibility, and that AI adoption evolves hand in hand with the needs, goals, and security requirements of the companies we support.

How Jalasoft Ensures Responsible AI Use

Responsible AI adoption is the foundation for a successful business; that's why, at Jalasoft, every decision we make around AI is anchored in client trust, security, and transparency.

Our practices include:

• Human-in-the-loop validation at every stage

• Client-controlled authorization for AI tool usage

• Strict anonymization and data protection

• GDPR-compliant processes

• Clear reporting on when and how AI is used

This ensures clients retain full control while benefiting from the efficiency and intelligence AI brings to engineering.

Conclusion: AI That Amplifies Human Talent

“At Jalasoft, we’ve invested in building some of the most talented engineering teams in Latin America. One lesson has become clear: technology will always change, but mindset is what endures,” says López. That belief guides the way we integrate AI, not as a shortcut, but as a strategic layer that amplifies human capability. By combining top-tier engineering talent with intelligent, well-governed AI workflows, we accelerate delivery, improve quality, and help our partners scale with confidence. Our frameworks are deliberately designed to prioritize human oversight, rigorous quality assurance, and long-term alignment with client goals, never speed for speed’s sake.

This people-first philosophy also shapes how we prepare the next generation of talent. Through Jala University, future engineers are learning to thrive in an AI-powered world. Their training includes hands-on experience with machine learning and deep learning tools such as Python, Scikit-learn, PyTorch, and Hugging Face. More importantly, they develop a practical understanding of how AI supports real engineering work across three levels: automation, augmentation, and agency.

By cultivating talent that understands both the power and the responsibility of AI, Jalasoft and Jala University are building a future where innovation is driven by skilled people, with AI as an enabler, not a replacement. As the outsourcing landscape continues to evolve, our commitment remains unchanged: responsible innovation, a people-centered approach, and unwavering engineering excellence.