AI AT WORK
AI investment for small businesses: Closing the gap between Türkiye and the United States
In Türkiye, 7.5% of enterprises with at least 10 employees use AI. In the United States, 46% of small employer firms report that their business or employees use it. There is an apparent distance between those figures. For a CEO, however, a more important question is whether adoption changes business capacity and profitability. [1][5]
Access to a tool is no longer the difficult part. Applying it to the right work, making its use stick and seeing a return require management attention. Across the research, investment is growing faster than demonstrable business results.
Small businesses in Türkiye have an opportunity to focus on the most valuable parts of their own operations rather than copy a large company’s transformation programme. The evidence helps put that opportunity into perspective.
1. Türkiye’s gap is between access and business use
TurkStat’s 2025 research shows a clear difference by enterprise size. [1]
| Enterprise size | AI use |
|---|---|
| 10–49 employees | 6.6% |
| 50–249 employees | 9.6% |
| 250 or more employees | 24.1% |
| All enterprises with at least 10 employees | 7.5% |
Large-enterprise adoption is approximately 3.7 times the rate among firms with 10–49 employees. Access alone is unlikely to explain the whole difference: Evaluating a new way of working also takes time, capability and clear responsibility.
Individual generative-AI use was 19.2% in the same year. The individual and enterprise surveys cover different populations; those percentages do not prove unauthorised employee use. They do draw attention to whether personal capability becomes a shared way of working. [1]
In the Mastercard, TOBB and Akıllı KOBİ research, 76% of participating SMEs report digital-strategy awareness, 65% have digital-transformation objectives, 44% have a separate budget, and 53% have received digital-transformation consulting. The awareness–budget gap is 32 percentage points. This is a different survey from TurkStat, but it illustrates the distance between intention and resources. [2]
Eurostat’s 2026 publication, using 2025 data, reports AI adoption of approximately 19% among EU SMEs and 55% among large enterprises. Türkiye’s 9.6% is the medium-enterprise category, not an aggregate SME rate. A single country ranking is less useful than understanding the capability needed to put AI to work. [3]
2. US surveys measure different stages of adoption
US estimates range from 8.8% to 58%. They can measure production use, an employee’s use, generative AI, or a paid purchase. These are different things.
| Research | Reported rate | Measure |
|---|---|---|
| Census BTOS, May 3, 2026 | 19.8% | AI use in any business function during the previous two weeks |
| Federal Reserve, 2025 Small Business Credit Survey | 46% | AI use by a small employer business or its employees |
| NFIB, 2025 | 24% | AI use by small employer firms |
| U.S. Chamber, 2025 | 58% | Generative-AI use by small businesses |
| SBA Office of Advocacy, November 2025 account | 8.8% | Small businesses experimenting with AI |
| JPMorganChase transaction research | 10% | New businesses paying for at least one AI service in their first six months |
These figures should not be combined into an average or a single multiple comparing the two countries. BTOS also broadened its question from production to any business function in November 2025, affecting comparisons over time. [4][5][6][7][8][9]
NFIB reports adoption of 21% among firms with 1–9 employees, 24% with 10–24, 28% with 25–49, and 48% with 50 or more. Nonemployer adoption is 18%. The U.S. Chamber series rose from 23% in 2023 to 40% in 2024 and 58% in 2025: A 35-percentage-point increase over two years. Scale and diffusion matter, but adoption does not necessarily mean maturity. [6][7]
In the Federal Reserve survey, approximately half of AI users are still experimenting, 44% report partial integration, and only 7% report full integration. US experimentation has not ended. For management, the question is which work has changed, what has improved and who follows the result. [5]
3. Commercial value starts with information and decision flows
The Federal Reserve’s four-period BTOS averages at the end of 2025 put adoption at approximately 37% in information, 33% in professional services, 30% in finance, 24% in real estate, 13% in wholesale, and 8% in accommodation and food services. These are period averages, not a single-day observation. [4]
Information-intensive sectors have clear places to apply AI. A manufacturer’s sales team, for example, searches technical documents before drafting a quotation. Value can come from less searching and rework rather than more text. Uptool’s Velocity CNC case examines quotation preparation and accuracy; it is a supplier case, not evidence of a universal improvement in win rates. [16]
In logistics, value may come from operational visibility. Samsara’s TP Trucking & Logistics case reports installation of approximately 40 minutes per vehicle and fleet deployment in less than five months. Its Hogland Transfer case describes moving from paper-based dispatch to real-time vehicle visibility and prioritisation of safety events. The change reaches the way information is collected and decisions are made. [17][18]
In services, customer intake and access outside working hours can matter. Geek Window Cleaning combined call handling, messaging, price estimates and booking tools. The account described a trajectory toward more than $1 million in 2025 revenue; that was an expectation, not a verified realised result attributable solely to AI. The useful lesson is the connected customer-intake workflow. [19]
In Türkiye, the TalentFocus and Plusture research reports use concentrated in marketing and communications at 52%, compared with 12% in supply chain. That suggests where starting points are being found, but a particular business may have more valuable opportunities in quotations, technical knowledge, reporting or customer requests. [10]
4. Productivity, profit and investment return are different measures
In KPMG’s Türkiye–US comparison, 87% of Turkish executives plan to allocate some AI budget to operations and 77% to customer experience. These are shares of respondents selecting an area, not the distribution of total spending. Success measures include productivity at 94%, operational improvement at 87%, customer satisfaction at 58%, and profitability at 39%. [11]
This does not prove that profitability is unimportant. It shows how early gains are being measured. Management needs to connect operational improvement to economic value.
Deloitte’s 2026 research reports efficiency and productivity benefits at 66%, decision-making and insights at 53%, and cost reduction at 40%. Only 20% report revenue increases, while 74% expect them in future: A 54-percentage-point difference between reported achievement and expectation. These large-organisation results are not a direct forecast for an SME. [12]
BCG’s 2026 research with 423 IT leaders reports expected IT-budget growth of 5.8%, with 66% planning higher AI/ML spending. Measured generative-AI and agent returns average 13.8%, reaching approximately 19% at high maturity versus 8–9% at low maturity. The maturity gap is approximately 10–11 percentage points. These findings are a signal about implementation discipline, not a promise that an individual project will deliver 19%. [13]
A faster quotation draft, for example, creates economic value only when that time supports more qualified quotations, earlier responses or less correction. If it disappears into another wait in the process, the business has not realised the full benefit.
5. Cost extends beyond the subscription
Futurum Group’s second-half 2026 research reports 46.9% of enterprises spending above their AI budget; 61% reduced outside-consultant and contractor spending to fund overruns. It is a large-enterprise finding, not a prediction for half of Türkiye’s SMEs. It does show why scope and cost visibility matter. [14]
Document preparation, data organisation, system connections, training, review and maintenance all contribute to cost. A cheap tool can still become an expensive investment if those responsibilities are undefined.
Commercial budget guides estimate approximately $18,000 in annual small-business AI spending, including $8,500–9,000 for subscriptions, $5,000–6,000 for implementation and $2,500–3,500 for training. SmartDev’s guide includes different scope bands, such as $50,000–150,000 for lean five-year use and $75,000–250,000 for a single-workflow pilot. These estimates use different assumptions. They are not a common budget, Türkiye market averages or our service prices. [15][20]
Their value is in making the full cost visible: What is needed for the application to work, the team to use it and the results to be checked?
6. Türkiye’s implementation gap is a connected business need
Among enterprises that do not use AI but have considered it, TurkStat reports insufficient expertise at 74.2%, cost at 67.4%, unclear legal responsibility at 62.4%, privacy and data-protection concerns at 61.8%, and incompatibility with existing systems at 61.7%. These percentages concern that specific group, not all enterprises. [1]
Together, they describe a need wider than training alone or software alone. Staff capability, management priorities, implementation and data conditions belong in the same plan.
The 2025 ecosystem report from AI Startup Factory, with Startups.watch and Endeavor Türkiye, reports 1,188 active AI startups. The Istanbul ecosystem report puts the city’s active AI startups at 660. Taken together, the figures suggest roughly 56% concentration, but report scopes would need to match for a definitive geographic measure. They do not establish that support is unavailable elsewhere. The business challenge is connecting available capability to a workable solution. [21][22]
7. Competitive advantage comes from connecting technology with the whole business
The opportunity is clear: Faster quotations, more consistent customer responses, greater work capacity and better use of company knowledge. Realising it depends on connecting management’s decision with everyday work.
A business-centred approach begins before choosing technology. The investment follows commercial priorities: Helping sales handle more qualified work, enabling customers to receive accurate answers sooner, or making reliable information easier for managers to reach. Tools, connections and implementation take shape around that objective.
Training, consulting and implementation belong together. Training strengthens the team’s use; consulting clarifies commercial priorities; implementation places the selected solution in the workflow. A shared plan helps a management decision become part of daily work.
For an owner, there is another benefit: Less time coordinating different suppliers for the same task. An approach that takes responsibility for the need, technical solution, specialist participation and acceptance protects management time. Clear scope, responsibility and cost, followed by checking the agreed result, form the basis of that trust.
There is room for Türkiye’s SMEs to move forward. The commercial outcome will become visible in businesses that respond faster, use their knowledge more consistently and complete more qualified work with their teams.
That is the value of AI investment: Connecting the part of the business that needs to grow with team capacity and suitable implementation. The approach that builds this connection can turn today’s first application into a stronger business tomorrow.
What this approach could mean for your business
Sources
[1] TÜİK — Yapay Zeka İstatistikleri, 2025.
[2] Mastercard / TOBB / Akıllı KOBİ — Dijital dönüşüm araştırması, 2025.
[3] Eurostat — Digitalisation in Europe, 2026.
[4] U.S. Census Bureau — AI Use in Businesses, Mayıs 2026; Federal Reserve — Monitoring AI Adoption in the U.S. Economy, Nisan 2026.
[5] Federal Reserve Banks — 2026 Report on Employer Firms, 2025 Small Business Credit Survey. Eylül–Kasım 2025 sahası, 6.525 küçük işveren işletme; rastgele olmayan örneklem.
[6] NFIB Research Center — Small Business and Technology, 2025.
[7] U.S. Chamber of Commerce — Empowering Small Business, 2025.
[8] SBA Office of Advocacy — A Veteran’s Vision, Kasım 2025. %8,8 oranını aktaran yazı; bu oran diğer anketlerin ortalaması olarak kullanılmamıştır.
[9] JPMorganChase Institute — Understanding the Use of AI Among Small Businesses.
[10] TalentFocus / Plusture — Türk Şirketlerinde Yapay Zekâ Uygulamaları, 2025.
[11] KPMG — Yapay zekâ dönüşümü: Türkiye ve ABD perspektifleri.
[12] Deloitte — State of AI in the Enterprise, 2026.
[13] BCG — IT Budgets and AI Spending Priorities, 2026.
[14] Futurum Group — AI Spending Over Budget, 2026 ikinci yarı araştırması.
[15] SmartDev — Real Cost of Generative AI: What SMEs Actually Pay. Ticari maliyet rehberi.
[16] Uptool — Velocity CNC vaka çalışması. Tedarikçi tarafından yayımlanan vaka.
[17] Samsara — TP Trucking & Logistics. Tedarikçi tarafından yayımlanan vaka.
[18] Samsara — Hogland Transfer Company. Tedarikçi tarafından yayımlanan vaka.
[19] U.S. Chamber of Commerce — AI Growth Across Industries. İşletme sahiplerinin aktarımlarını içeren yazı.
[20] AI Business Weekly — AI Spending Statistics. Ticari bütçe tahminleri; bağımsız KOBİ piyasa ortalaması değildir.
[21] Yapay Zekâ Fabrikası / Startups.watch / Endeavor Türkiye — 2025 Türk Yapay Zekâ Ekosistemi ve Global Etki Raporu.