Business Challenges in 2026: What the Surveys Show

In the Federal Reserve's 2026 survey of small employer firms, 73% named rising costs of goods, services or wages as a financial challenge. Among firms whose business or employees use AI, 7% have fully integrated it. This piece examines selected surveys published in 2025 and 2026: what they report about business challenges and AI use, and where their limits are.

At a glance

Six needs come up again and again across government statistics, central-bank surveys and large independent studies. Each figure below is a share of the respondents named in its base column.

Need	Headline figure	Base	Source
Relief from rising costs	73%	US employer firms (1-499 employees) naming higher costs of goods, services or wages as a financial challenge	Fed Small Business Credit Survey 2026
Customers and sales	57%	US employer firms naming reaching customers and growing sales as an operational challenge, the most common one	Fed Small Business Credit Survey 2026
People	46%	US employer firms struggling to hire or retain qualified staff	Fed Small Business Credit Survey 2026
Steady cash flow	50%	US employer firms reporting uneven cash flow	Fed Small Business Credit Survey 2026
Certainty	43%	US CEOs ranking uncertainty as a top economic threat	Conference Board C-Suite Outlook 2026
AI that works	46%	US firms using AI that name accuracy as their top challenge with it	Fed Small Business Credit Survey 2026

Relief from costs, and customers to sell to

Rising costs were the most common financial challenge in the Federal Reserve's 2026 Small Business Credit Survey (about 6,500 employer firms, fielded September to November 2025): 73% named higher costs of goods, services or wages. More than four in ten (42%) named tariff costs, rising to 69% in retail and 62% in manufacturing. Of the firms facing higher prices on foreign inputs, 76% passed at least some of the increase on to customers.

The pressure has not let up in 2026. Inflation was the single most important problem for 20% of owners in the NFIB's September small-business survey, up four points in a month (via Trading Economics). The Fed's October Beige Book reported continued price pressure from commodities, tariffs and insurance. In the Richmond and Atlanta Fed CFO Survey for the third quarter, optimism fell for small and financially constrained firms even as it rose for large ones.

Customers are the other half of the squeeze. Reaching customers and growing sales was the most common operational challenge in the Fed survey, at 57%. The survey's index of expected revenue fell from 39 to 33 in a year, its lowest since 2020. The Beige Book found little or no change in overall consumer spending.

People, cash and certainty

People. Labor quality was the single most important problem for 26% of owners in September, the top issue for a third straight month, and 32% had openings they could not fill (NFIB via NewKerala). In the Fed survey, 46% of employer firms struggled to hire or retain qualified staff. Globally, 37% of CEOs named finding qualified workers as a key hiring concern (Conference Board via HR Dive), and the Beige Book reports shortages of specialized, technical and skilled-trade workers.

Cash. Half of employer firms (50%) reported uneven cash flow. Credit does not always close the gap: about one-third of firms faced a funding gap despite applying for financing, and only 42% of applicants received the full amount they asked for. Among firms that borrowed from online lenders, 60% said costs were higher than expected.

Certainty. In the Conference Board's 2026 outlook, 43% of US CEOs ranked uncertainty as a top economic threat. The Beige Book describes an outlook "burdened by persistent uncertainties", and small firms' expectations for revenue and hiring in the Fed survey are at their lowest since 2020. The specific concerns reported include tariffs and trade policy (Fed survey, Beige Book) and monetary policy (CFO Survey).

AI: wanted, but working

Adoption is real but shallower than the headlines suggest. The Census Bureau's Business Trends and Outlook Survey, the best measure of the share of US firms using AI, put usage between 17% and 20% through May 2026. Among firms with 250 or more employees it reached 37%, while use among firms with fewer than 20 employees did not grow from December to May. In the Fed survey, only 7% of firms using AI said they had fully integrated it; 49% were still experimenting.

Not every firm wants AI. A third of employer firms have no plans to adopt it, mostly because it does not apply to their business (56% of them) or they prefer not to (30%). Among firms using or planning to use AI, the complaints are about fit:

• Firms already using AI named accuracy (46%) and adapting tools to their business (43%) as their top challenges.
• Firms planning to adopt named finding tools that meet their needs (54%) and the time to implement and train (37%).
• In the EU, 71% of enterprises with 10 or more employees that considered AI cited a lack of relevant expertise, and 53% cited unclear legal consequences (Eurostat, data extracted December 2025).
• The top AI priority for 46% of US CEOs is better data to measure return (Conference Board). In a Gartner survey of 204 finance leaders, 63% said AI deployment went slower than expected in 2025 (via CPA Practice Advisor).

The evidence is not one-sided. In BCG's 2026 study, nearly half of 1,330 executives said their companies now generate value from AI, up from 5% in 2025. In the Fed survey, 71% of AI users said it raised productivity. Both are self-reported, and BCG's sample is large companies. BCG attributes the gains to companies that run AI as an enterprise-wide program; whether that holds for small firms is untested.

One caution on numbers. Surveys measure "AI use" very differently. The Census figure counts firms. The Fed survey asks whether the business or its employees use AI and finds 46%, from an optional module about 81% of firms answered. Advocacy surveys report higher still. A Federal Reserve note found a single wording change in the Census survey raised measured adoption by 47% to 159% depending on the industry.

What this means for anyone building for businesses

The most common needs in these surveys are business problems: lower costs, more customers, staff they can keep, cash they can count on, and more predictable policy. What follows is our editorial reading of the evidence, not a finding of the surveys themselves.

1. Start from the business problem, not the model. Frame the value in the customer's terms: hours saved, errors avoided, cash freed.
2. Accuracy before features. Accuracy is the most common challenge for firms already using AI. Design for output people can check easily, before adding capability.
3. Reduce the adaptation work. Tools that do not fit, and the time to adapt them, are the barriers firms report most. Building on the systems and data a company already has addresses both.
4. Measure the return in the customer's own numbers. Better data to measure return is the top AI priority for US CEOs. Show the result in the customer's figures before asking for the next step.
5. Small firms are a gap worth investigating. AI use among firms with fewer than 20 employees did not grow from December to May, and sits well below the 37% of firms with 250 or more employees. Many small firms also say AI does not apply to them, so the opportunity needs testing, not assuming.

How we sourced this

We used evidence published from January 2025 to October 2026, ranked in two tiers. Tier A is government statistical agencies and central banks. Tier B is independent research that discloses its method and sample. Vendor-sponsored surveys and "idea list" articles were excluded. Where a publisher's own page could not be opened, the figure comes from a named secondary source, shown as "via".

Caveats:

• The Fed Small Business Credit Survey is a weighted convenience sample of employer firms, not a random sample.
• NFIB, Conference Board and Gartner figures are taken from secondary coverage of their releases.
• CEO surveys reflect large companies and self-reported views.
• Measures of "AI use" differ widely by survey (see above).

Tier A

• Federal Reserve Banks, Small Business Credit Survey: 2026 Report on Employer Firms (March 2026; fielded Sep-Nov 2025)
• US Census Bureau, AI use among businesses (May 2026)
• Federal Reserve, Beige Book (October 14, 2026)
• Richmond and Atlanta Fed, CFO Survey Q3 2026 (September 23, 2026)
• Federal Reserve, FEDS Note: Monitoring AI adoption in the US economy (April 3, 2026)
• Eurostat, Use of artificial intelligence in enterprises (data extracted December 2025)

Tier B

• NFIB Small Business Economic Trends, September 2026, via Trading Economics and NewKerala (October 13, 2026)
• Conference Board C-Suite Outlook 2026, via HR Dive and the release (January 2026)
• BCG, AI is starting to pay off (September 30, 2026)
• Gartner finance AI survey, via CPA Practice Advisor (May 2026)

About Aiterated

Aiterated builds operational AI for manufacturing, distribution and supply-chain businesses, one workflow at a time.

Our method, which we call Krino (Greek for "to sift"), is shaped by two of the challenges in this data: cost pressure and accuracy. Deterministic rules handle the cases covered by explicit criteria, with the aim of limiting model use and cost. Small, fast models handle routine cases, a large model sees only what remains, and a person makes the final call on the hardest ones. Human decisions are fed back as training data, with the aim of reducing the share that needs expensive review over time. The surveys above do not evaluate Krino: this describes our approach, not a finding.

Read how we work with a national promotional products supplier in our High Caliber Line case study, or schedule a call.