The financial sector is experiencing a revolution with the arrival of AI, which forces it to rethink issues such as trust and leadership. In this context of change, Aaron Harris, CTO of Sage, a global leader in accounting, finance, HR and payroll technology for SMEs, analyzes how AI will influence the behavior and evolution of financial and accounting departments over the next year.
From the activation of trust audits in AI, the adaptation of software systems and new technological leadership, to the total transformation of the sector with intelligent systems, traceable data and innovative solutions designed for effective collaboration between humans and AI itself. Below, the Sage expert details the 5 key predictions that will guide the evolution of the financial landscape in 2026:
CFOs take charge of AI reliability
AI is already present and influencing how teams plan, how customers are served, and how financial work is carried out. As this technology plays a larger role in everyday decisions, expectations are growing that CFOs will take responsibility for how they behave: whether the data is reliable, whether the recommendations make sense, and whether the results truly support the company’s objectives.
This change is being driven by pressures from different sides. More decisions are being made through AI, regulators are paying more attention, and risks are focused on systems that can learn faster than any team can review.
Financial managers simply will not be able to blindly trust because in finance “almost right” is wrong. They will wait for the AI to earn trust the same way their teams do: by demonstrating how it came to that conclusion. They will need visibility into why a model has arrived at a recommendation, whether the data on which it is based holds up, and how reliable those decisions are in terms of traceability and auditability.
When CFOs understand and trust the systems working alongside them, they can act faster, make better decisions, and free their teams from a host of manual oversight tasks. And, like any critical contributor, AI will only earn its place when its decisions can be explained, vetted, and trusted.
SaaS designed for the era of intelligent agents
There’s a change happening in financial software that most people won’t notice at first: systems are being redesigned to support tasks not just performed by humans. As agents take on more execution roles in finance, they will rely on software for the same reason people always have: to get work done in a controlled, predictable and auditable way.
Systems developed for the new era must provide agents with the same things as humans: structure, guardrails, and consistency so that work is done correctly every time. And that’s when teams start to notice the impact: agents can execute multi-step processes much faster, with fewer errors and much less discrepancy in routine work.
This is where systems stop being tools and become teammates. That shift transforms everything about how finance teams spend their time.
This is not the end of SaaS. It is the beginning of a new generation of software designed to serve both humans and intelligent agents. And that means accountants will spend less time crunching data and more time exercising judgment and making decisions.
Trust goes from principle to proof in AI for accounting
Finance does not work with “approximations”. The figures are correct or incorrect. Generic statements about responsible AI are therefore no longer sufficient. Companies want to know how a model arrived at a recommendation, how its data is managed, and whether its results can pass an audit.
It is not something expendable, but rather the basis for using AI in financial workflows. In 2026, trust will become something measurable. We will see the first wave of independent assurance systems applied to AI systems, with firms evaluating the models behind reconciliation, forecasting and anomaly detection. And we are already seeing the foundations: leading accounting firms such as PwC and KPMG last year launched dedicated “AI assurance” services to subject data integrity, model governance and regulatory compliance to external scrutiny.
If AI is to support critical finance tasks, it must be subject to the same level of professional oversight that finance teams are subjected to on a daily basis.
Trust is not earned by promises or vague statements, but by evidence. If a model is to support financial decisions it must be as transparent as a spreadsheet, and it must always be possible to see how it was arrived at.
The rise of the real Internet
An increasing portion of what we see on the Internet is synthetic. That is, written, perfected or influenced by AI. That doesn’t mean that real information is disappearing, but it does mean that the useful information/noise ratio is more difficult to manage. For financial managers, the real question is not “Was this done by a human or a machine?” but “Can I trust it?”
To answer that, we will see broader adoption of provenance frameworks: cryptographic signatures, secure metadata, and open standards that show where information comes from, how it has been handled, and how it has changed over time. These tools will not only identify the content, but also help determine whether it is suitable for use in regulated environments.
For accountants, provenance becomes a practical requirement, not a theoretical one. As more workflows rely on AI-generated data, businesses will need clear, verifiable indicators that the data underlying a decision is accurate, traceable and reliable.
This is the beginning of a new generation of software designed to serve both humans and intelligent agents.
In the next era of finance, knowing the origin of data will be as important as the data itself.
The role of the CTO in accounting firms
As intelligent systems take on more of the execution tasks in finance, someone has to guide the behavior of those systems. Yes, I’m biased, but the most suitable position for this is CTO. We have been preparing for this moment for a long time.
In many companies, technology leadership will shift from supporting the business to shaping it. Leaders who consider technology as a source of innovation, and not just as a set of tools, will stand out. Those ahead of the curve will spot where AI can optimize workflows, boost accuracy, and open up entirely new consulting opportunities. They will also equip teams with the confidence and skills to work effectively with intelligent systems.
And when teams take that first step with AI, something interesting happens. As soon as they see that it works, even just once, confidence grows quickly. That confidence increases like a snowball. The most difficult thing is to start. Afterwards, the benefits are obvious.
Companies that invest now in these capabilities – leadership, mindset and skills – will act faster for clients, offer better advice and stand out in a rapidly evolving profession.
Aaron Harris, CTO at Sage
