An internationally recognized IT expert shares how AI and automation are reshaping the role of the business analyst.
According to McKinsey’s The State of AI 2025 report, up to 70% of all business tasks can already be automated using existing technologies. AI and automation are not just trends — they are growth drivers fundamentally transforming not only technologies but also team roles.
The role of the business analyst is evolving. Once seen primarily as a “translator” between business and IT, the analyst is increasingly becoming a digital architect, says Viktoriia Trofymchuk, a recognized authority in IT and business analysis. Viktoriia holds the Senior Member status at IEEE — the world’s largest professional association for engineering and IT. She is also a lecturer, researcher, and practitioner with over 13 years of experience.
According to her, the analyst’s role as a bridge between strategy, technology, and people is becoming more complex and more critical.
In a conversation with Tech Bullion, Viktoriia discussed how AI and automation are turning the business analyst into a strategic partner in business transformation — someone who designs systems, works with data, manages risk, implements AI tools, and builds communication across teams.
From Tasks to Architecture: A Shift in Responsibility
As AI and automation become integrated into business operations, analysts are expected to go beyond documenting how things work today — they’re being asked to anticipate how business will function tomorrow, and to help design that future.
“Today, a business analyst is not just a requirements gatherer — they’re a digital solutions architect,” says Viktoriia. “They don’t just describe processes — they create them.”
The main challenge facing the profession now is the shift from formal documentation to designing integrated digital ecosystems. In one of her projects, Viktoriia developed a CRM architecture that fully integrated accounting and logistics, replacing fragmented tools with a single source of truth. Automated dashboards delivered real-time KPIs, allowing faster and more accurate decision-making.
This reflects the broader trend of moving away from manual analysis toward data-driven management and AI-enhanced decision-making.
“Data is becoming a strategic asset, and the system itself becomes the foundation for forecasting, process optimization, and risk reduction through machine learning and predictive analytics,” she explains.
Viktoriia sees A/B testing and behavioral analytics as two of the most transformative tools for analysts in 2025. These techniques allow teams to validate hypotheses, observe real user reactions, and make decisions based on data — not intuition.
Efficiency: The Fusion of Integration and Automation
In 2025, understanding APIs, data models, and process automation is no longer enough. The real value of a business analyst lies in identifying growth opportunities, formulating and testing hypotheses, analyzing user behavior, and fostering a culture of continuous product improvement.
“I often use A/B testing and behavioral analysis, especially when working with digital products,” Viktoriia says.
“It’s not just experimentation for its own sake — it’s about making fact-based decisions, not assumptions.”
While integration and automation form the infrastructure, experiments and behavioral analytics are the “engine of growth” — enabling businesses to adapt quickly and validate ideas before scaling them. This is the new core responsibility of the analyst: not just process optimization, but enabling innovation.
Viktoriia has served as an expert advisor for academic projects at the international ITHEA institute in Bulgaria and as a scientific advisor at the ELPA–NDT conference. These experiences have given her a broad view of analytical approaches.
“In my experience, the most promising approaches are those where processes are formalized, and outcomes are measurable,” she says.
“Such methods are easier to scale and automate — and can be enhanced with AI tools to speed up data processing and improve accuracy.”
As an IEEE Senior Member and independent IT business analyst, Viktoriia observes how processes are evolving in different countries and how AI is being applied in logistics, finance, and healthcare. This global perspective helps her adapt best practices to local realities — and anticipate global shifts.
AI in Business Analysis: Risks, Responsibility, and Strategy
Business analysts play a crucial role in AI-driven projects. Even if they’re not building the algorithms themselves, they are responsible for evaluating the safety and architecture of solutions — including data flows and access scenarios.
As an author of scientific papers on cybersecurity and risk modeling, Viktoriia emphasizes the importance of seeing the system as a whole and understanding the ripple effects of any changes.
“You need to analyze the architecture and data flows, identify where leaks might occur, where data input could be manipulated, or access rights violated,” she explains.
“These technical threats must be connected to real business consequences — operational failures, financial losses, or compliance breaches.”
To mitigate risks from the start, Viktoriia builds in safeguards and monitoring mechanisms at the design stage. She uses systems modeling, scenario analysis, probabilistic, and dynamic models to assess risk and forecast outcomes.
“Mathematical models don’t replace expert judgment,” she notes,
“but they help businesses make decisions based on data and predictions — not just gut feeling.”
This approach is especially critical for projects where AI tools influence core business functions.
Key Skills for the Modern Analyst
Having worked extensively with university students who later entered the business analysis field, Viktoriia has observed their development firsthand — as well as the challenges they face. Drawing from this, and her own experience in IT projects, she identifies three essential skills every analyst must master in the digital era: systems thinking, data fluency, and communication.
It’s no longer enough to understand individual business processes — analysts must be able to design and analyze complex, interconnected systems: CRM, logistics, accounting, marketing, and customer interfaces. A single integration failure can disrupt the entire flow.
In a data-driven world, analysts must confidently navigate data structures, understand data origins and distortions, and know how to formulate and test hypotheses using A/B tests and behavioral insights.
“I often use A/B testing and behavior analysis in digital products,” Viktoriia says again.
“It’s not just an experiment to check a box. Companies benefit from a ‘culture of validation’: every new feature is tested on a small group, metrics are measured, and only then are decisions made — based on facts, not assumptions.”
AI doesn’t replace the analyst — but it does drastically change the expectations.
No longer focused on linear task analysis, analysts now engage with complex systems.
Instead of documenting requirements, they lead product thinking and data architecture.
Instead of producing reports, they facilitate, influence, and drive change.
As Viktoriia Trofymchuk concludes: “We are at a turning point — the analyst is no longer just a function. It’s becoming a profession of strategic importance.”
