With everything moving at breakneck speed, how do you keep quality rock-solid?

The 2024 World Quality Report breaks down what’s working (and what’s not) so you can hit the ground running in 2025. From tightening up data accuracy to making automation actually work, the focus on quality has never been sharper.

Here’s what every organization needs to keep quality strong, steady, and ready for what’s next.

What is the World Quality Report?

The World Quality Report is an annual analysis of global trends, practices, and challenges in Quality Engineering (QE) and software testing, produced by Capgemini, Sogeti, and their strategic technology partner OpenText. 

Now in its 16th edition, this is the only global report that compiles insights from thousands of industry professionals across sectors to shed light on how organizations are approaching quality in an increasingly complex digital landscape. 

It covers key areas like test automation, data quality, Agile practices, and sustainability, aiming to help companies improve their QE strategies, adapt to new technologies, and meet rising standards for business performance, compliance, and customer satisfaction.

World Quality Report 2024: Trends and challenges for the quality landscape

The World Quality Report 2024 addresses the evolving landscape of quality engineering and the challenges organizations face in adopting it, especially within the agile lifecycle. According to the report, there’s a significant gap between the perception of quality engineering’s importance and its strategic value to business success. 

Key challenges in adopting quality engineering into the agile process include lack of automation, insufficient skills among quality engineers, and slow quality engineering processes. These issues directly impact how businesses can optimize their quality assurance processes and leverage continuous improvement to boost business outcomes.

Here are some of the pillars the World Quality Report focuses on this year:

1. The transformation of agile quality management
2. Test automation and process efficiency
3. Data quality as a pillar of QA
4. Sustainability in quality
5. Sector-specific quality engineering needs
6. Intelligent product testing and validation

The transformation of agile quality management 

As agile methodologies dominate the software development lifecycle, the role of quality engineering has shifted. No longer just a final checkpoint, quality engineering is now integrated into each phase of development, particularly in agile environments. 

However, according to the key findings of the World Quality Report, many organizations still face difficulties embedding quality engineers into agile teams. A key finding is that 56% of companies don’t see quality engineering as a strategic activity, which slows down the adoption of more agile and efficient processes.

The Skills Gap: AI and Gen AI Expertise in Demand

With more responsibility in agile environments comes the need for more specialized skills. QA teams embedded in agile are increasingly expected to bring AI and Gen AI skills to the table—a challenge when 66% of organizations are struggling to find the talent. 

Quality pros who can keep up with agile demands while understanding advanced automation tech are a hot commodity, so many companies are focusing on upskilling to bridge the gap. 

The learning curve may be steep, but the payoff is big when teams can adapt to both agile practices and new tech.

Source: WQR 2024

Here are the core challenges of integrating QA into agile:

• As noted, 56% of organizations don't view quality engineering as strategic, meaning quality engineers often lack a seat at the decision-making table. This disconnect limits the broader impact of quality efforts on business assurance and digital core reliability.
• Another 56% of companies believe their quality engineering process is under-automated, slowing development cycles and reducing efficiency. Organizations are struggling to fully implement quality engineering lifecycle automation, which is essential for meeting the speed demands of modern agile teams.
• A further 53% of companies cite insufficient engineering skills among quality engineers, particularly around AI solutions and generative AI adoption. This skills gap hinders the effectiveness of quality engineering in ensuring seamless customer experiences and optimized testing for digital core solutions.

Test automation and process efficiency

The World Quality Report 2024 puts automation front and center, and for good reason. With 71% of companies using AI-driven tools to handle repetitive tasks like test data generation and test analysis, automation is speeding up processes left and right. 

Why automation matters more than ever

Automation is a game-changer when done right. And much like the World Quality Report 2023, this year's edition also underlines this fact. For the organizations that manage to get it rolling, it’s reducing manual testing by up to 62%. That means faster releases, fewer errors, and less firefighting when something inevitably breaks. 

But the key is a clear strategy for quality engineering lifecycle automation. Without one, even the best tools will feel more like duct tape than a solution. 

But—and there’s always a but—legacy systems are throwing a wrench in things. 

A hefty 64% of companies say their old tech is holding them back from achieving proper automation. Without a solid plan to bring their tech stack into the 21st century, these companies will continue to struggle with efficiency.

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Data quality as a pillar of QA 

Data is everything in today’s digital world, but only if it’s good data. The report shows that 64% of organizations see data quality as a critical part of their QA strategy. 

And let’s be real, if your data is garbage, your insights, predictions, and even AI solutions are going to be garbage too. High-quality data ensures that every decision—whether it’s about a product feature or a business strategy—is based on reliable, accurate information.

Challenges in data management

Managing data is where things start to get messy. Only about half of companies have proper frameworks for data governance, which means there’s a lot of guesswork happening when it comes to ensuring data quality. QA teams are stepping up, but without clear business stakeholders taking ownership, it’s tough to ensure continuous improvement in this area.

The good news? Companies that get data quality right see big payoffs in terms of better product decisions and fewer compliance headaches. With strong quality assurance processes for data, businesses can optimize their entire quality ecosystem, making everything from intelligent testing to cloud testing more effective. 

In industries like MedTech and finance, where accuracy is everything, non-functional aspects like security and privacy become much easier to manage with reliable data.

Sustainability in quality 

Sustainability has gone from a corporate buzzword to a business imperative, and QA is no exception. 58% of organizations in the World Quality Report 2024 say that sustainability is a priority, but only 34% have actually put sustainable practices in place. 

So, what gives? It turns out that quality assurance processes are often overlooked when it comes to eco-friendly initiatives.

If companies are serious about going green, they need to start incorporating Green IT KPIs into their QA processes. This means finding ways to cut down on resource-heavy testing methods, optimizing cloud testing, and reducing the environmental footprint of their testing function. 

The report suggests that continuous testing and service virtualization are key to reducing waste and improving efficiency. It’s not just good for the planet—it’s good for business too.

Sector-specific quality engineering needs

The World Quality Report 2024 highlights the different ways various industries like healthcare and finance are tackling quality engineering. While both sectors deal with strict regulations and high stakes, their challenges—and the tech they’re using—are pretty unique. Let’s break it down.

Healthcare and life sciences: precision and compliance, or bust

In healthcare, there’s no room for error. With 60% of companies battling tough regulations like the FDA’s, compliance is their biggest headache. Add to that the need for rock-solid data security (because no one wants patient info floating around), and you’ve got a high-pressure environment. 

That’s why 55% of healthcare and medtech companies are turning to AI and intelligent testing to make sure their devices work flawlessly in real-world situations. Safety isn’t just a priority—it’s life or death.

Financial sector: the growing demand for mid-level and senior professionals

Financial institutions are moving away from relying on a single region, like India or the US, for IT outsourcing. About 50% are shifting resources to Latin America (LATAM) to reduce costs and spread operations across different time zones. However, challenges like language barriers and skill shortages in advanced IT tools need to be addressed.

Although the financial sector has been cautious about AI due to data security concerns, Generative AI (Gen AI) is gaining traction. AI is being used to automate tasks like test scripts and code generation, improving efficiency and productivity across the board.

With AI taking over repetitive tasks, the need for entry-level roles is shrinking. Instead, there's a growing demand for mid-level and senior professionals with expertise in both Quality Engineering and AI-driven tools. The integration of Gen AI is transforming how financial institutions approach quality, pushing for more specialized skills and advanced testing techniques.

Intelligent product testing and validation 

With the rise of smart, connected products, intelligent product testing has become more critical than ever, especially in high-stakes industries like finance and medtech. 

According to the World Quality Report 2024, 55% of organizations are now relying on AI-driven tools to help test complex, multi-system products. 

In finance, this might involve testing sophisticated AI algorithms for fraud detection, while in medtech, it could mean validating medical devices that need to interact seamlessly with healthcare systems.

Key takeaways from the World Quality Report 2024

The World Quality Report 2024 underscores a fundamental truth: quality engineering is no longer a back-office function—it’s a critical driver of business success. From test isolation and test prioritization to adopting AI solutions and addressing the engineering skills gap, QA leaders must focus on optimizing processes, automating where possible, and ensuring data quality to keep pace with demanding customer experiences. 

Here’s what you should keep in mind from this report:

• 68% of organizations are now using Generative AI in their quality engineering processes, moving beyond mere experimentation. AI is being heavily used for test reporting and defect analysis.
• 64% of companies see data quality as critical, but many still don’t have proper frameworks in place to manage it effectively.
• Test automation has grown to 44% as companies adopt more AI and cloud-native technologies, driving faster and more efficient testing.
• 21% of testing budgets now go to validating intelligent products, with a growing focus on ensuring complex AI systems work properly.
• In sectors like the public sector, predictability in testing—ensuring projects stay on time and budget—is more critical than speed or cost.
• Although 58% of organizations prioritize sustainability, only 34% have fully implemented green practices in their testing processes.
• Companies are investing in upskilling quality engineers to handle new technologies like Gen AI, as demand for more technical skills increases.