Sage, a leader in accounting, financial, HR and payroll technology for small and mid-sized businesses, today announced the advancement of AI agents across finance, HR and operations at its flagship event Sage Future, embedding intelligent automation directly into core business systems. These capabilities help teams act on work directly, not just analyze it.
Sage is bringing these AI agents directly into the systems that businesses and accountants rely on, automating finance workflows in Sage Intacct, workforce management and payroll in Sage’s HCM solutions, and operational insights in Sage X3. This enables organizations to identify issues earlier, respond faster and operate with greater confidence, supported by AI that is transparent, governed and built for real-world financial processes.
As AI becomes embedded in everyday operations, organizations are shifting from manual processing to automated, insight-driven workflows. IDC forecasts that by 2030, 45% of organizations will orchestrate AI agents across core business functions, signaling a major shift in how work gets done and reinforcing the need for AI that is explainable in high-trust environments such as finance and payroll.
For finance teams, this means moving from processing transactions to managing exceptions and acting on insights, while remaining accountable for the outcomes delivered by AI Agents.
“Our focus is simple: apply AI where it genuinely helps finance teams and business owners do their work better,” said Aaron Harris, Chief Technology Officer at Sage. “That means reducing manual work, improving visibility and helping people act faster with confidence. In finance, ‘almost right’ isn’t good enough. AI must be accurate, auditable and reliable in real workflows, not just impressive in a demo.”
Intelligent agents that help finance teams act with control
At the center of Sage’s latest advancements is the Sage Intacct Finance Intelligence Agent, which is being rolled out as part of a phased release. It marks a shift from AI that supports analysis to AI that helps finance teams progress work directly within their workflows.
Built on Sage’s financial AI models, the Finance Intelligence Agent allows users to interact with the system using natural language. It can prepare tasks such as payment reminders and approvals within existing workflows, while keeping people in control of final decisions.
Every recommendation includes a clear explanation of the underlying data, logic and assumptions, allowing users to understand and interrogate how outputs are generated. This enables finance teams to move from manual execution to review and decision-making, with greater confidence in the results.
All AI-driven actions are logged, providing full visibility of what was recommended, what was approved and by whom. This creates a complete audit trail, supporting confidence, control and accountability in finance where accuracy and traceability are critical.
A governed platform for partner-built AI
Sage is also expanding its AI platform to enable partners and developers to build new solutions that integrate directly with Sage data and customer workflows. New capabilities including AI Gateway, Agent Builder tools and a dedicated Agent Marketplace will allow partners to design and deploy specialized AI agents tailored to specific industries while meeting Sage standards for trust, security, and interoperability. This opens the next wave of partner-led innovation, enabling partners to build agents that carry their expertise directly into customer workflows.
“AI is transforming how businesses operate, and partners will play a critical role in helping customers adopt these technologies in ways that deliver real value,” said Gretchen O’Hara, EVP Strategic Partnerships and Business Development, Sage. “By opening the Sage platform with strong governance at its core, we are creating new opportunities for innovation across our ecosystem.”
Financial systems require deterministic rules and auditability, so Sage follows a glass box approach to AI. This ensures recommendations remain transparent, explainable and auditable, so organizations can trust the systems running their most critical workflows.
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