Can AI improve the financial performance of businesses?
Artificial intelligence is no longer a futuristic concept—it is increasingly shaping how companies operate, compete, and grow. But a key question remains for many organizations: does AI actually improve financial performance, or is it simply another technological trend?
Recent empirical evidence from Slovak enterprises suggests that the answer is nuanced—but ultimately promising.
From experimentation to measurable impact
AI adoption across businesses is still in a relatively early stage, characterized by experimentation and selective deployment. Companies differ significantly in how they approach AI, from early exploration to more advanced, integrated use across multiple business functions.
Despite this variability, one pattern stands out clearly: firms that adopt AI more extensively tend to report better performance outcomes. Organizations with higher levels of AI adoption consistently evaluate improvements in key financial and operational indicators more positively than those at lower adoption stages.
Where AI delivers the most value
Among the most notable benefits reported by firms is increased labor productivity—often reflected in higher revenue per employee. This aligns with the broader expectation that AI enhances efficiency by automating routine tasks, improving decision-making, and enabling better use of data.
Beyond productivity, companies also report moderate improvements in:
- Revenue growth
- Cash flow from operations
- Quality of customer service
However, these effects are typically incremental rather than transformational. Most performance indicators fall within a range of “slight improvement,” suggesting that AI’s impact builds over time rather than delivering immediate breakthroughs.
The hidden trade-offs
Importantly, the data also highlights that AI adoption is not without trade-offs. Firms with higher AI maturity sometimes report increases in certain costs—such as material and energy consumption or longer receivables cycles.
This reflects a broader reality: implementing AI often requires upfront investment, organizational change, and process redesign. Financial gains may therefore be partially offset in the short term, especially during early adoption phases.
Why adoption level matters more than size
One of the most striking insights is that the level of AI adoption—not firm size, ownership, or age—is the strongest differentiator of outcomes.
Companies can be broadly grouped into three categories:
- Adopters – already using AI
- Planners – preparing to adopt
- Non-adopters – with no current plans
Across virtually all dimensions—performance, strategy, and internal readiness—these groups form a clear gradient: adopters perform best, planners follow, and non-adopters lag behind.
This suggests that hands-on experience with AI plays a critical role in unlocking its value.
Strategy without execution is not enough
While many organizations recognize AI’s strategic importance, fewer have translated this into concrete investments—such as budgets, training, or structured implementation plans.
This gap between strategic intent and operational readiness helps explain why financial impacts remain moderate. AI delivers value most effectively when it is not just discussed at the leadership level, but actively embedded into business processes.
So, can AI improve financial performance?
The evidence points to a clear conclusion: yes—but not automatically.
AI has the potential to improve financial performance through higher productivity, better decision-making, and enhanced customer outcomes. However, these benefits depend heavily on:
- The depth of adoption
- Organizational readiness
- Investment in skills and infrastructure
- The ability to integrate AI into core processes
In other words, AI is not a shortcut to better performance—it is a capability that must be built.
The bottom line
AI is already contributing to improved business performance—but its impact is gradual, uneven, and closely tied to how seriously companies approach its implementation.
For organizations willing to move beyond experimentation and invest in real adoption, AI represents not just a technological upgrade, but a tangible driver of long-term financial value.
Author(s):
Ing. Filip Stovíček, PhD. (filip.stovicek@euba.sk)
Bratislava University of Economics and Business
Faculty of Business Management
