Technology Spotlight: Accelerating engineering with AI

In an increasingly competitive market, AI may be the edge mid-market companies need not just to keep up – but to get ahead. Inflexion is supporting its portfolio companies to embrace this.

Artificial Intelligence is no longer a futuristic concept but a present-day reality transforming the software industry. Building and scaling software products is a resource-heavy endeavour. Those who have undertaken the task know it often demands large teams, significant capital, and long timelines. 

For mid-market companies, this shift presents a real opportunity. With AI adoption in software engineering increasing, the competitive advantage now lies not in if a company uses AI, but how it leverages these powerful tools to drive real business value.

For mid-market software companies, the challenge has always been doing more with less. With engineering teams typically ranging from 50 to 300 developers, these companies must deliver enterprise-grade solutions without enterprise-scale resources. They compete for the same talent, serve increasingly demanding customers, and face the constant pressure to innovate faster than their rivals.

Mid-market firms are uniquely positioned to harness this revolution. Unburdened by the inertia suffered by many large enterprises yet possessing more operational maturity than startups, they can move with speed and precision. As Inflexion’s Mike Arshinskiy notes, the landscape has fundamentally changed: "The engineering revolution has unlocked speed and possibility - mid-market companies are no longer catching up, they’re taking the lead."

The Opportunity: Supercharging productivity and innovation

The most immediate impact of AI is a dramatic boost in engineering velocity. A 2025 survey found that 82.3% of companies using AI in software development reported productivity gains of 20% or more, with nearly a quarter seeing improvements of over 50%.

This surge is particularly beneficial for the lean, agile teams typical of mid-market businesses. AI acts as a force multiplier, automating routine work like code generation and documentation, which frees senior engineers to focus on high-level architecture and strategy. For junior developers, AI serves as an always-on mentor, accelerating their learning and making them productive members of the team from day one.

"For lean, fast-moving teams like ours, AI is not just an accelerator; it's a fundamental change in our operational physics,” says Dominik Nienhaus, Co-Founder at Finanzen.net. “We can now empower new joiners to contribute meaningfully from day one by leveraging AI as a guide for our existing codebase, while our senior talent is freed from repetitive coding to focus on the complex architectural challenges that drive real innovation. This allows us to compete on a level that was previously unimaginable for a mid-market player, turning our size into an advantage of speed and agility."

Beyond coding, AI is demolishing the barriers to innovation. Rapid prototyping has become significantly more affordable, enabling companies to experiment with less fear as it reduces development time by 30-50%. This allows mid-market firms to validate ideas faster and more cheaply, ensuring precious engineering resources are focused on building products the market truly wants.

The Strategic Edge: Modernising legacy systems and unlocking data

For many mid-market companies, especially those that have grown through acquisition, legacy technology is a significant drag on progress. Modernising these systems is traditionally a high-risk, high-cost endeavour, hampered by a shortage of developers skilled in older programming languages.

AI is changing this equation by making code migrations safer and more efficient. AI-powered tools can analyse, translate, and validate entire applications, with some projects seeing a 300% increase in delivery speed. This de-risks the integration of acquired technology and unlocks value that was previously trapped in outdated systems.

"In a mid-market environment shaped by acquisitions, you inevitably inherit a complex and fragmented technology landscape,” explains Paul McCabe, Chief Digital Officer at Giacom. “Our approach combines AI with structured engineering practices to accelerate the understanding and integration of these systems without compromising quality or control. AI helps us rapidly map complex dependencies, analyse legacy code, and highlight migration options, but the direction and decisions remain with our engineers. This means we can reduce risk, shorten timelines, and focus our talent on designing the future state, not getting stuck in the past."

At the same time, AI is democratising access to one of a company's most valuable assets: its data. New AI-driven data visualisation and information retrieval tools allow any user, regardless of technical skill, to ask questions in plain language and receive instant and insightful visual answers. This breaks down data silos and empowers teams across the organisation to make decisions that are smarter and faster. It means today’s AI isn’t just speeding up processes – it’s changing how software interacts with users and data. Retrieval Augmented Generation (RAG), for example, allows for richer, more contextual search capabilities by combining structured and unstructured data. Instead of links or documents, users get answers – and fast.   Similarly, agentic or autonomous AI can allow conversational execution and interpretation of advanced analytics models, replacing multiple analytics efforts of investigation and interpretation that typically lie between a business question and an actionable insight.

"The true impact of AI on data analytics is the radical democratisation of exploration and visualisation to enable insight,” points out Olly Downs, Chief Technology and AI Officer at Curinos. “For decades, deep analysis was the domain of specialists. Now, with natural language interfaces and automated insight generation, we are empowering every business user to have a conversation with their data and even exercise and interpret advanced modelling capabilities. This collapses the time between questions, informed decisions and action."

The benefits of AI are also manifesting within portfolio support models, where specialist networks and dedicated value creation teams help identify and implement AI opportunities across engineering functions. This is a core area where Inflexion supports, utilising a combination of its in-house value acceleration expertise and that of its wider global network. 

From product acceleration to back-office automation, it is clear that AI isn’t replacing engineers; it’s amplifying their output and enabling them to focus on the work that matters.

All Inflexion portfolio companies, regardless of size or ownership stake, have full access to our dedicated value acceleration resources covering digital enhancement (including data, AI, technology, cybersecurity and digital marketing), international expansion, M&A, sustainability, commercial strategy and talent management.