Introduction – AI as a Driver of Strategic Change
Artificial Intelligence has become one of the most significant sources of competitive advantage. Strategically, AI is no longer viewed as a supporting technology but as a capability that fundamentally reshapes how organizations operate.
At the same time, market data reveals a clear gap between companies’ declared interest in AI and their actual level of adoption. Many organizations lack a structured approach, which results in projects that remain at the pilot stage without progressing to full-scale implementation.
The purpose of this report is to clarify which processes AI can automate, what value companies are already capturing, and what a successful enterprise-grade AI deployment process looks like from a consulting perspective.
The Types of Processes AI Can Automate
Analyses of real-world implementations show that AI delivers the strongest impact in areas characterized by high repetition, intensive data use, and substantial manual workload. Key categories include:
Information search and analysis
AI dramatically accelerates access to information by automating document processing, summarization, and verification tasks that typically consume significant employee time.
Creation of business documents and content
Generative AI automates the creation of reports, presentations, proposals, marketing materials, and internal documentation, increasing operational efficiency.
Support for daily operational tasks
AI assists with data analysis, documentation workflows, preparation of summaries, and the automation of routine reporting.
IT operations, cybersecurity, and internal processes
AI enhances system monitoring, detects anomalies, streamlines ticket management, and improves operational and compliance workflows.
Customer service, sales, and procurement
AI-based assistants speed up client communication, support sales teams with data insights, qualify leads, and prepare personalized offers.
Product development and operational decision-making
Organizations using AI agents note higher agility, faster innovation cycles, and improved market responsiveness.
Current State of AI Adoption in Polish Enterprises
Despite clear interest, the maturity of AI deployment in many companies remains limited.
75% of enterprises have initiated AI-related projects
yet
only 33% have successfully scaled those projects into production environments.
In other words, most organizations operate in a state of “permanent pilot mode,” where initiatives remain experimental and do not evolve into enterprise-level solutions.
Additionally, 80% of employees using AI tools do so without formal approval, contributing to the rise of Shadow AI. Without governance, this introduces risks related to data privacy, security, and regulatory compliance.
Where AI has been deployed effectively, the value is already measurable:
66% of companies reported at least a 10% reduction in time spent on daily tasks
37% observed a decrease in operational costs
The most significant benefits appear in IT, internal operations, and cybersecurity.
Furthermore, 44% of companies already use AI agents, with another 14% planning to adopt them.
Half of surveyed organizations plan to increase budget allocations for AI, indicating growing recognition of its strategic importance.
Key Barriers to Effective AI Deployment
Based on the findings, four primary obstacles prevent organizations from achieving full value from AI:
Lack of a formal AI strategy
Companies often launch isolated initiatives instead of implementing a coherent, long-term AI transformation plan.
Insufficient digital competencies and cultural readiness
Without employee upskilling, structured guidelines, and change management efforts, AI adoption remains superficial.
Shadow AI and lack of governance
Unsupervised AI usage creates data exposure and compliance risks that may outweigh the benefits.
Difficulty scaling from pilot to production
Organizations can often validate a concept but lack the infrastructure, processes, or risk controls needed to operationalize it enterprise-wide.
A Model Enterprise AI Deployment Framework
To shift from potential to measurable business value, companies must adopt a structured, strategic approach. A mature AI implementation model includes:
1. Development of an AI strategy
Identification of high-value use cases, alignment with business priorities, definition of KPIs, and establishment of responsible AI principles.
2. Process mapping and use-case prioritization
Focusing on processes with high volume, high repetition, clearly defined rules, and quantifiable ROI potential.
3. Pilot deployment and value validation
Testing solutions within controlled environments, evaluating performance, and assessing scalability.
4. Scaling and integration into core operations
Transitioning pilots to production systems, integrating with IT architecture, standardizing workflows, and managing risks.
5. Capability building and cultural transformation
Training employees, establishing governance policies, ensuring ethical and compliant AI use, and fostering data-driven thinking.
6. Continuous performance monitoring
Evaluating the impact of AI on cost efficiency, productivity, quality, and customer value, and optimizing deployments accordingly.
Benefits Achieved by Organizations with High AI Maturity
Companies that deploy AI strategically report:
Higher productivity through automation of manual tasks
Employees complete tasks significantly faster, often by double-digit percentages.
Reduced operational costs
Automation and improved process efficiency translate directly into cost savings.
Increased organizational agility
AI shortens decision cycles and enables faster response to market dynamics.
Accelerated innovation and product development
AI agents enable rapid ideation, testing, and data-driven iteration.
Enhanced customer experience
Personalized interactions and streamlined communication lead to higher satisfaction and retention.
Conclusion
AI has entered a stage where its role is no longer experimental; it is becoming a cornerstone of enterprise modernization.
The companies achieving the largest benefits are those that:
• treat AI as a strategic capability
• invest in workforce readiness and governance
• successfully transition from pilots to scalable deployments
• systematically measure value and manage risks
Implementing AI is both a technological and organizational transformation. Organizations that master this dual challenge are already building competitive advantages that will be increasingly difficult for others to replicate.
Data Source: https://www.pwc.pl/pl/publikacje/polskie-firmy-nie-wykorzystuja-w-pelni-potencjalu-ai.html