As the next stage in the evolution of artificial intelligence, agentic systems have the potential to deliver groundbreaking productivity and performance improvements for small and mid-sized businesses (SMBs). We explain how AI agents work, look at some of the most effective uses of the technology, and highlight how businesses such as Sage are accelerating innovation in this area while prioritising safety and reliability.
By Chris Torney
Change agents: How agentic AI is poised to transform SMB productivity
AI agents offer businesses the opportunity to streamline processes, increase efficiency and make smarter, faster decisions. Agentic AI is set to have a transformative impact on global productivity – provided it is implemented carefully and responsibly.
The widespread adoption of the generative AI services provided by large language models (LLMs) such as OpenAI’s ChatGPT and Google’s Gemini is just a staging post in the AI revolution. A new iteration of the technology – agentic AI – has the potential to help businesses drive significant productivity and efficiency gains by automating a wide range of tasks and processes. AI agents are also able to make instant decisions and interact with other agents, such as those employed by SMBs’ customers, suppliers and accountants.
“AI is already transforming how SMBs operate, and because automation has been part of our products for nearly a decade, we’re building on a foundation our customers already trust,” says Aaron Harris, Chief Technology Officer at Sage. “We’re not just delivering generative intelligence, we’re making sure that intelligence scales across workflows and we’re building toward autonomous capabilities that can support smarter, faster, more confident decision-making.”
Agentic AI: building on the progress of generative AI
Generative AI is a technology that creates content, such as text, images and even video, in response to a user’s questions or prompts. It can also analyse data and write software code based on specific instructions. Sage Copilot, for example, helps customers to uncover operational insights, analyse financial information and speed up processes such as the month-end close.
Agentic AI, on the other hand, refers to systems that can coordinate tasks, make reasoned decisions and take actions – within certain parameters – with minimal direct human involvement.
“AI agents are purpose-built systems that use LLMs as their core engine to execute tasks,” explains Kamales Lardi, the author of Artificial Intelligence for Business and an expert on AI transformation. “As an analogy, the LLMs function as the ‘brain’ of the system, while the agents are the ‘worker bees’ designed to complete tasks by combining the brainpower with tools, data and predefined step-by-step instructions.”
“AI agents are not just futuristic novelties; they are practical tools delivering measurable value for businesses today,” adds Kevin Quirk, director of technology consultant AI Bridge Solutions. “For SMBs, they represent a unique opportunity to close operational gaps, automate workflows and unlock new levels of productivity without significantly increasing overheads.”
How AI agents are already driving growth
Duncan Kreeger, the founder and CEO of property finance company TAB, says: “As someone who has spent over 15 years building businesses in property lending, I have seen first-hand what slows companies down: repetitive tasks, legacy systems and human bottlenecks. At TAB, speed and certainty are everything. That is where AI agents come in.”
He adds: “In our industry, we are now using agents to screen property deals, flag anomalies in loan applications and assist with underwriting. They operate around the clock, never miss a step and reduce the risk of human error. I have seen mortgage brokers integrate agents to run affordability checks, complete compliance logs, and automate lead qualification, often without the client even noticing. The gains in speed and accuracy are material.”
Kreeger points out that adopting an AI agent should usually be a straightforward process. “It is not a heavy lift: just assign a task, give it access to the right data, and let it run. The first one might manage five hours of admin a week. The next, 50. The benefits compound quickly. What starts as a tool becomes part of the team.”
Maintaining trust while implementing agentic AI
Businesses that use AI in any form should be aware of potential ethical concerns and implications – not least when using AI agents.
“AI agents will be able to take over a broad range of actions across organisational functions, including hiring, customer service and decision support,” Lardi explains. “The very autonomy that makes AI agents powerful and unique also poses a danger for companies adopting them. For example, the absence of human oversight and governance raises concerns about fairness, bias and accountability. To maintain trust, organisations must design workflows with transparency, traceability and ethical oversight built in to manage the AI agents.”
Quirk says: “At AI Bridge Solutions, what sets our approach apart is a focus on ethical deployment. Every AI agent we design operates within clear boundaries and is fully auditable. We embed guardrails that align with regulatory requirements and stakeholder expectations. This builds trust, not just with employees who are working alongside these tools, but with customers and partners too.”
“The narrative that AI agents replace jobs is an oversimplification. Instead, they evolve roles. Much like how [cloud computing technology] VMware revolutionised IT infrastructure and freed engineers to innovate rather than configure, AI agents are enabling staff to shift from execution to strategy. From legal clerks using AI to draft contracts to HR departments using agents to triage employee queries, the impact is cross-functional and positive.”
At the recent flagship Sage Future event, Sage unveiled its roadmap for the adoption of agentic AI. As well as embedding AI into its products, the company is transforming how products are built in the first place: by providing developers with access to shared frameworks, smart tooling and built-in guardrails, Sage is accelerating innovation without compromising trust.
Ashok Patel, research manager at market intelligence firm IDC, says: “While agentic AI represents a new phase in the evolution of enterprise applications, it is essential for vendors to ensure that its deployment addresses real-world challenges and delivers tangible benefits to users.
“Sage’s roadmap reflects a measured, phased approach to embracing agentic AI in ways grounded in the practical needs of SMBs. The vendor is embedding this technology into business workflows and processes, while maintaining a clear emphasis on transparency and trust – principles that are central to responsible AI adoption.”
Meanwhile, Sage has also launched a new AI Trust Label that is designed to provide customers with clear information about how AI is developed and used within business software. “Businesses deserve to know how the technology works, how their data is used and what safeguards are in place,” says Harris. “The AI Trust Label is a direct response to that need – for transparency, not assumptions.”
