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Accounting firms serving Main Street and lower middle-market companies face a strategic choice: remain primarily compliance providers, or become technology-enabled partners that help clients improve financial visibility, control risk and run more efficiently. Kurt Gresens, CEO of Wipfli Advisory LLC, describes this as a defining moment because smaller businesses are encountering more complexity than their internal teams can absorb.
His argument, published in Accounting Today on July 30, 2026 (updated the same day), is a professional perspective rather than a quantified market study. The practical takeaway is still clear: accurate tax, accounting and audit work remains essential, but firms that connect that work to measurable business outcomes can serve clients more completely.
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What makes this a defining moment?
Gresens points to several pressures arriving at once for Main Street businesses: energy costs, inflation, workforce constraints, geopolitical shifts, changing regulation, higher technology expectations and expanding cybersecurity risk. He presents these forces as a convergence that makes routine financial reporting harder to translate into decisions.
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The capacity gap
A lower middle-market company can have a sophisticated problem before it has a sophisticated department. It may need cash-flow forecasting, controls over a growing technology stack, incident-response planning, better data or process automation, while its internal finance team is focused on closing the books and serving customers. Hiring a full-time specialist for every need can be uneconomical, and waiting until a crisis forces a response is expensive.
That gap creates an opening for accounting and advisory firms that can bring specialized people in when the client needs them. The relationship is not simply “outsource everything.” It is a way to access capabilities at a scale that matches the business’s actual demand.
Compliance is the floor, not the whole service
Gresens states the distinction directly: “Delivering accurate compliance work is still essential, but it is no longer sufficient.” Compliance includes work such as financial statements, tax filings, required controls and audit support. These activities protect the business and meet obligations; they do not automatically tell an owner which product is most profitable, whether cash will cover a planned investment or where a process is creating avoidable risk.
Moving beyond compliance does not mean treating statutory work as obsolete. It means using reliable books and controls as the information base for decisions. A firm can ask what the client needs to do with the information, then design reporting, technology and advice around that decision.
From deliverables to outcomes
An invoice for a completed return or a finished audit is a deliverable. An outcome is a change the client can recognize in the business. Gresens names four examples:
- better financial insight for planning and resource allocation;
- reduced risk, including technology and cybersecurity exposure;
- greater efficiency through improved processes or appropriate automation; and
- stronger operating performance.
These outcomes are not guaranteed by adopting a particular service. They are tests for whether the engagement is solving a business problem rather than adding another report to a client’s calendar.
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Service areas that can fill the gap
The article gives three examples of capabilities an accounting firm can combine with core compliance. They are service categories, not a ranking of providers or proof that one model works for every company.
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|---|---|---|---|
| Client Accounting Services (CAS) | Reliable day-to-day finance support, management reporting or finance leadership without building a complete internal department | Faster, more useful reporting; clearer cash position; decision-ready forecasts and controls | Scope must define who owns approvals, accounting judgments and management decisions |
| Cybersecurity and technology management | Help governing systems, access, vendors, resilience and security practices as technology use expands | Documented controls, reduced exposure, clearer response procedures and better visibility into technology risk | Security responsibilities, incident authority and regulatory obligations must be explicit |
| AI and automation advisory | Identify repetitive work that may be automated and establish a safe way to evaluate new tools | Less manual effort, more consistent processes and documented gains in cycle time or capacity | Human review, data protection and model limitations remain part of the design |
Client Accounting Services
CAS can range from transaction processing to a broader outsourced finance function. The useful question is not whether a firm offers “CAS,” but which decisions and controls the service will support. A well-scoped engagement should specify reporting frequency, close responsibilities, cash and payment controls, forecast ownership, system access and escalation procedures.
For a company that has outgrown an owner-managed spreadsheet but does not need a large permanent finance department, this arrangement can provide structure while preserving the ability to add internal staff later. It can also give an existing controller access to specialized capacity during a growth period, acquisition or systems change.
Cybersecurity and technology management
Accounting firms increasingly handle sensitive financial data, so technology risk is inseparable from client service. Advisory work in this area may cover access reviews, vendor oversight, backup and recovery practices, policy development, system road maps or coordination with security specialists.
The objective is not to promise that a client can eliminate cyber risk. It is to make responsibilities and exposures visible, establish a response path and align technology decisions with business operations. A firm should state whether it is advising, managing a control, monitoring an environment or merely making a referral; those are different obligations.
AI and automation advisory
Automation can be appropriate for repetitive, rules-based work, such as data movement, reconciliations or workflow routing. Gresens also cautions that AI adoption and the use of AI in audit methodologies are still at an early stage, with their full impact developing. That means a responsible engagement starts with a bounded use case rather than a promise that AI will transform the entire finance function.
Human oversight is part of the proposed model. People must review exceptions, validate important outputs, protect confidential information and decide when a result is unsuitable for a tax, audit or management decision. Automation should remove avoidable effort, not remove accountability.
Three operating models for an accounting firm
The following framework translates the article’s themes into practical distinctions. It is an editorial comparison, not a measured performance ranking.
| Model | Primary promise | Specialist access | Technology integration | Human oversight | Evidence a client should request |
|---|---|---|---|---|---|
| Compliance-centered | Accurate, timely required filings and reports | Usually limited to the engagement team | Focused on production and documentation | Reviews work for correctness and compliance | Deliverable timetable, quality controls and escalation process |
| Project advisory | Resolve a defined issue, such as a system change or transaction | Brought in for the project | Depends on the project’s scope | Concentrated at milestones and decisions | Project objectives, owner, milestones and post-project handoff |
| Integrated outcome-focused | Improve financial insight, risk, efficiency or operating performance over time | Multidisciplinary access across finance, technology, risk and operations | Connected to workflows, data and management routines | Continuous review of automated and specialist work | Baseline measures, review cadence, named owners and documented results |
A firm does not need to force every client into the third model. A small company may only need compliance, while another may need a temporary project. The important distinction is whether the firm can explain the model it is using and why that model fits the client’s capacity and risk.
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1. Start with the client’s decisions
Ask which decisions are currently slow, uncertain or dependent on one person. Examples include hiring, pricing, borrowing, expansion, acquisition integration or technology investment. This prevents an advisory program from becoming a list of fashionable services.
2. Map the current information flow
Document where data originates, who changes it, which systems hold it, when management receives it and where manual work or duplicate entry occurs. The map should include controls and approval points, not just software names.
3. Identify the capability that is missing
Separate a knowledge problem from a capacity problem. A client may know what a forecast should contain but lack time to maintain it. Another may have staff time but need cybersecurity or automation expertise. The remedy, staffing pattern and price will differ.
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4. Assemble a multidisciplinary team
Gresens’s model depends on combining accounting with technology, risk and operational skills. The client should know who is accountable for the engagement, which specialists may join, how they share information and who makes the final recommendation.
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5. Automate selectively
Choose a process with a clear rule, a stable data source and a defined exception path. Establish a baseline before changing it. For AI-enabled work, specify permitted data, review requirements, retention rules and the person who signs off on the result.
6. Set a review cadence
Outcome-focused work needs regular management conversations, not just an annual handoff. The cadence might be monthly for cash and operating indicators, quarterly for risk and technology priorities, and event-driven for incidents or major transactions. The interval should match the decision, not a generic package.
How to measure whether the relationship is working
Measurement turns a broad promise into an accountable engagement. Establish a baseline and agree on definitions before claiming improvement. Suitable indicators may include:
- days from period end to a management-ready close;
- forecast updates completed on schedule and the assumptions documented;
- time spent on a targeted manual process before and after automation;
- open control, access or remediation items and their age;
- the proportion of management reports delivered with the agreed data and explanations; and
- operating measures selected by the client, such as margin, utilization, working-capital cycle or service reliability.
Not every metric belongs in every engagement. A cybersecurity project should not be judged solely by close speed, and a CAS engagement should not claim reduced cyber risk without security work and evidence. The measure must follow the stated outcome.
Safeguards against a shallow transformation
Moving beyond compliance can create new risks if the boundaries are vague. Firms and clients should address these failure modes at the start:
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- Service sprawl: adding tax, finance, security and AI offerings without a single accountable lead can produce fragmented advice. Use one engagement plan and a clear escalation route.
- Automation without control: a faster process can spread errors faster. Require reconciliations, exception handling, access controls and human approval for material decisions.
- Unclear independence or conflicts: firms should explain how advisory, bookkeeping, tax and assurance roles interact, including any limits on what can be provided alongside an audit.
- Outcome claims without a baseline: “more efficient” is not evidence. Record the starting condition, measurement method, time period and factors outside the firm’s control.
- Overpromising AI: early-stage tools may change quickly and can produce plausible but incorrect output. Treat pilots as controlled experiments with a rollback plan, not as replacements for professional judgment.
- Client dependence: outsourcing a process should not leave the owner unable to understand cash, controls or key assumptions. Maintain documentation, access and knowledge transfer.
Questions a Main Street company should ask an accounting firm
Before signing an expanded engagement, a company can use the following checklist to distinguish a durable operating model from a collection of add-on services:
- Which business outcome are we trying to improve, and how will we measure it?
- What work will your team perform, and what decisions remain ours?
- Which specialists can participate, and who is accountable when advice conflicts?
- What systems and data will you access, and how are permissions reviewed?
- Where will automation or AI be used, where will it not be used, and who reviews outputs?
- What happens during a cyber incident, system outage or staffing change?
- How will knowledge, credentials and documentation be returned if the engagement ends?
- Can you show a reporting sample, implementation schedule and review cadence for a company of our size and complexity?
These questions focus on scope and accountability rather than brand names. They also reveal whether a firm has built a repeatable capability or is improvising around a single project.
What may persist after uncertainty eases
Gresens predicts that flexible operating models could remain attractive even after current economic and geopolitical uncertainty declines. His reasoning is that some businesses may prefer external specialist partners to building every function internally. That is a forward-looking claim, not an established outcome, and its validity will depend on cost, trust, data security, service quality and the client’s ability to retain strategic control.
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For accounting firms, the durable lesson is less about adding a particular product than about changing the unit of value. Compliance work supplies the foundation. The opportunity is to connect that foundation to decisions, controls and operating improvements that a client can see and manage.
The practical verdict
Main Street companies do not need an accounting firm to promise everything. They need a firm that can accurately handle required work, recognize where internal capacity is thin, bring in the right specialist, use technology carefully and show what changed. Firms that make those links explicit can move from one-off deliverables toward relationships organized around financial insight, risk reduction, efficiency and operating performance—while preserving the human judgment that compliance and emerging AI tools still require.
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