Published on 04.02.2026
The AI industry faces a striking paradox in 2025: over 73% of organizations worldwide are either using or piloting AI in core functions, yet only 46% of people globally trust these systems, according to the KPMG Global Study. This trust gap threatens to undermine billions in AI investments and slow digital transformation across industries.
Oleksandr Tserkovnyi has spent his career closing this gap. As Principal Engineer at TrialBase Inc., IEEE Senior Member, and AITEX Associate Member, he’s developed AI solutions for organizations where trust isn’t optional — legal firms processing sensitive documents, financial platforms handling millions of transactions, and marketing systems for BBC, The Economist, and Orange.pl. His approach contradicts conventional wisdom about AI complexity. At TrialBase, Tserkovnyi’s intelligent document parser handles massive legal document volumes through an intuitive chatbot interface — proving that sophisticated AI can be powerful and transparent. Previously at Oracle’s Maxymizer, his visual no-code platform enabled marketing teams to run complex A/B testing without developer involvement, pioneering an approach now considered essential for AI adoption.
The key insight from Tserkovnyi’s implementations across multiple industries: successful AI isn’t about the most advanced algorithms but about giving users control and understanding. His modular architectures at Parimatch connected disparate systems while maintaining transparency, demonstrating that trust comes from design choices, not just technical capabilities. As he puts it, creating transparent and user-friendly AI isn’t just a technical requirement — it’s the foundation for making AI a reliable partner in business and society.
Human-Centered AI Tools with Visual Controls to Enhance User Trust and Adoption
Drawing on the extensive international experience of Oleksandr Tserkovnyi, a key strategy to enhance AI adoption and build trust worldwide lies in implementing human-centered, explainable tools that leverage visual and no-code approaches. These solutions empower users with diverse technical backgrounds to independently configure AI systems and interpret their outcomes, significantly reducing barriers to adoption and increasing transparency in algorithmic decisions. Oleksandr emphasizes that building explainability and user-friendliness into AI is crucial for fostering trust and ensuring widespread adoption — ultimately turning AI into a reliable partner across industries and regions.
“When 73% of organizations deploy AI but less than half of people trust it, we’re not dealing with a technology problem, but with a transparency one,” explains Oleksandr Tserkovnyi. “The solution isn’t more advanced algorithms; it’s giving users genuine control and understanding.”
At TrialBase Inc., Oleksandr led the successful integration of AI technologies into tailored products for the legal sector, significantly speeding up data processing for legal professionals. One of his standout projects was deploying an intelligent document parser that extracts critical information from large volumes of legal documents and presents it through an intuitive chatbot interface, streamlining workflows and increasing accuracy. This example demonstrates that implementing AI is possible even in an industry where the cost of error is significant, but it requires a strict approach to data processing and creating solutions that are explainable and transparent.
Previously, during his tenure at Maxymizer (Oracle), Oleksandr developed a preprocessing system and a visual no-code platform for creating and running marketing campaigns, including A/B and multivariate testing, implementing projects for major clients such as The Economist, BBC, and Orange.pl. His approach simplified the process of creating and running campaigns by creating no-code tools accessible to business staff without engaging with the development process, thus streamlining the process of implementing marketing campaigns and making it faster and more efficient. At that time, it was a pioneering implementation of such an approach, but now, in the era of AI, providing users with accessible no-code and visual tools becomes even more important, as it allows them to stay in control of their tools and data.
This visual approach proved essential when Tserkovnyi faced an even greater challenge at Parimatch — integrating not just interfaces, but entire disparate systems across multiple platforms. His experience demonstrates that effective AI strategies blend transparency, human-centered design and technological adaptability to accelerate digital transformation, strengthen market competitiveness, and promote responsible development across industries.
Modular and Scalable Architecture as a Key to Sustainable AI Solutions
Oleksandr Tserkovnyi’s global expertise highlights that to foster greater adoption and trust in AI solutions, it is crucial to develop them on modular, scalable architectures optimized for seamless cross-platform integration. This strategy facilitates the incorporation of AI into diverse existing business environments, minimizing resistance while allowing for agile responses to changing needs. Central to this approach is the creation of an open ecosystem that provides transparent access to tools and components, enabling effective collaboration between developers and users.
At Parimatch, Oleksandr architected an innovative integration framework that connected disparate software products and services across multiple platforms, serving both client-facing applications and internal operations. By establishing clear communication protocols and standardized interfaces, he spearheaded the coordination of three multidisciplinary teams, ensuring seamless interoperability and system coherence. The emphasis on an open, collaborative culture inspired teams to actively share best practices and iterate rapidly on product features, significantly enhancing solution robustness and user satisfaction.
“The methodology we implemented in Parimatch allowed us to integrate entire third-party platforms in days instead of months by building architecture that different teams could understand and trust,” comments Oleksandr Tserkovnyi. “When your systems speak the same language through standardized interfaces, you eliminate the risks that make people doubt the efficiency of AI solutions.”
Oleksandr’s experience reinforces that building AI ecosystems with modular scalability and transparent integration capabilities is a foundational pillar for sustainable digital transformation globally, enabling explainable AI systems to evolve responsively while meeting diverse stakeholder demands.
These implementations reveal a consistent principle: visual tools empower non-technical users while maintaining system integrity. At TrialBase, legal professionals interact with complex document parsing through conversational chat interfaces. At Maxymiser (Oracle), marketing teams were able to deploy sophisticated A/B tests through plain-English commands rather than code. At Parimatch, that same philosophy was scaled to integrate entire third-party platforms across web, iOS, and Android through standardized interfaces. Each solution addressed a different technical challenge, but all shared a common architecture: complexity hidden behind intuitive controls, allowing users to leverage powerful technology without becoming engineers themselves.
A Key To Successful Implementation of AI Strategies
Successful integration of artificial intelligence into national strategies hinges not only on cutting-edge technologies but equally on human-centered design, transparency, and architectural flexibility. By marrying explainable, visual no-code AI tools with modular, cross-platform frameworks, organizations can dramatically lower adoption barriers, build user trust, and adapt swiftly to new challenges.
“After working across legal tech, marketing platforms, and betting systems, I’ve learned one principle: always start with people—give them understandable, controllable AI components they can actually see working,” explains Oleksandr Tserkovnyi. “People don’t fear AI when they can watch it work, understand its decisions, and override it when needed.”
His record shows that this dual focus accelerates deployment, optimizes resources, and drives measurable gains in efficiency and engagement. When embedded into a coherent organizational and cultural roadmap, these best practices create a resilient foundation for any nation’s digital transformation. Only by aligning advanced AI innovations with a clear, human-centric strategy can governments and businesses worldwide deliver transparent, accessible, and impactful solutions at scale.
