• PwC’s recent study says artificial intelligence has transformed the software industry at an unprecedented pace.
  • The report links AI adoption to faster development cycles, new product capabilities, and shifting workforce skills.
  • PwC highlights emerging risks: governance gaps, security exposure, and the need for upskilling.

What PwC found

PwC’s recent study describes a rapid, industry-wide shift driven by AI tools and platforms. While the firm frames the change as a major opportunity for software creators and businesses, it also signals clear risks if organisations don’t adapt their governance, security and training approaches.

How AI is changing software work

Across development teams, AI is speeding up tasks that once took weeks: code suggestions, automated testing, performance tuning and even parts of system design. Vendors and cloud providers are embedding generative models into IDEs, CI/CD pipelines and monitoring suites, making it possible to deliver new features faster and at lower cost.

Business impact and new product possibilities

Beyond developer productivity, AI is changing software business models. Products are being rethought to include AI-powered personalization, smarter automation, and embedded analytics. These capabilities can create stronger customer value — and new revenue streams — but they also increase product complexity and operational risk.

Risks PwC points to — governance, security and skills

According to the study, the speed of AI adoption has outpaced many organisations’ ability to manage it safely. Key concerns include weak governance over model use, hidden security vulnerabilities introduced by third-party models, and bias or compliance problems in AI-driven features. PwC warns that without stronger oversight, companies could face reputational, legal and operational fallout.

Workforce shifts and the need to reskill

The report highlights a shift in required skills: fewer routine coding tasks and more emphasis on system design, model evaluation, and AI risk management. That means companies need to invest in training and new hiring profiles to avoid a skills gap that slows adoption or increases reliance on outside vendors.

What leaders should do now

PwC’s analysis suggests a few practical priorities for leaders: accelerate targeted upskilling for engineering and product teams; put governance frameworks around model selection and monitoring; and treat security and compliance as first‑class concerns in AI-enabled products. Acting early reduces the risk of costly mistakes and missed opportunities.

Why this matters

AI is no longer a niche enhancement — it’s reshaping how software is built, sold and maintained. For companies that move responsibly, the technology promises clear productivity and product benefits. For those that delay, the report warns of regulatory, security and competitive downsides. PwC’s study is a reminder that strategic choices now will determine which organisations capture the gains — and which will be left managing the fallout.

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