Should leaders be using AI to Bridge the Gap Between IT and Business?

We’ve come a long way since the siloed days of enterprise computing, IT and business teams operating as separate departments, each with its own responsibilities, processes and most importantly, its own language. Today, business teams have become more dependent on IT, which has introduced delays, reduced agility, and constrained innovation.

Enterprises have worked tirelessly to try to bridge the chasm between business and IT teams, so with the emergence of Generative AI (GenAI) tools, can this formidable gap be reduced, or even eliminated?

Martin Schirmer explores the intersection of AI and business, and what needs to be achieved for enterprises to make the most out of today, and future opportunities for competitive advantage.

Data Literacy Hasn’t Bridged the Gap

Historically, to close the gap between IT and business, many enterprises invested in data literacy programs. The goal was to empower them with skills in tools like Structured Query Language (SQL), data visualisation, and analytics platforms. While this approach may work in technology-centric environments, it failed to scale across industries. The reality is that most business professionals are not inclined or equipped to be a part-time engineer or analyst.

The core issue isn’t a lack of intelligence or willingness from the wider team – it’s a matter of focus and value. Business users are experts in customer needs, market dynamics and strategic execution. Pushing them to engage in technical languages introduces friction and results in the appearance of digital adoption, but without the impact.

Modern GenAI Tools and Natural Language Processing

GenAI capabilities, like natural language processing (NLP), are transforming data access by allowing users to interact with systems in plain English – or any preferred language. Instead of filing IT tickets or learning SQL, users can simply ask, “What were our top performing products by region quarter over quarter?” and get immediate responses in text, table, chart or even audio formats. Acting as a translator, NLP interprets the questions, finds the data and delivers insight – removing the need for technical skills and reducing reliance on IT.

This collaboration between teams allows businesses to capitalise on opportunities. One study revealed that workers waste an average of 9 hours a week locating the information they need to carry out their role, inflicting significant strain on teams. As new technology allows for more cross-alignment, it's important that teams take advantage of these new capabilities, like many already have. 

For example, global financial services firms are developing AI models with input from data scientists, fraud analysts and business leaders. These models can process billions of transactions in real time to detect fraud and uncover customer spending patterns. Similarly, global entertainment companies are using cross-functional teams of data engineers, product managers and creative professionals to power content recommendations and greenlight original productions based on viewer behaviour data.

When IT and business share a common language and vision, they can adapt quicker to market shifts, customer needs and technological disruptions. Innovation cycles accelerate, experimentation grows, and silos disappear. Modern data and AI tools are vital to that shift. The most successful organisations will be the ones where every employee, regardless of where they or data is located, has the tools to deliver strategic outcomes. Merely giving business users NLP tools or making IT more business-oriented isn’t enough. What’s needed is a culture where insights, agility and innovation thrive across every function.

In a culture like this, IT and business don’t just collaborate – they speak the same language, sit at the same table and are aligned on vision. Shared services evolve into shared vision and translators become transformers, delivering business impact from revenue growth, cost savings and risk reduction.

The Future of Decision-Making

As the convergence of IT and the business accelerates, decision-making will shift from slow, IT-driven reports to real-time analytics that blend technical and business value. When IT and business teams share a common language, organisations gain agility, respond faster to change and innovate more freely. Success hinges on culture where every employee – engineer to executive – has the tools and mindset to drive outcomes. In this model, IT and business sit at the same table, united in purpose, turning data into strategic impact and driving improvement in the bottom line.