In today’s accounting landscape, technology has moved far beyond “nice to have.” It is the backbone of a profitable, scalable, client-centric firm. On the Building the Premier Accounting Firm podcast, host Roger Knecht and long-time accounting-technology authority Randy Johnston broke down how firms should think about building modern tech stacks—and what’s coming next that will reshape the profession entirely.
Below is a reframed look at their insights—not as a recap of the episode, but as a guide to designing a tech-forward accounting practice.
Start With Strategy, Not Software
Knecht emphasized on the podcast that building a tech stack begins with defining the work you want the firm to do, not with picking tools. Johnston echoed this: your service model determines everything—from the core accounting platform to the advisory, workflow, and AI tools that layer on top of it.
Johnston noted that a fully developed CAS practice can offer “around 23 services,” but firms shouldn’t start there. Both he and Knecht stressed that leading firms typically anchor around one to three core services—such as payroll, bookkeeping, dashboards, or bill pay—and expand strategically. This approach mirrors banks’ use of “stickiness” through bundled services.
Once the service model is clear, firms can choose software that supports those goals, instead of the other way around.
Building a Modern CAS & Advisory Stack
Johnston shared on the podcast that he now prefers the term Client Accounting and Advisory Services (CAAS), because true advisory requires more than reporting. He described three tiers firms should plan around:
- Core bookkeeping
- Controllership
- CFO-level advisory
Different tools support each tier, and Knecht pointed out that CAS staff often identify advisory opportunities first—meaning the tech you choose must support both accurate accounting and meaningful insights.
Core Accounting Platforms
Johnston highlighted several platform types and when they fit:
- QBO/Xero ecosystems → flexible, widely supported
- Sage Intacct / Zoho Books → mid-market or multi-entity needs
- Aplos → nonprofits
- Accounting Power → integrated GL + document management + bill pay
His guidance: choose the platform based on your client base and services, and avoid getting locked into single-vendor ecosystems unless it clearly improves efficiency.
Advisory-Centric Tools
Knecht asked Johnston about tools specialized for advisory, and Johnston pointed to 4ImpactData as an example of software built around true business modeling rather than basic dashboards. It integrates with QBO and generates Power BI dashboards tied to transaction-level detail. It also incorporates the DuPont model and AI-driven recommendations—an example of where advisory technology is headed.
Workflow, Management, and Document Automation
On the podcast, Knecht noted that workflow is one of the biggest pain points for firms. Johnston agreed—and outlined a clear structure for tech selection:
Workflow Management
Top options he cited include:
- Keeper
- Jetpack Workflow
- Carbon
- Aero Workflow
These tools handle recurring work, deadlines, delegation, and client deliverables—essential for a scalable CAS operation.
Document Management & Client Intake
Johnston recommended separating document storage, gathering, and extraction:
- Storage: SmartVault, Box, LedgerDocs
- Gathering: Liscio, DexPrepare (ReceiptBank), HubDoc, Entryless
- Extraction: MakersHub.ai (especially for construction, healthcare, restaurants requiring line-item classification)
He emphasized that document extraction is where AI is making the clearest immediate impact—reducing manual work and improving accuracy.
AI Is Becoming Invisible—and That’s the Point
Knecht asked about how AI is realistically changing accounting workflows. Johnston explained that we are moving past the “prompt phase” of AI and into deep product integration. Firms will soon rely on AI-enhanced features without realizing it—just as modern users no longer think about VPNs or SSL.
Three Levels of AI Productivity
According to Johnston:
- Prompt-based general productivity
- AI built into standard accounting tools
- AI-enhanced platforms designed specifically for accounting
He warned, however, that general AI models like ChatGPT can hallucinate, making accuracy-critical work risky. Tools purpose-built for accounting (e.g., 4ImpactData or MakersHub.ai) avoid this issue because they operate on structured financial data.
Hardware matters again
Johnston advised firms to invest in devices with neural processing units (NPUs)—a shift that hasn’t been this significant since the move to the cloud. NPUs will allow AI models to run faster and more securely on local devices, improving tools from trial balance automation to reconciliation.
What’s Coming: The Next Wave of Accounting Technology
Knecht asked Johnston what emerging tools excite him most. Johnston pointed to Basis, which he believes could become a breakthrough platform for reconciliation, reporting, and firm management. Firms using it report 5× productivity gains on QuickBooks and up to 10× on Sage Intacct.
This reflects a broader trend Johnston sees:
Accounting software design has barely evolved since the late 1990s. AI-driven platforms are about to change that.
He expects major leaps in rapid close technologies and consolidation of fragmented toolsets—cutting down on the “ten add-ons for CAS” problem.
Choosing Technology the Right Way
Knecht emphasized on the show that firms often buy tools before understanding them. Johnston agreed and suggested a simple two-step evaluation:
- Is this improving something you already do?
- Is it internal efficiency or client-facing?
Client-facing tools should be changed very rarely—every 4–5 years—because clients resist switching portals and apps. Internal tools, on the other hand, can evolve more frequently.
Johnston also highlighted on the episode that technology spend directly impacts profitability.
- Under 3% of revenue → firms tend to be underperforming
- 3–7% → healthy range
- Up to 15% → fine if managed well
Technology is a lever, not an expense.
Final Direction for Firms Building Their Tech Future
Knecht and Johnston aligned on one core message:
Technology should simplify your firm, not complicate it.
Their guidance from the episode can be distilled into four principles:
- Define your services first; build your stack second.
- Choose the smallest number of tools that solve the biggest problems.
- Adopt AI where it improves real workflows, not because it’s trendy.
- Remain client-centric and team-centric in every tech decision.
Firms that follow this approach will be positioned not just for efficiency—but for deeper advisory, stronger client relationships, and long-term competitive advantage.
