Companies using artificial intelligence in innovation are increasingly adopting it consciously—not only operationally, but also strategically. While most investments are still self-funded, many organizations are actively seeking external financing. Key barriers remain: a shortage of AI talent—both on the market and within companies—and difficulties in securing external investment support. Despite these challenges, AI is clearly driving growth: it boosts innovation, enhances offerings, and strengthens teams.
These are the findings of the report “AI. Innovation Leaders on Business Transformation”, based on research conducted by Ayming Polska in April 2025 among 150 companies from the technology, industrial, and FMCG sectors. Only firms using AI in R&D were surveyed, ensuring a focus on organizations with real technological experience.
“These are organizations with concrete experience, and they approach AI implementation with intention,” says Piotr Frankowski, Managing Director at Ayming Polska. “An impressive 84% have moved beyond the testing phase, showing that they treat AI as a real growth tool—not just a novelty. In 22% of these companies, AI is already embedded in their business strategy.”
Strategic Thinking Drives Bigger AI Budgets
More than 60% of surveyed companies allocate less than 2% of their annual revenue to AI development. Larger investments are rare: only 16% dedicate 3–5%, and just 3% exceed 5%.
However, among companies that include AI in their business strategy, the picture shifts: 57% invest over 2% of revenue into AI—mostly in the 2–5% range—signaling deeper commitment.
“Where AI is part of the strategy, we see stronger investment. It’s no longer an add-on, but a core development pillar. This isn’t just curiosity—it’s a business decision, sometimes a critical one,” explains Frankowski. “Conversely, larger budgets can also make strategic integration easier. As systems evolve and implementation becomes more predictable, AI feels less foreign and more like a natural tool for development.”
Investment trends show a steady increase in commitment: over the last two years, 64% of companies raised their AI budgets, with 25% doing so significantly. Only 5% reduced spending. Looking ahead, 64% plan further increases.
Talent Shortages and Funding Access Still Major Obstacles
The top barrier to AI adoption is a shortage of skills—internally and in the market. 41% of firms report that a lack of AI specialists seriously hinders implementation, while 38% cite insufficient internal expertise.
Only 24% of companies have a mature internal AI team, while 64% rely heavily on external providers. These capability gaps aren’t just about headcount—they carry a real financial cost. After IT infrastructure (49%), the cost of hiring or training AI experts (45%) ranks second among major AI-related expenses, on par with software and licensing costs.
The third most common barrier, cited by 36% of firms, is difficulty accessing external funding.
“Competence gaps—internally and in the market—are the biggest challenge,” says Frankowski. “Finding or building a capable team is hard and expensive. These personnel costs are a major part of AI budgets. Add to that the challenge of securing outside funding, and it all comes down to one thing: money.”
Self-Funding Dominates, While Tax Incentives Remain Underused
A striking 82% of companies fund AI investments from their own capital, underscoring the challenge of obtaining outside support. National and EU grants are used by 47%, while only 21% take advantage of R&D tax credits.
“That’s surprising,” says Agnieszka Hrynkiewicz-Sudnik, Consulting Director at Ayming Polska. “R&D tax relief is far more accessible than grants. It doesn’t require competition for funds or nationwide innovation—just in-house development work.”
Every surveyed company uses AI in at least one R&D activity, whether for data analysis, prototyping, or testing, or developing AI-based solutions. Even creatively integrating existing tools may qualify for tax benefits, she adds.
Interestingly, only 19% of companies cited a lack of available funding—meaning the real issue lies in limited ability to access what already exists.
Technological Maturity and Strategic Ambition
Despite constraints, companies show strong AI maturity. Beyond popular tools like generative AI (57%), many use predictive and prescriptive systems (56%) and traditional machine learning (53%). More advanced solutions like deep learning (18%) and reinforcement learning (9%) are also gaining traction.
These tools are being applied in critical areas: manufacturing (66%), logistics (58%), and customer service (58%)—indicating a focused approach aimed at boosting operational efficiency and delivering business value.
“Companies see the value of AI and act on it—even in challenging conditions. If barriers like skill gaps and funding access were removed, AI adoption could scale up significantly. These challenges impact even innovative companies—so they’re likely even more serious for the broader market,” Frankowski says.
63% of companies say AI has made their offerings more innovative, making it the most recognized area of impact. This reinforces the view of AI as a growth tool, not just a technical enhancement.
“AI is strongly linked to innovation today,” adds Hrynkiewicz-Sudnik. “It supports not only process optimization or automation but also drives real product and service transformation. In many cases, AI is now part of the product itself—enhancing its value and functionality. At the same time, AI accelerates R&D by analyzing data, automating experiments, generating solution concepts, and predicting outcomes.”
Toward a Coordinated System-Level Response
The report paints a consistent picture of companies that are technologically ready, strategically ambitious, and increasingly adept at leveraging AI. But to translate this potential into a lasting competitive advantage, coordinated systemic support is needed.
On the business side, the focus must be on competency development, talent retention, and team building. On the institutional side, policy support, continued training initiatives, and promotion of funding opportunities are essential. Programs from global tech providers help, but should become systemic, not isolated.
Public institutions can also play a key role by scaling up investment incentives, particularly by promoting tools like R&D tax credits, grants, and other mechanisms that support innovation—especially where companies are already signaling a clear need.
Source: ManagerPlus – How Polish Companies Are Investing in AI: Ayming Report Reveals Clear Trend
