2026 AI Predictions for Accounting Firms
TL;DR:
- Agent skills are the game-changer that help firms win with AI
- AI adoption within firms will lag within firms
- AI model providers ship awesome industry-specific products
- Talent exodus from laggards
Prediction 1: The agent skills framework leads to highly successful AI implementations
What are agent skills?
Agent skills are a framework for building AI agents with extremely predictable outcomes. Think of a skill as an automation an AI agent has access to run and review the results. A skill that reads a PDF, extracts specific data points, and populates an Excel template. The agent runs the skill, reviews the output, determines if the task is complete, and responds. Anthropic open-sourced this framework. OpenAI has already adopted it. I expect skills will work in ChatGPT very soon.
Why will agent skills change the game?
The way AI has been deployed thus far has been disastrous. More than 80% of AI projects fail, which is twice the rate of IT projects that don't involve AI. The infamous MIT study reported that 95% of AI pilots were failing. Whether firms deployed pre-built AI agents or built their own with broad instructions, the results were the same. The AI didn't fit firm-specific workflows. It hallucinated. It needed constant supervision. You end up spending more time fixing mistakes than you'd spend just completing the tasks. Skills change this because they constrain AI to narrow, well-defined tasks with predictable outputs. Chain them together and you get real power. Extract data from 10 PDFs, pivot the Excel data, create an executive summary. That sequence might save 15-30 minutes per engagement. This isn't magic. It requires significant time and effort upfront. Firms need to map workflows, create SOPs, write very specific instructions, define what good output looks like, and test and iterate. But the payoff is AI that actually works.
What’s your agent skills prediction?
By the end of 2026, the stigma of failed AI implementations shifts dramatically to success stories by firms who have implemented agent skills and narrowly defined agentic workflows specific to their firm's processes.
Prediction 2: Firm rollout of AI licenses explodes, but staff adoption lags
How do software rollouts typically fail?
There's a consistent pattern. Firms buy software. They roll it out and assume people will use it. Six months later, the adoption rate sucks and the staff hate it. It's not because the software is bad. It's usually because staff aren't trained and there's poor support for change management.
How is AI different from a typical software?
Most software is purpose-built for one specific problem. AI is stochastic, meaning the same input can produce different outputs each time. And it's flexible, meaning it can be used across service lines for a variety of reasons. Staff need training to understand when and when not to use it. Most importantly, unlike training for typical software, AI training doesn't end. Models and tools continually improve and evolve. We all learn new things each week. It's an ongoing process, and firms must treat it as such.
What’s your accounting firm adoption rate prediction?
By the end of 2026, firm-wide AI access will hit 70%+, but weekly usage by staff will lag at less than 50% because firms skip the training.
Prediction 3: Model progress slows down, but… that’s a good thing
Is AI model progress slowing down?
The honest truth: this is an educated guess. Model progress has slowed over the last year. We've had good releases, but nothing like the leap between GPT-3 and GPT-4 or Claude 3 and Claude 4. The proof is in what AI providers are shipping. Claude Code. Claude Skills. ChatGPT Health. Same models underneath. Different delivery mechanisms.
Why is AI progress slowing down good?
It's hard to gain market share when the difference between your flagship product and someone else's is immaterial. This pushes AI providers to lean into products fine-tuned for specific industries or verticals. That's good for us, meaning more purpose-built tools for accounting instead of generic chatbots we have to adapt ourselves.
What’s your prediction for AI progress?
By the end of 2026, AI providers ship multiple products fine-tuned for specific industries using current model capabilities. These products become differentiators since model quality is so similar.
Prediction 4: Talent exodus precedes client exodus
Are employees excited about AI?
65% of employees are excited to use AI at work. 77% will take AI training when offered. 79% say AI skills are important for career advancement. And firms that invest in AI training unlock 7 additional weeks of capacity per employee per year. Staff see this. They know which firms are investing in their growth and which aren't.
Why will employees leave?
Talent cares about professional development. They want to build skills that matter for their careers. They want to work at firms that aren't stuck in 2015. This isn't about replacing accountants with AI. It's about accountants with AI skills replacing accountants without them. Staff understand this even when leadership doesn't. They'll see how another firm has automated 15 hours of boring work they have to do on every engagement. They'll see their peers at other firms learning and building and feel the FOMO. The gap becomes visible, and unbearable to many.
What’s your prediction for AI-forward firms?
By the end of 2026, AI-forward firms will report measurably lower staff turnover than AI-resistant firms. This becomes a standard question on exit surveys and a recruiting differentiator.
