With over two decades of experience in software development and testing—and of conversations with industry leaders across the field—I’ve found that many of these challenges can be addressed by building a quality testing culture where speed and stability coexist. Here are six steps to help create that kind of culture:
1. Quality As Shared Ownership, Not Isolated Function
When you isolate testing, you create bottlenecks that slow releases and fragment accountability. Developers write code, testers find bugs and the cycle repeats without anyone truly owning the user experience.
But, to truly understand the user experience, teams should include testing in the design phase, encourage developers to own their code quality and make quality metrics visible to the entire company. When everyone owns outcomes, teams stop blaming the bug on someone and start preventing the next one.
2. From Execution To Orchestration
The infrastructure you build determines whether your team writes more tests or avoids testing because it’s too slow. This becomes especially apparent at scale, where approaches like sequential testing often create bottlenecks.
3. AI Augments, Not Replaces, The QA Engineer
I hear a lot of fear that AI will replace QA engineers. Even though I’m working on building agentic testing systems, I disagree. AI will not replace the tester. It will only change the job description.
Instead of QA engineers writing repetitive test scripts, they’ll move to strategic work like designing complex scenarios, focusing on exploratory testing that requires human intuition and managing self-healing tests where AI adjusts tests when application code changes.
The tools can act as virtual users that understand natural language. This means humans can stop writing code for every single test case. Instead, they can focus on strategic ways to use AI to generate complex test scenarios and let AI handle the maintenance of test scripts.
This frees your engineers to think about what machines cannot do yet and allows your team to be more intelligent about where they spend their time.
4. Data-Driven Risk Prediction
Most engineering teams sit on massive datasets but use them reactively rather than strategically. Every test run, every failure pattern and every deployment generates logs that can help to understand where your next production incident will occur.
Strong quality cultures analyze this historical execution data to identify flaky tests, unstable code sections and deployment patterns that correlate with incidents. Machine learning algorithms can then help to detect patterns human testers miss, moving teams from reactive debugging to proactive prevention.
A strong understanding of why code fails can allow you to move from reacting to bugs to preventing them.
5. Testing Real User Conditions
In the past, testing was simple. A feature worked, or it did not.
Today, your users access applications on smart TVs, tablets, aging phones, 4G networks and spotty Wi-Fi. A feature might work perfectly on a developer’s fast laptop. That does not mean it works for the user. You must test the actual digital experience. If your app is slow or glitches on a specific device, the user will leave.
In other words, your testing strategy must match the real world. You cannot rely only on simulators. You need to test on the actual devices and browsers your customers use. This is the only way to guarantee a consistent experience.
6. Respecting Engineering Teams Through Better Tools
Culture is about people. You cannot build exceptional products with burnt-out engineers working on inadequate infrastructure. Developers want to ship code. When you force them to use slow or outdated testing environments, their morale suffers and productivity drops.
Giving teams the right environment, on the other hand, can impact the entire organization. In fact, according to McKinsey research, companies with higher developer velocity experience four to five times faster revenue growth.
Investing in reliable, fast testing infrastructure signals how much you value your team’s time. When developers feel supported, they take pride in their work and ownership of quality naturally follows.
Quality: An Endless Game
The software industry has moved from monoliths to microservices to AI-augmented development, with each transition introducing new failure modes and testing challenges. In this environment, the ability to release stable software quickly is a strategic capability, not only an engineering concern.
With intelligent orchestration, data-driven decision making and a unified culture, you can build an organization that thrives on change, which can underpin long-term resilience and sustained performance in software development.
Finance At The Forefront: Leading Transformation Amid Uncertainty And Innovation
Finance leaders are transitioning from traditional back-office roles to strategic drivers of enterprise growth, navigating economic uncertainty and leveraging AI. They prioritize tech adoption, despite ROI challenges, and focus on upskilling talent, which positions finance at the forefront of innovation to build future-ready organizations.Show More
CFOs and other finance executives continue to face growing urgency to build for the future, as technologies like AI reshape business and the speed of innovation accelerates across industries. Yet those same leaders find themselves facing an increasingly challenging external environment: risks including economic uncertainty and supply chain disruption threaten instability for their organizations and cast longstanding strategies in a new light.
One thing is clear: finance should seize a strategic leadership role and innovate traditional tools to drive organizational growth. The days of laser-focusing on cost management and quietly supporting business priorities from the “back office” are over. Finance belongs at the forefront of enterprise growth – and the data shows this shift is already well underway. Deloitte’s inaugural Finance Trends 2026: Navigating the expanded scope of finance report dives into where finance goes from here – and what leaders can do to be successful.
Finance Leaders’ Priorities are Driving a Strategic Agenda
Today’s finance leaders are expected to juggle a number of competing priorities that span planning for external challenges to adopting new technologies and optimizing capital allocations, making their ability to act as strategic advisors increasingly vital to their organizations. Encouragingly, more than half (57%) of surveyed finance leaders reported that they play a lead role in shaping enterprise strategy for their organizations, transforming finance’s reputation from that of a “back-office” function to one that is now integral to driving enterprise growth.
Among leaders’ top priorities, two are tied for first place: planning for external challenges and adopting new technological capabilities, both of which are closely linked to financial executives’ strategic agendas.
Strategic finance leaders continue to prioritize responding to new and evolving operational and macroeconomic risks. Economic uncertainty (26%) ranked as the top risk to manage for surveyed professionals, followed closely by financial reporting (25%) and data privacy (24%). In response to these challenges, financial executives are strengthening advanced scenario planning (30%) and building more agile governance models to support faster decision-making (28%).
In every instance, finance leaders are prioritizing both challenges and opportunities and transforming them into strategic plays to help their organizations drive more business value.
AI and Technology Use is Growing – But Leaders Have an Opportunity to Do More
Technology adoption in finance is moving ahead at a rapid pace, especially among finance leaders with strategic oversight and responsibility over cost management. However, the maturity of AI solutions and implementation of them remains unique and varied, as do the savings tied to these solutions. Sixty-three percent of surveyed leaders have fully deployed and actively use AI. Yet many are still in the process of demonstrating and maximizing these investments: only 21% of financial leaders report clear, measurable ROI from their AI initiatives. Early-stage adopters cite legacy technology (41%) and justifying ROI (30%) as major adoption barriers, while those in advanced implementation stages indicated that data privacy concerns (57%) remain their greatest challenge.
Despite these barriers, leaders remain bullish on AI overall and are approaching the adoption of it with a long-term vision. Case-in-point: even though just 14% of financial executives have fully integrated AI agents, many see significant future opportunities for AI agents in sales and profitability management (48%), working capital optimization (46%), and expense management (44%).
As finance leaders continue to lean into technology — whether it is AI or cloud — it is clear they need to also keep the goal post focused on a few key areas, including demonstrating results, driving efficiencies, and developing a workforce capable of maximizing both of these important measures of success.
Talent and Skills Challenges Remain a Primary Focus for Finance Leaders
Technology is changing the face of talent across all business functions and finance is no exception. As finance leaders adopt new technologies, they recognize the need to reshape finance talent to suit their needs. Many finance leaders (64%) plan to infuse more technical skills – including AI, automation, and data analysis – into their teams in the next two years.
As they look to center these technical skills in their organizations, many leaders are pursuing specialized AI training (39%) to upskill their workforce in addition to hiring more specialized tech talent to help structure finance teams to more effectively capitalize on the combined talents of data science and traditional finance capabilities.
For many finance leaders, today’s talent concerns and how they choose to address them will undoubtedly have significant and exciting implications for what the future of finance could look like.
Where Do Leaders Go From Here?
The Finance Trends 2026 report makes clear that uncertainty and change are the baseline environment for finance professionals today, with no certainty of that changing anytime soon.
The questions on the minds of finance leaders won’t be answered overnight. But by expanding their leadership beyond the realm of the finance function, unleashing the power of AI, and thinking creatively about the talent of tomorrow, finance leaders may hope to build a finance function – and an enterprise – that is poised for growth in any environment.
https://www.forbes.com/sites/deloitte/2025/12/02/finance-at-the-forefront-leading-transformation-amid-uncertainty-and-innovation/a>