“I want it gone.”
Aaron Harris, CTO of Sage, isn’t talking about making the financial close faster. He wants to eliminate it completely. No more monthly scrambles to lock the books. No more accountants working late to reconcile accounts. No more rigid cycles that control how businesses operate.
He shared this goal during his recent appearance on The Accounting Podcast, recorded at Sage Future in Atlanta. Harris has been a returning guest since 2019, and his message has stayed remarkably consistent: artificial intelligence will fundamentally change accounting processes and how businesses operate.
Harris isn’t just talking about automation making things faster. He’s challenging the basic business cycles that have defined corporate operations for generations. He envisions a future where annual audits become continuous, where quarterly tax filings disappear into real-time government systems, and where rigid business cycles give way to always-on, intelligent operations.
From Simple Tasks to Autonomous Operations: The Three Waves of AI
Harris breaks down AI’s evolution in accounting into three distinct waves, each building toward his vision of eliminating business cycles completely.
Wave One: Task-Based AI
The first wave focused on very specific jobs like reading invoices or classifying transactions. These systems worked like sophisticated scripts. They could automate tasks, but they needed humans at every step. “You can’t really interact with this AI,” Harris explains, “and because these are sort of very narrowly defined models, they can’t do a lot very flexibly.”
Wave Two: Generative AI
This wave brought conversational interfaces like Sage Copilot. Suddenly, AI could interact naturally with users and work more flexibly. This opened up possibilities for people outside the accounting team to use these systems. “The two big things are now you can interact with the AI,” Harris notes, “and it’s those underlying capabilities allowing that interaction that allow the AI to work more flexibly.”
Wave Three: Agentic AI
This is where Harris sees the real transformation. These systems can plan, execute, and operate on their own. They can access tools and interact with other systems without constant human guidance. “The real breakthrough comes with Agentic AI, where we’re now equipping these large language models. They think through how to plan something start to finish and execute on that.”
The progress has been dramatic. Harris tracks the journey from two to three weeks for financial close in 2019 to just two to three days today for some customers. But he’s not satisfied with just making things faster. “There are some breakthroughs, and we’re going to reach a point where businesses say, you know what, we’re just not going to operate this way anymore,” he predicts.
Sage already has AI systems handling complex tasks autonomously. Their outlier detection works across accounts payable, supply chain operations, and construction bidding. These systems don’t just flag problems; they prevent them by catching patterns humans would miss.
This evolution leads Harris to ask, if AI can keep our data accurate all the time, why do we need to “close the books” at all?
Why the Financial Close Needs to Die
Harris challenges something most accountants take for granted: the need for periodic closes. “Why do I need a close?” he asks. “Isn’t that kind of an archaic concept? Like, I’m locking up the books so nobody can access them anymore, and so that the data is memorialized forever. That’s ancient.”
This isn’t just theory. Real examples around the world show businesses moving toward continuous operations. In Brazil, every invoice must be filed with the government in real time. The UK’s “Making Tax Digital” (MTD) program requires businesses to upload their general ledgers to government servers quarterly, with AI automatically coding transactions. “Fundamentally what happens,” Harris explains, “is your general ledger gets uploaded to a government server. When it comes time to file the taxes, you’re just signing something, because they already know what you owe.”
These government requirements force businesses to modernize in ways that make continuous operations inevitable.
Harris’s vision for continuous auditing might be the most radical change. Instead of annual audits that review old data, he sees auditors providing ongoing assurance with technology constantly monitoring books. “My vision for continuous auditing is that the auditors are going to make a lot more money than they’ve been making,” he predicts. “It’s going to be continuous assurance.”
This would transform the relationship between businesses and auditors from periodic validation to ongoing collaboration. Instead of finding problems months later during annual reviews, continuous auditing would catch issues immediately and help fix them in real time.
Building Trust: Making AI Accountable
The biggest challenge is psychological. How do you get CFOs to trust AI systems with decisions they’re responsible for?
Harris understands this deeply. “You have to understand that psychology to design this experience,” he explains. The key is creating a “trust journey,” gradually giving AI more autonomy as users gain confidence through transparency and proven results.
Sage’s answer is its AI Trust Label, which Harris compares to a nutrition label. Click on any AI feature and you can see exactly how it works: what models it uses, how it handles data, security measures, and whether it uses your data for training. “We’re not saying here’s how much you should trust this,” Harris clarifies. “We’re saying here’s the compliance we are subject to and we are meeting and here’s the models we use.”
This transparency is crucial for complex tasks like accrual processing. Before a CFO trusts AI to handle accruals alone, they need to see the system’s suggestions, verify it contacted purchasing about pending invoices, and understand how it decides what to accrue. “I want to see in a very transparent, auditable way what the AI is doing before I say ‘yep, you can do it now’,” Harris emphasizes.
Sage’s careful approach reflects what customers really want. Harris cites a survey showing 75-80% of businesses want AI companies to “take it slow and get it right.” This finding shaped Sage’s strategy of gradual rollout rather than rushing autonomous agents to market.
This approach contrasts sharply with competitors like Intuit, whose AI agents Harris criticizes as trained on community forum content rather than authoritative sources. He describes Sage’s strategy as “a lot less reckless,” emphasizing their focus on serving CFOs who demand absolute accuracy. “We’re ruthlessly focused on the accounting profession. That CFO needs to trust us and they’re not going to use something they don’t trust.”
Instead of using general-purpose AI models, Sage is developing specialized accounting expertise through their partnership with the AICPA. These smaller, fine-tuned models focus specifically on accounting knowledge rather than trying to be good at everything. “I want it to be an expert at a very narrow set of things,” Harris explains. “You want it to be as capable as a CPA.”
AI in Action: What Sage is Building Now
Harris shared several examples of AI already working in Sage products, showing how these concepts are becoming reality.
Sage Copilot has been rolling out across different products over the past year. It started with small businesses using Sage Accounting, then expanded to Sage for Accountants, Sage 50, and now Sage Intacct. The system helps with three main areas:
- Close management. Copilot keeps users informed about what’s preventing the books from closing and helps them through the process
- Budget variances. It engages budget owners outside the finance team to understand performance and explain variances
- Product guidance. Users can ask conversational questions about how to use the software instead of searching through help files
Outlier Detection is Sage’s first major AI investment. Harris explains they built this capability first because “when we talk to finance teams and CFOs, the thing that comes through loud and clear is that they need to be trusted. The thing they care about the most is that their books are accurate.”
The system works differently for each company because “an outlier for company A is not the same as an outlier for company B.” Examples include:
- Accounts payable. Detecting vendor impersonation, unusual billing patterns, or duplicate invoices using fine-tuned models that create “fingerprints” for common vendors
- Supply chain. Warning about potential fulfillment problems by spotting irregularities in supply chain activity
- Construction. Helping estimate projects by recommending which subcontractors to get bids from and flagging unusual bid amounts
What’s impressive is how these systems work together. Harris notes that building AI isn’t just about creating one model. “You’re building a system, and that system is going to have traditional tech. It’s going to have AI. And usually, when there’s AI in it, there’s a lot of different pieces of AI that work together.”
The Bigger Picture: Reimagining Business Operations
Harris’s vision involves fundamentally changing how businesses operate in a real-time economy.
Consider the implications: When we can continuously validate financial data instead of reviewing it annually, investors get unprecedented confidence in business performance. When tax compliance happens in real-time instead of quarterly bursts, businesses can allocate resources more strategically. When companies can predict supply chain issues and prevent them instead of discovering them during month-end reviews, they can maintain customer relationships without the traditional firefighting that defines many finance roles.
For accounting professionals, this means preparing for a future where the monthly close might become as obsolete as manual ledger books. Annual audit cycles that consume enormous resources could give way to continuous partnerships between businesses and their assurance providers. Rigid approval workflows that slow decisions could be replaced by intelligent systems that understand context and risk better than static rules ever could.
The early signs are already here. Harris points to the international examples, Sage’s current AI capabilities, and the continuous monitoring being deployed across industries. “The question isn’t whether this transformation will happen,” Harris suggests, “but how quickly businesses and professionals will adapt.”
What This Means for You
Harris’s predictions might sound futuristic, but they’re grounded in technology that’s already working. The measured approach Sage is taking—building trust through transparency, developing specialized expertise through professional partnerships, and prioritizing accuracy over speed—suggests this transformation will happen thoughtfully.
Accounting professionals should start preparing for a world where traditional business cycles might disappear entirely. The skills that matter won’t be about managing monthly closes, but about interpreting continuous data streams, collaborating with AI systems, and focusing on strategic analysis that only humans can provide.
The future Harris describes isn’t just possible; it’s already beginning. Understanding this evolution and preparing for it might be the most important investment accounting professionals can make in their careers.
Listen to the full episode above to hear Harris’s complete vision for how AI will reshape the fundamental rhythms of business.