In an interview with ERP Today, Sage Global CTO Aaron Harris outlined five AI predictions that will reshape finance and accounting in 2026.
Harris said AI has moved beyond pilots and into daily financial operations, placing new demands on governance, accountability, and system design.
Drawing on his experience building cloud financial platforms, he described a shift toward auditable AI, agent-ready software, and stronger technology leadership inside finance teams as organizations adapt to production-scale AI use.
1. CFOs Will Take Direct Responsibility for AI Assurance in Finance
As AI becomes embedded in daily financial decision-making, Harris said accountability will increasingly sit with CFOs rather than technology teams alone.
“There’s a growing expectation that CFOs will take accountability for how they behave: whether the data is sound, whether the recommendations make sense, and whether the outputs actually support the goals of the business.” That shift reflects the growing influence of AI across planning, operations, and customer-facing finance processes.
Tolerance for uncertainty remains low in finance, Harris said, limiting how far trust can be assumed. “Finance leaders simply won’t be able to rely on blind trust, because in finance, ‘almost right’ is wrong. CFOs will expect AI to earn trust the same way their teams do: by showing how it got there.” When that standard is met, AI becomes an accelerator.
“When CFOs understand and trust the systems working beside them, they can move faster, make better calls and take huge amounts of manual oversight off their teams,” Harris said, adding that AI will only earn its place when decisions can be “explained, examined, and relied upon.”
2. SaaS Platforms Will Be Rebuilt for Intelligent Agents
“There’s a shift happening inside finance software that most people won’t see at first—systems are being rebuilt to support work that isn’t done by humans alone,” Harris said. Core systems are being redesigned to support workflows that no longer depend solely on human interaction as intelligent agents take on more execution-layer work.
Those systems, he said, must provide agents with the same foundations traditionally designed for people. “The systems built for this era need to give agents what they give humans, structure, guardrails, and consistency, so the work gets done right every time.”
The result is not the decline of SaaS, but its evolution. “It’s the beginning of a new generation of software built to serve both humans and intelligent agents,” Harris said.
3. Trust in Accounting AI Will Move From Principle to Proof
Harris said broad claims about responsible or ethical AI will no longer be sufficient in finance, where systems must withstand professional scrutiny. “Finance doesn’t run on ‘close enough.’ The numbers are right, or they’re wrong.”
As AI takes on reconciliation, forecasting, and anomaly detection, businesses will demand evidence that models are explainable, data is governed, and outputs can withstand audit. “Generic claims about responsible AI won’t cut it anymore,” Harris said, adding that independent assurance will play a growing role in validating AI systems used in finance.
Models supporting critical decisions, he argued, must meet the same transparency standards finance teams already live with. “If a model is going to support financial decisions, it needs to be as transparent as a spreadsheet.”
4. Data Provenance Will Become Essential as AI-Generated Content Spreads
The growing volume of AI-generated content is changing how finance teams evaluate information. Harris said the key question is no longer whether content is human- or machine-made, but whether it can be trusted.
To manage that risk, Harris said organizations will increasingly adopt provenance frameworks that document the full history of information.
“We’ll see broader adoption of provenance frameworks: cryptographic signatures, secure metadata, and open standards that show where information came from, how it was handled and how it has changed over time,” he said.
Those tools will help determine whether content is fit for regulated use. “They’ll help determine whether it’s suitable for use in regulated environments.” In finance, Harris said, traceability will become as important as accuracy.
5. The CTO Role Will Become Central Inside Accounting Firms
With intelligent systems taking on more execution-layer work in finance, responsibility for guiding how those systems behave will move higher inside accounting firms.
“Someone needs to guide how those systems behave—and yes, I’m biased, but the role best positioned for that is the CTO,” Harris said.
That shift, he argued, will separate firms that treat technology as an engine of innovation from those that see it only as infrastructure. “The leaders who treat technology as the source of innovation—not just a stack of tools—will stand out.”
Once firms take the first step, adoption accelerates. “When teams take that first step with AI, something interesting happens: once they see it work even once, trust grows quickly,” he said. “That confidence snowballs. The hardest part is getting started, after that, the benefits become obvious.”
What This Means for ERP Insiders
AI governance is shifting from IT to finance leadership. Harris’s predictions signal that AI risk is becoming a financial control issue rather than a technical one. Accountability is moving toward CFOs because AI now influences judgments that must withstand audit, regulation, and investor scrutiny.
ERP competition is shifting from features to architecture. Future differentiation will come from how systems are built rather than what they claim to do. Vendors investing early in auditability, agent-ready design, and data lineage are positioning for durable advantage as AI matures.
Trust is becoming an auditable system property. Harris frames trust as something that must be proven continuously, not asserted through policy. Independent assurance, provenance controls, and transparency standards are converging into procurement requirements for AI used in financial decision-making.
