CFOAgent · AI Implementation
AI Implementation · Accounting & ControllingImplementing AI in finance and accounting.
No slide battles, no months-long assessment phases. We start in day-to-day operations, look at the actual workflows with your leads and turn them into a concrete plan: which use cases, which tools, in what order. For corporates and larger SMEs with their own accounting and controlling teams.
How an AI implementation runs with us.
We do not start with a weeks-long analysis. We start in day-to-day operations. Together with the people in charge, we look at the actual workflows in bookkeeping, controlling and reporting: how documents come in, how the monthly close is built, where things get reconciled, commented, copied and rebuilt.
Because we have seen a great many companies with completely different accounting and controlling processes, across industries, system landscapes and company sizes, we quickly recognise which processes are suited to artificial intelligence and which are not. The patterns repeat, the details differ everywhere. Exactly that combination makes prioritisation fast.
After a short time, a concrete implementation plan is on the table: Which use cases deliver the most value? Which tools fit? Which systems get connected? Which projects come first, and what do we deliberately leave alone?
Our strength is not knowing as many AI tools as possible. Our strength is recognising very quickly, based on decades of work in finance and accounting, where AI creates real value in your specific environment, and where it does not. That applies to AI in finance as a whole: from the general ledger to controlling to management reporting.
- No lengthy presentations and no theoretical AI strategy papers.
- No months of as-is documentation before anything happens.
- No tool zoo: tools follow the use cases, not the other way round.
- No software sales: we are independent and earn nothing on licences.
From day-to-day operations to a plan, from the plan to implementation.
Review the workflows
On site, in daily business, with the people who do the work. Not interviews about processes, but the processes themselves.
Identify use cases
Where is repetitive work, where are media breaks, where is Excel acrobatics. Every use case is rated by value and feasibility.
Build the plan
A concrete roadmap: which projects first, which tools, which systems, who does what. Pragmatic rather than exhaustive.
Run pilots
The first use cases go into live operation, together with your staff, at their workplaces.
Anchor it
Training, ground rules and further development: AI becomes part of daily work, not a project that fizzles out.
Where AI delivers in accounting and controlling.
Every company is different, but these areas come up in almost every review:
Document processing & payables
From inbox to posting proposal: capturing, coding and checking recurring documents.
Reconciliations
Bank, clearing accounts, intercompany: finding, documenting and preparing differences instead of hunting for them.
Monthly close
Checklists, plausibility checks on the income statement, spotting anomalies before someone finds them in the report.
Reporting & commentary
Compiling reports and commenting variances cleanly, in your language and your format.
Ad-hoc analysis
Answering questions about the numbers in minutes instead of days, down to the individual document.
Planning & forecast
Data preparation, driver logic and scenarios: less copy-paste, more time for the message.
Excel automation
Defusing the grown Excel chains: automate what eats time daily, replace what is dangerous.
Contracts & documents
Extracting information from contracts, invoices and correspondence in a structured way and processing it further.
Whether the answer is an AI agent, a lean automation or deliberately nothing at all is decided case by case. Sometimes the best recommendation is: simplify this process first, then automate it.
Experience from more than 80 mandates in finance and accounting.
Behind CFOAgent stands Roman Kalberer: a finance practitioner with more than 80 mandates as CFO, head of accounting, controller and project lead, in corporates, SMEs and the public sector. That shapes how we implement AI:
- We speak accounting: account assignment, VAT, subledgers, reconciliations and closing processes are our daily business, not foreign words.
- We recognise patterns fast: whoever has seen many finance organisations sees in hours what takes others weeks.
- We work with your people: implementation happens at the workplace, not in the meeting room. Your staff can run it themselves afterwards.
- We stay independent: recommendations follow value, not licence models. From the Microsoft stack to specialised tools.
For teams that answer for the numbers.
Accounting and controlling departments
The finance department with several employees, several entities, grown processes and reporting chains: this is usually where the greatest potential lies, and where a partner counts who knows group processes from his own responsibility.
Finance teams with several employees
A well-rehearsed finance team with grown workflows: AI creates room for analysis and steering, without needing an IT department for it.
Looking for a ready-made digital employee for defined tasks instead? Then our page on AI agents in accounting is the right place. The two combine well: the implementation shows where agents make sense.
Four companies, clear roles.
Whenever a project needs more than AI implementation, the paths are short: data platform, interim reinforcement or sparring for leadership come from the same group.
AI implementation, answered briefly.
How does an AI implementation in accounting start sensibly?
Not with a strategy presentation, but with the actual workflows: documents, closing, reconciliations, reporting. The review produces the use cases, and the use cases produce the plan. That way you invest first where the value is greatest.
How quickly is there a concrete plan?
Considerably faster than in classic consulting projects: the review takes days, not months. Because we know a great many finance organisations, prioritisation is fast, and the plan contains concrete projects, tools and responsibilities instead of declarations of intent.
Which tools do you use?
The ones that fit your environment. It often starts with the tools you already licence, such as the Microsoft stack, complemented by established AI models and, where needed, specialised solutions or dedicated agents. We sell no software and earn nothing on licences.
Do our staff need prior AI knowledge?
No. Implementation happens at the workplace, with your staff’s real cases. Whoever knows their process learns to use AI within it surprisingly fast. Training and ground rules are part of the implementation.
What about data protection and confidentiality?
We clarify that per use case: what may go to which cloud, what stays in-house, what anonymisation is needed. There is a viable path for practically every requirement, from Swiss cloud hosting to local models. The important thing is to ask the question at the start, not at the end.
Does AI replace our accountants and controllers?
No, it changes their work: less capturing and retyping, more reviewing, steering and analysing. At a time when finance professionals are hard to find, that is relief rather than threat.
What does an AI implementation cost?
That depends on scope. The entry via review and first pilots is deliberately lean, so value and cost become visible early. After the intro call you receive a clear estimate.
What sets you apart from classic AI consulting?
We come from finance and accounting, not from technology consulting. Instead of concepts we deliver running use cases in daily operations, and we stay until your staff work with them independently.
Does this work in our industry?
Very likely: we have supported finance processes in manufacturing, construction, trade, services and the public sector. The basic accounting patterns are similar across industries; we pick up your industry specifics in the review.
Let’s talk about your processes.
In the intro call we listen, ask the right questions and tell you honestly where we see potential and where we do not. Then you decide whether a review makes sense.
Book an intro call