TLDR: Sage is spearheading a new ‘Agentic AI era’ to transform finance for small and medium businesses (SMBs). This initiative moves beyond traditional and generative AI, introducing autonomous AI agents capable of reasoning, planning, and executing complex tasks with minimal human intervention. The company emphasizes trust, transparency, and accountability through its ‘AI Trust Label’ and five core AI commitments, aiming to empower finance professionals with real-time insights and strategic capabilities.
Sage is charting a new course in financial technology, ushering in what it terms the ‘Agentic AI era.’ This strategic shift aims to profoundly impact finance professionals and significantly boost productivity for small and medium businesses (SMBs) by deploying autonomous AI agents. Aaron Harris, CTO of Sage, articulated this vision, emphasizing that agentic AI represents a fundamental leap from reactive to truly autonomous systems, capable of independently pursuing complex goals with minimal human supervision .
Unlike conventional AI tools that merely respond to prompts, agentic AI systems are designed to actively reason, plan, and utilize digital tools to complete entire multi-step tasks. This evolution transforms AI from a passive assistant into a proactive digital worker, poised to disrupt numerous industries, particularly finance . Kamales Lardi, author of ‘Artificial Intelligence for Business,’ aptly describes this by stating, ‘LLMs are the brains, agents are the worker bees’ .
The benefits for finance teams are extensive. Agentic AI is expected to free up considerable time, allowing professionals to focus on strategic insights, business advisory, and forward-looking planning. This is achieved through ‘continuous accounting,’ where intelligent systems monitor exceptions, detect anomalies, and correct patterns; ‘continuous assurance,’ providing real-time data reconciliation and variance analysis; and ‘continuous insight,’ delivering contextual, actionable updates and recommendations without the need for manual report generation . Dan Miller, Sage EVP of Financials and ERP, noted that tasks like reconciliation and variance analysis will start earlier, be flagged sooner, and be completed faster .
Sage’s journey into AI has unfolded in three distinct waves. The first involved ‘Task-based AI,’ embedding machine learning for automating repetitive tasks like invoice categorization. This was followed by ‘Generative AI,’ exemplified by Sage Copilot, which assists finance teams in drafting reports, answering queries, and surfacing relevant data. Currently, over 40,000 Sage customers globally utilize Sage Copilot . The third and current wave, ‘Agentic AI,’ builds upon these foundations, combining predictive, generative, and agentic technologies to enable autonomous actions and orchestrated intelligence .
Central to Sage’s strategy is an unwavering commitment to trust and transparency. Aaron Harris highlighted that trust is ‘non-negotiable’ in AI, especially within the finance sector . To this end, Sage has introduced the ‘AI Trust Label,’ a pioneering initiative providing clear, accessible insights into how its AI solutions are developed and operate. This label details how data is protected, bias is mitigated, and ethical safeguards are in place, directly addressing concerns raised by SMBs . Sage’s dedication is further underscored by five AI commitments, ensuring solutions are built ethically and without bias, aligning with frameworks like the NIST AI Risk Management Framework and the UK Government’s AI Cyber Security Code of Practice .
Sage has deliberately chosen to train its own large language models, rather than relying on generic off-the-shelf models, to ensure precision, consistency, and accountability in a financial context. These internal models, built on 7 billion parameters, are trained on accounting standards, real-world customer and compliance data, industry-specific terminology, and Sage product documentation. This specialized training ensures predictable, audit-ready outcomes, which are critical for CFOs and auditors . Furthermore, Sage announced a partnership with the AICPA to train its models on the profession’s official content, a move Harris described as ‘a signal to the industry that we’re building AI you can trust’ .
Also Read:
- FactSet Highlights Modular AI Agents as Catalyst for Finance’s New Operating System
- Agentic AI Adoption: Tech Sector Accelerates While Manufacturing Lags
The agentic AI market is projected to grow rapidly, from an estimated $5 billion today to $47 billion by 2030 . This growth is fueled by the tangible value AI agents deliver, automating workflows and increasing productivity without significant overhead, as noted by Kevin Quirk of AI Bridge Solutions . Stripe reports that its top 100 AI companies have seen almost double the revenue growth compared to SaaS counterparts, underscoring the financial impact of AI . Sage’s vision for agentic AI is not just about technological advancement; it’s about empowering finance leaders to embrace a future where insight finds them, enabling smarter, faster, and more confident decision-making.
