Recently, Forbes Ukraine, together with Top Lead, published AI Focus 2026, one of the most comprehensive overviews of how Ukrainian businesses are adopting and scaling AI today. Based on research across 200+ companies, the report shows a market moving toward enterprise-scale AI operations, infrastructure, and organization-wide implementation. Sigma Software is among the companies demonstrating mature AI adoption, reflecting broader changes already happening across the Ukrainian technology ecosystem.
AI Is Entering Its Infrastructure Era
AI Maturity Is Becoming the Real Differentiator
Ukraine Is Emerging as a Highly Adaptive AI Market
AI Is Expanding Beyond IT Departments
AI Is Entering Its Infrastructure Era
One of the clearest signals in the report is where investment priorities are moving. In 2025, 46.4% of global private AI investments were directed into AI infrastructure, models, research, and management rather than industry-specific applications.
AI is increasingly becoming part of core operational and technology architecture. Companies are investing not only in applications, but also in orchestration layers, governance, infrastructure, and private AI environments capable of operating at scale.
At Sigma Software, we increasingly see enterprises moving from standalone copilots toward AI-native delivery models, agentic orchestration, secure AI systems, and AI-integrated SDLC processes embedded into day-to-day operations.
AI Maturity Is Becoming the Real Differentiator
The report highlights a major gap between companies with low and high levels of AI implementation. Organizations with high implementation levels demonstrate a 72% probability of productivity growth, compared to 3.4% among companies with lower implementation levels.
The research also notes that AI adoption often helps reduce the productivity gap between lower- and higher-skilled employees, particularly in customer support and consulting-related tasks.
This reflects what many enterprises are now facing in practice. The discussion is no longer about access to AI tools, but about workflow redesign, governance, operational integration, and enterprise-wide implementation.
At Sigma Software, this is already reflected in production environments:
- AI-native software engineering workflows reducing testing time by up to 40%
- AI agents for legal document review helping save up to €500K annually
- Financial data processing systems reducing manual workload by 70%
- Agentic orchestration enabling legacy codebase rewrites in weeks instead of months
The advantage increasingly comes not from experimenting with AI, but from building operational models designed around it.
Ukraine Is Emerging as a Highly Adaptive AI Market
One of the notable findings in the report is that Ukraine demonstrates relatively high AI adoption among SMBs despite having a medium level of digital infrastructure readiness compared to many European countries.
The result is an ecosystem producing globally recognized AI companies across very different domains:
- Grammarly in language AI
- Respeecher in voice AI
- SWARMER in autonomous defense systems
- Esper Bionics in AI-powered prosthetics
- People.ai in sales intelligence
- YouScan in consumer intelligence
For global enterprises, this creates access to a market combining strong engineering capabilities with practical experience in rapid adaptation, operational resilience, and large-scale digital transformation.
AI Is Expanding Beyond IT Departments
The report provides several examples showing that AI implementation is increasingly moving beyond engineering teams alone.
Raiffeisen Bank reports that 83% of its engineers use AI during development, while 68% receive at least half of their code with AI assistance. The bank also states that it is expanding its agentic AI platform beyond IT departments into non-IT functions.
Another example comes from AI-powered quality control in contact centers. According to the report, one implementation resulted in a 15% increase in call quality and an 86% reduction in calls with violations after AI monitoring was introduced.
These examples show how AI implementation is increasingly affecting operations, customer interactions, compliance processes, support functions, and organizational workflows rather than remaining limited to software development.
Secure and Private AI Are Becoming Strategic Priorities
The report also highlights a growing focus on data security and private AI infrastructure. According to the research, 62% of AI prompts contain sensitive data that may enter training datasets. At the same time, 47% of US IT companies are already developing generative AI on their own infrastructure.
This aligns with growing interest in private GenAI environments, localized LLMs, and infrastructure that allows organizations to maintain greater control over data, governance, and compliance requirements.
For industries such as BFSI, healthcare, telecom, defense, and GovTech, AI architecture is increasingly becoming a strategic infrastructure decision.
At Sigma Software, this is reflected in ongoing work around secure enterprise AI systems and AI-native SDLC transformation for enterprise environments.
What Comes Next
The companies gaining the greatest long-term advantage from AI are increasingly those integrating it into operational architecture, engineering workflows, governance, and decision-making processes rather than treating it as a standalone toolset.
That is the idea behind Sigma Software’s AI Compass offering: helping enterprises move from fragmented AI initiatives toward structured AI transformation across operations, engineering, governance, and products.
If your organization is already scaling AI initiatives or preparing for the next stage of transformation, AI Compass is designed to help accelerate that journey through production-ready engineering expertise, enterprise AI implementation, and AI-native operational design.
