Tech Firms Bet Big on Upskilling as AI Transforms Developer Roles

Over the past year, it’s become apparent to many in tech that a major change is underway across the sector. Artificial intelligence is no longer just a productivity tool that helps developers write code faster or automate repetitive tasks. Instead, it is fundamentally reshaping how software is built, how teams are structured, and most importantly for workers, how value, responsibility, and income are distributed across technical roles.

As AI takes on more basic tasks, developers are moving into strategic and architectural roles. These roles focus less on writing code and more on designing systems, overseeing AI-driven workflows, and translating business needs into scalable technical solutions. In turn, this shift is already raising expectations across the board, from clients, leadership, and the market at large, about what senior talent should be able to deliver.

Recent findings from across the industry confirm this. A report from Cisco, Microsoft, and Google found that 92% of roles within the ICT sector are expected to undergo significant change as AI adoption accelerates. At the same time, 84% of engineering leaders say they have raised productivity expectations for their teams in direct response to AI-driven efficiencies.

For tech consultancies and software development firms, staying competitive now depends on how effectively they integrate AI into delivery. As tools evolve rapidly, even highly experienced engineers must continuously sharpen their skills to deploy new capabilities and unlock productivity gains.

That pressure is growing. According to recruitment firm Harvey Nash, the number of organizations running large-scale AI or machine learning implementations increased by 90% in 2025. Clients increasingly expect delivery partners to provide engineers who are already fluent in AI, and who can evolve their skill sets as the technology changes.

Despite growing demand, many organizations are struggling to keep pace. More than half (52%) of tech leaders report an AI skills gap in 2025, compared to just 20% the year before. AI has also become the number one skill in short supply, rising from sixth place in 2024. For many professionals, the challenge is no longer whether to upskill, but how to do so while meeting demanding delivery expectations.

Without structured, high-quality training embedded into daily workflows, companies risk falling behind.

Making Upskilling a Strategic Imperative

One firm that has taken this question seriously is BairesDev, which recently acquired AI upskilling platform Modal Learning. Over the past decade, BairesDev has built its reputation around sourcing and deploying the top-tier engineering talent, including specialists in machine learning, data engineering, and AI-enabled development. The acquisition is intended to deepen internal AI capabilities while scaling structured, role-specific learning across its workforce.

“Every client conversation now touches AI, both as a technology challenge and an organizational one,” said Darren Shimkus, founder of Modal and newly appointed President of North America at BairesDev. He added: “In 2024 alone, BairesDev saw a 383% increase in demand for AI and machine learning talent, underscoring the need for upskilling to be practical, intentional, and scalable.”

Modal’s platform focuses on applied learning, combining cohort-based live instruction, one-to-one coaching, and hands-on labs that reinforce skills using real business problems. “Since launching in 2022, Modal has delivered a 90% upskilling success rate across AI, machine learning, and data engineering by focusing on applied learning,” Shimkus said. “The programs are intentionally built to fit into engineers’ day-to-day work, typically requiring four to six hours per week.”

By pairing its rigorous hiring process with continuous AI upskilling, BairesDev aims to build AI-ready teams faster, adapt more quickly to emerging technologies, and deliver greater value to enterprise clients navigating complex digital transformations.

Expanding a Culture of Continuous Learning

The acquisition complements BairesDev’s existing internal initiatives, including Circles, a peer-led platform designed to facilitate knowledge sharing across technical, business, and soft skills. Together, these programs aim to strengthen long-term talent development across its globally distributed workforce, while building deeper, role-specific AI capabilities aligned with evolving client requirements.

The approach also supports internal mobility, enabling engineers to progress into higher-impact roles without stepping away from client work.

What the Future Holds

For tech services firms, the next phase of AI adoption is likely to favor smaller, more agile teams with a stronger emphasis on system design, governance, and strategic oversight. Shimkus pointed to growing demand for roles such as AI Architects, MLOps Engineers, Data Quality Engineers, Prompt Engineers, and technically advanced QA professionals. “These roles reflect how AI is reshaping both career paths and what senior engineering talent looks like today,” he said.

The transition will not be seamless for companies or workers. But one thing is clear: demand for experienced developers is not disappearing. Instead, value is shifting toward those who can combine technical depth with strategic thinking and who can continue to evolve as AI becomes a core part of how modern software is built.