Automation Was AI’s First Chapter - Prescription Is Next

When news broke that Botkeeper had closed its doors, my reaction was reflection.

Reflection on the founders' building in one of the most challenging areas of accounting. Reflection on the firms that trusted a technology partner with critical workflows. Reflection on how quickly our profession is evolving and how uncomfortable growth can feel in real time.

It would be easy to reduce this headline to AI bookkeeping is failing. That would be a mistake. Because AI in accounting isn’t failing. It is maturing. Which means we can expect skinned knees and bruised ribs as we learn. KPMG announced in the first quarter of 2026 they are cutting costs by reducing manual effort and time through AI-driven compliance automation. This is a clear message: traditional compliance work is no longer the prize; strategic advisory is. This signal is a shift across the accounting profession.

The real battleground is moving from labor to intelligence, hours to outcomes, and processes to insights.

Automation as infrastructure was the first chapter

The first wave of AI in accounting focused on automation. As a professional in the field, I have felt the weight of the work we perform, and my hope is AI can move us from operating at 120% maximum effort down to 80%. I see this as my first AI goal. We need help with transaction coding, bank feed matching, consistency checks, workflow management, and month-end acceleration. I believe we will be there soon. Many large firms are getting there faster because they have in-house programmers helping narrow the gap in systems and data decentralization.

Clean books, faster closes, and fewer manual touches still matter because automation reduces burnout. Increased accuracy created capacity and will help firms survive talent shortages and rising labor costs.

But here’s what we’re learning: Automation is no longer the differentiator. It’s infrastructure. And infrastructure alone does not make a firm indispensable.

If your platform primarily automates coding and review, you’re competing in a layer that is rapidly becoming expected. Native accounting systems are embedding AI. Workflow tools are improving. Categorization engines are advancing. Efficiency is assumed.

So, if efficiency is assumed, what creates value?

Bookkeeping redefined

For decades, bookkeeping meant categorization, reconciliations, and month-end close. But bookkeeping is shifting to the structured intelligence layer of the business, changing the role from compliance to prescriber. As AI handles the mechanical work, the human role shifts. No longer is the focus on historical data input; the focus has evolved to interpreting patterns. And this is where we have untapped potential.

• We see payroll across dozens of businesses.
• We see personal tax behavior.
• We see lending trends.
• We see cost shifts and tariff impact.
• We see margin compression before owners do.

We sit at the intersection of micro-business data and macroeconomic signals. That is economic insight. Accountants can share firsthand stories about their clients' patterns, not just hear them secondhand in news headlines. We are living with and breathing data in real time. The question becomes: how do we leverage this shift profitably? How do we share insights in a way clients will actually act on?

The medical parallel: diagnosis and prescription

In medicine, we don’t visit the doctor hoping for organized charts. We seek a diagnosis and expect a prescription. When we don’t get what we want, we become frustrated. As an added bonus, we want prevention and life optimization.

Accounting is heading in the same direction, and AI is the right tool to take us there. The medical profession is the perfect parallel. Over the years, I've worked with numerous solution partners who first designed medical applications, then applied the same concepts to accounting to aggregate data, spot trends, and design data dashboards. It’s not a coincidence that we are in the same situation as the medical field. In both professions, we see multiple “patients” presenting symptoms. We deal with fragmented systems and segmented data. Without aggregation, diagnosis is incomplete.

Clients don’t hire us for categorized transactions.

They hire us for answers:

• How do I stay profitable?
• How do I survive market shifts?
• How do I grow without breaking?
• How do I spot trouble before it becomes failure?

AI’s true potential is not coding transactions faster. It is helping us diagnose economic health in real time. And generating prescriptive guidance using market insights. This is true not only for diagnosing illness but also for enhancing opportunities.

The uncomfortable truth: we haven’t cracked delivery

Here’s where we admittedly get stuck. Even when accountants provide good advice, it often dies in delivery. Reports don’t change behavior, dashboards don’t drive implementation, meetings get skipped, and recommendations stall.

Why? Because most small businesses lack:

• Operational infrastructure
• Financial fluency
• Leadership bandwidth
• Capital runway
• Accountability systems

The most advanced firms offering advisory services generate prescriptions. But we don’t have a structured model for treatment adherence. In medicine, there are prescriptions, pharmacies, compliance monitoring (labs), and follow-up.

In accounting, we send a PDF and hope. That is the advisory gap. We need systems that integrate data, support clear communication, and enable continued interactive monitoring. If it were gamified to drive behavior, that would be the cherry on top. I believe we will get there.

What competitors are seeing in real time

To understand how this is unfolding across the ecosystem, I reached out to several AI-enabled bookkeeping platforms.

Double, a bookkeeping solution with AI review functionality, confirmed they are seeing inbound interest from firms previously on Botkeeper. Double CEO Ben Stein shared:

“We have definitely seen inbound interest from firms who were previously on Botkeeper. It sounds like they were not given much notice, so affected firms are pretty urgently looking for alternatives.”

That urgency matters. When a platform closes, disruption is not theoretical. Firms aren’t casually exploring options; they’re stabilizing operations under pressure.

When asked how they position differently and what makes their model durable, Double offered clarity:

“We can provide great software, and rely on the firm to complete the operations. For those seeking the labor component, we partnered with a firm called NoLogo… together we can provide a complete solution.”

Rather than blending software and labor internally, Double separates the two through partnership.

Software infrastructure, labor through alignment, and clear role separation are one approach to solving the hybrid complexity challenge.

Puzzle, an AI Accounting Software, CEO Sasha Orloff, shared their structural philosophy.

They began by acknowledging the weight of the closure:

“Accounting is built on trust and continuity, and any disruption understandably raises questions for firms about stability and the role of AI going forward.”

On increased interest, they reported:

“We’ve seen a meaningful increase in inbound interest from firms over the past month (40% growth last month)… firms want to understand how to use AI in a way that strengthens their practice, rather than introducing new dependencies or risks.”

When discussing durability and positioning, Puzzle was direct:

“We are software, never have been, and never will be a services firm. Our success depends on our accounting partners succeeding. We use AI to increase the value of accountants, not replace them.”

They emphasize: Software only, no competing services, data transparency and control, and capital discipline.

Digits, an AI-Native Accounting Software, sees the moment through a different lens — not as a single company’s story, but as a broader inflection point. Rob Hamilton, Head of GTM from Digits, shared:

“The interest we’ve seen is less about Botkeeper and more about growth and what AI in accounting is actually becoming. Botkeeper going away is indicative of an inflection point — not simply about timing, but about how these platforms are built and whether the underlying technology can truly deliver on the vision.”

Digits emphasized an important distinction: some early platforms identified the right opportunity. The vision of reducing manual work and modernizing the back office was sound. Where approaches have differed is in how deeply the technology was built to support that ambition.

“As AI becomes central to the future of accounting, this moment serves as a reminder that architecture matters. Firms will increasingly need to look beyond positioning and ask how the work is actually being done. Is automation foundational to the platform? Can the technology clearly demonstrate how it performs and improves over time? Digits is built for the machine learning era from day one, with automation as the core engine rather than an overlay. That architectural foundation allows us to automate tedium in a fundamentally different way and augment accountants with tooling that drives meaningful efficiency and long-term durability.”

Digits frames this not as a retreat but as timing. There is an architectural difference since they built for the machine learning era from the beginning.

Double, Puzzle, and Digits are responding to the same market signal that durability and alignment matter as we position ourselves and the profession for what’s next.

What’s still missing is collaboration for implementation

Automation helps us organize. AI helps us diagnose. And what we still need are tools to help us ensure implementation and accountability.

What’s missing is the collaboration layer:

• Alert-based interventions
• Clear ownership of action steps
• Deadline tracking
• Accountability loops
• Behavioral nudges
• Outcome monitoring

Without collaboration, prescription remains a theory. Collaboration determines whether the client's future actually changes.

The economic advisory shift

As I've said before, traditional accounting is becoming an economic advisory service. Accounting becomes a real-time interpreter of business health when data and trends are combined.

Our sustained value becomes predicting patterns, evaluating risk, identifying early signals, generating prescriptive options, and guiding implementation.

Coding transactions will become automated to near perfection.

The question is: how can accountants leverage this shift to elevate their role? 

What has been exposed

The closure of an AI-enabled workflow-focused automation platform does not signal the end of AI bookkeeping and accounting. It signals the next phase.

The profession is moving from:

Automation → Diagnosis → Prescription → Implementation

Firms are not asking whether to adopt AI. They know they must. So instead, they are evaluating which solutions best leverage this shift. Not only who will get there first, but who will do it best.

AI equips accountants to prescribe. But a prescription without collaboration is incomplete.

Accounting is evolving. Automation was the first chapter. Prescription is the next. And collaboration will determine whether it works.