2025 Tech Trends: Navigating AI, Data, Regulation, and an Evolving Workforce

The tech industry is undergoing a period of rapid evolution, driven by advancements in artificial intelligence, shifts in global political landscapes, and changes in market dynamics. These forces are reshaping how companies approach development tools, data infrastructure, regulatory technology, workforce strategy, and pricing models. As businesses adapt, new challenges and opportunities are emerging, requiring thoughtful approaches to remain competitive and sustainable in this evolving landscape.

The use of AI in dev tools, such as for code completion and agents capable of writing entire sections of a codebase, will continue to accelerate. This growth will be fuelled by more engineers and managers recognising the significant productivity gains these tools provide. As a result, engineers will spend marginally less time on repetitive boilerplate code, and more time on addressing complex problems that with higher impact.

AI-powered tools will also offer greater insights into legacy codebases, enabling engineers to tackle complex migrations more effectively. However, the limits of these tools will start to be more widely understood. Engineers have context not just of the task at hand, but the overall direction of a company and the interpersonal politics of a company that make very real demands on architecture. Engineering teams will start to discover in which scenarios these tools stop being useful, and where they generate low quality, unmaintainable code.

Many companies are now experiencing the frustration of over a year of executives demanding AI-driven improvements to products, only to face roadblocks caused by pervasive low data quality. As patience wears thin, we are likely to see major overhauls of data infrastructure receiving approval to address these issues.

However, companies that embark on these projects without learning from past experiences—such as the challenges of migrating from large monolithic systems to distributed architectures—risk encountering endless and ultimately failed migrations.

As this wave of data infrastructure investment unfolds, traditional skill sets in architecture and data design will re-emerge as crucial and highly sought-after. Companies will come to recognise that the legacy replacement skills developed over the last 30 years are just as essential as machine learning expertise in unlocking AI's full potential and achieving meaningful, sustainable advancements, and engineers with this experience will be in high demand.

Significant changes in the global political landscape are prompting companies to adopt a cautious and reactive stance toward implementing regulatory projects across their platforms. With the potential for an era of deregulation on the horizon, businesses are preparing to navigate unpredictable shifts in regulatory requirements.

As a result, the justification for large, costly compliance projects is facing increased scrutiny. Companies are wary of committing substantial resources to initiatives that could become sunk costs should sudden regulatory changes render them unnecessary. This cautious approach underscores the need for flexibility and adaptability in planning regulatory tech investments in an uncertain political and regulatory environment.

Since the pandemic, the market for junior engineering roles has been cold. However, as larger tech companies face the reality of five years of senior talent taking retirement, they are likely to revive junior hiring programs. This shift will come as a necessary alternative to competing for an increasingly limited pool of experienced professionals.

These junior roles, however, will undergo greater scrutiny. With the anticipated workforce changes driven by AI productivity gains, companies will set more stringent expectations for each position. The emphasis will be on ensuring that every new hire aligns closely with evolving business needs.

In this landscape, career switchers may become more attractive candidates than recent university graduates. Companies may view individuals with proven aptitude and experience in a commercial environment as a safer investment, prioritising practical expertise over purely academic credentials.

With low interest rates and a hot IPO market failing to re-emerge, the demand for SaaS and PaaS tools that adopt usage-based pricing rather than seat-based pricing is set to grow.

The new generation of SaaS companies offering these tools will be lean by design, focusing on undercutting competitors with competitive pricing. Unlike many established SaaS providers that pursue elaborate and ambitious IPO plans in hopes of becoming the next tech giant, these new entrants will prioritise sustainability and a commodity-like business model from the outset. Customers, increasingly unwilling to fund the high costs associated with grandiose expansion plans, will gravitate toward these pragmatic offerings.

Established tools that have embraced usage-based pricing, such as Honeycomb and PostHog, are well-positioned to thrive. Operating in markets where larger players traditionally charge by seat, the transparent pricing of these companies positions them for strong adoption.

As technology continues to advance, companies must navigate a complex interplay of innovation, regulation, and workforce evolution. AI is transforming development workflows but revealing its limits, while the demand for better data infrastructure emphasises the importance of foundational skill sets. Regulatory tech investments are becoming more cautious, junior roles are being redefined to meet modern needs, and usage-based pricing models are reshaping SaaS and PaaS landscapes. By understanding these trends and adapting strategically, businesses can thrive in a rapidly changing environment, positioning themselves for long-term success.