Hi

As a chartered accountant and small business adviser, I’ve been following the rapid rise of agentic AI – a new generation of AI tools that can act more autonomously. 

You might already use software like Xero for accounting or simple AI chatbots for customer service. Now there’s talk of AI “agents” that can make certain decisions on their own. 

What does that mean for a business like yours, and why should you care? In this email, I’ll explain in plain terms what agentic AI is, why it’s relevant to small businesses right now, and how it could change your day-to-day operations. I’ll also share specific examples across retail, consultancy and manufacturing, and end with concrete steps you can take to prepare. Let’s dive in.

What Is Agentic AI (In Simple Terms)?

Think of agentic AI as an AI system that can make decisions and take actions by itself to achieve goals you set – all without needing you to micromanage every step. In other words, it’s like having a super-smart digital assistant or “agent” that doesn’t just follow strict rules, but can adapt, decide, and act on your behalf in certain contexts. 

For a small business, this isn’t sci-fi – it’s the next step beyond basic automation. For example, an agentic AI could automatically manage your inventory: it might notice stock running low and decide to reorder from the supplier (based on rules you’ve approved) without waiting for you to click a button. 

Or it could monitor your cash flow and take action by moving money into a savings account when it predicts a slow month, aligning with goals you’ve defined. The key difference from traditional software is that agentic AI has a degree of autonomy: once you set the goals and guardrails, it can figure out the how and carry out tasks, rather than just doing exactly what it’s told step-by-step.

Importantly, agentic AI isn’t about taking all control away from you. It’s about delegating routine or data-heavy decisions to reliable AI helpers so that you and your team can focus on the decisions that matter most. You remain the boss setting the strategy and handling critical judgments – the AI agents handle well-defined tasks in the background. 

This preserves human expertise where it’s most crucial, while offloading work that a machine can do faster or even better with vast data. In short, agentic AI is a practical partnership: you set the direction, the AI figures out the details within set boundaries.

Why Small Businesses Need to Pay Attention Now

You might be thinking, “This sounds interesting, but isn’t autonomous AI something only big businesses use?” That used to be true. Cutting-edge AI often started in large businesses with big budgets. But the landscape has changed dramatically in the last year or two. AI tools have become far more accessible and affordable, even for the smallest firms. 

A recent Chamber of Commerce report found that AI adoption among small businesses jumped from 40% in 2023 to 98% in 2024. Essentially almost every small business is now using AI in some form, whether it’s the smart features in Excel, an email marketing automation, or a bookkeeping assistant. AI has become as standard as smartphones – a must-have tool to compete and stay efficient.

So where does agentic AI fit in? Consider it the next stage of this AI evolution. Large organisations are already restructuring how they operate around autonomous AI decision-makers, and it’s creating performance gaps. In an IBM survey of 800 businesses, 24% said they already let AI agents take independent action in their company today, and 67% expect to do so by 2027.

The technologies behind agentic AI – from advanced chatbots to intelligent process automation – are increasingly available via cloud services and user-friendly platforms. This means small businesses can plug into these autonomous capabilities without massive IT investments, much like subscribing to software-as-a-service.

Crucially, paying attention now gives you a competitive edge. Early adopter small businesses will be able to do things that slower competitors can’t. Agentic AI isn’t just about doing the same work faster; it’s often about enabling completely new capabilities.

For example, a small retailer might use AI to dynamically adjust prices or offer personalised deals – something that would be impossible to do manually in real-time. A local manufacturer could run an AI agent to continuously fine-tune production schedules based on live sensor data and orders, achieving efficiency gains that larger rivals (who haven’t embraced AI) would envy. 

In short, this technology can level the playing field with bigger competitors by letting a lean small business act smarter and punch above its weight. On the flip side, ignoring it could mean falling behind: if your competitors start using agentic AI to deliver faster service, better predictions, or lower costs, customers may gravitate towards those advantages.

Lastly, there’s a strategic reason to start thinking about it now. Business advisors (myself included) are seeing that getting the full benefit of AI might require rethinking some of your processes. In the IBM study, 78% of executives said that to get maximum benefit from agentic AI, they needed to change how their business operates. 

In a small business context, that means it’s wise to gradually redesign certain workflows to integrate AI, rather than just bolting it on. The sooner you start experimenting and learning, the easier it will be to adapt your business model when autonomous tools become the norm.

How Could Agentic AI Affect Different Sectors?

Every business is unique, but here are a few examples of how agentic AI could make an impact in various small business sectors:

E-commerce 

Imagine you run a shop or an online store. An agentic AI could act like an always-on inventory manager. It can monitor stock levels and sales patterns in real time, then take action by reordering products or suggesting stock transfers between locations – all automatically. 

If certain products are not selling, the AI might lower the price or launch a targeted promotion to clear inventory (following rules you set). On the customer side, AI agents could personalise shopping experiences, such as automatically recommending items to customers based on current trends and the customer’s preferences. 

There are already early examples of dynamic pricing tools that adjust prices based on demand and stock – small retailers using these AI-driven pricing agents have seen immediate benefits in sales and margins. In essence, mundane decisions like stock replenishment, pricing changes, and loyalty offers could be handled by AI, freeing you to focus on merchandising and customer relationships.

Professional Services/Consultancy 

Suppose you’re a consultant, marketing agency, or run an accounting/bookkeeping practice. You deal with lots of information and client needs. An AI agent here could be your tireless research assistant or project coordinator. 

For instance, an agentic AI could continuously scan industry news, regulatory updates, or social media trends relevant to your clients, and autonomously flag opportunities or risks. 

In a small accounting firm, an AI agent could monitor changes in tax legislation and automatically update checklists or client advice templates – so you’re always up-to-date without having to manually research every change. 

For a marketing consultant, an AI might automatically A/B test different campaign ideas across digital channels, then allocate budget to the best performers on its own. These agents can also handle routine follow-ups: a chatbot agent might engage incoming client enquiries, gather initial information, even schedule meetings on your calendar if the prospect fits certain criteria. 

All this means your workflow could have a lot of “busy work” trimmed out – proposals drafted to 80% completion by AI, reports auto-generated and ready for your expert polish, and administrative decisions (like scheduling or initial qualification) done without occupying your time.

Small-Scale Manufacturing

 In a manufacturing or fabrication business, agentic AI can operate as a kind of autonomous operations manager. Picture a production floor where an AI agent monitors machine performance and output quality continuously. If it detects a machine is likely to overheat or produce defects (through sensor data analysis), it can decide to adjust the machine’s settings or schedule a maintenance check – avoiding downtime without a manager’s intervention. 

Similarly, an AI system could oversee your supply chain: if a shipment is delayed, the AI finds an alternative supplier or reschedules production sequences to minimise idle time. Small manufacturers are also experimenting with AI-driven scheduling, where the system juggles work orders and workforce availability autonomously to meet deadlines most efficiently. 

Even trades like plumbing or equipment servicing could use an AI agent to dispatch jobs: the AI could automatically assign field technicians based on location, expertise, and current traffic conditions, optimising daily routes without a person manually coordinating. The result is a smoother operation where many micro-decisions (when to service a machine, which job to do next, how to reroute supply orders) are handled swiftly by AI, and you step in only for exceptions or strategic choices.

These scenarios aren’t meant to be far-fetched; many of the capabilities exist in early forms today, and they will become more robust very soon. The common theme is that agentic AI can take over a layer of decision-making that currently eats up a lot of owner or manager time – especially decisions that rely on monitoring data and reacting fast. By delegating those to an AI, small businesses can react in real time to changes in a way that normally would require a full team working around the clock.

Changing Workflows and Decision-Making Processes

Adopting agentic AI will likely reshape some of your daily workflows. It’s not just inserting a new tool, but adjusting who (or what) does which tasks:

• Faster Decisions, Fewer Bottlenecks: One immediate change is speed. Tasks that used to wait for you or a staff member to notice and act on can be handled instantly by an AI agent. For example, if an online order triggers a low-stock alert, an AI can place a restock order within minutes. No more “end of day” manual checks needed. This reduces bottlenecks and keeps the business running smoothly 24/7. Decisions that are time-sensitive or data-intensive are especially suited to AI, because the agent can crunch numbers or check conditions far quicker than a human, and it never has an off day.

• Human Role as Overseer and Strategist: As more routine decisions get automated, your role and your team’s roles will evolve to oversight and strategy. You’ll spend less time ticking boxes or approving every small action, and more time reviewing the AI’s performance and focusing on big-picture questions. In effect, your workflow might shift to managing by exception – letting the AI handle normal cases and only stepping in when something unusual happens or a critical judgment call is needed. This can actually enhance control: you’ll have dashboards or reports of what your AI agents decided each day, and you can set parameters for when to be notified or when to require human sign-off. For instance, you might allow an AI agent to approve customer refunds up to £50 on its own, but anything higher comes to you. Over time, as trust grows, you might adjust those thresholds. Preserving trust and transparency is key: you’ll want visibility into how the AI is making decisions so you feel comfortable with its autonomy. Tools can log each action an agent takes – think of it like an audit trail – which is good for confidence (and compliance if needed).

• Collaborative Workflows: Rather than replacing employees, agentic AI often works alongside people. Your team might need to learn new ways of working, like checking an AI’s recommendations and giving feedback. In fact, businesses that succeed with autonomous AI treat it as a collaboration: the AI does the heavy lifting of data analysis and routine action, while humans handle customer interactions, creative thinking, and final approvals. This might mean updating job descriptions – for example, a sales manager might also become an “AI supervisor,” monitoring an algorithm that scores leads or sets prices. It’s a shift to a hybrid workforce model, where AI is like another team member. Your staff might initially worry about job security, so it’s important to communicate that the goal is to remove drudgery, not eliminate people. Many tasks will be upgraded – instead of manually compiling reports, an employee now interprets the AI-generated report and uses it to plan strategy.

• Decision Processes and Checks: We’ll also likely incorporate new checkpoints or KPIs to manage autonomous decisions. Just as you might track an employee’s performance, you’ll track your AI agent’s performance. Metrics like “How often did the AI have to hand off to a human?” or “Was the AI’s decision correct in hindsight?” become important. For example, if your customer service bot is handling enquiries, you might measure how many queries it resolves vs. how many it escalates. This helps identify if the AI is genuinely helpful or if it’s hitting its limits too often. 

The upshot is that decision-making becomes a blend of AI-driven decisions and human oversight. Workflows will include steps where AI does X, human reviews Y – a new kind of dance. Initially it may feel odd to trust a machine with decisions, but with the right monitoring in place, it can become as routine as trusting a software to calculate your VAT correctly.

How to Prepare Now: Concrete Actions

Transitioning to an AI-enhanced business doesn’t happen overnight. Here are some concrete steps you can take now to get ready for agentic AI and ensure your business is set up for success:

1. Educate and Stay Informed: Make it a point to learn a bit more about AI developments in your industry. Subscribe to a relevant newsletter or join a local business workshop on AI. The goal isn’t to become an AI expert, but to know what’s possible. The more you understand the capabilities (and limitations), the better you can spot opportunities in your business.
2. Identify Quick-Win Opportunities: Look at your daily operations and pinpoint repetitive, decision-heavy tasks that eat up your time or delay your service. Is it reordering stock? Chasing late invoices? Scheduling appointments? These are prime candidates where even basic AI or automation can help now, paving the way for more autonomous solutions. Start listing areas where a “digital helper” could make a difference.
3. Clean Up Your Data and Systems: Agentic AI thrives on data. Take this time to organise your digital information – whether it’s ensuring your financial data in Xero is up-to-date and categorized consistently or cleaning up your customer database. Also, check that the different software you use can integrate or share data (many modern tools can connect with each other). The better your data and system integration, the easier it is to add AI on top. Think of it like fuel for the AI engine: high-quality data in means better decisions out.
4. Experiment with Existing AI Tools: You don’t have to build a custom AI from scratch. Many tools you already use may offer AI features – try them out. For example, Xero has been adding AI-driven features for things like smart reconciliation suggestions. There are affordable AI plugins or services for email marketing, customer support, and more. Start with a small pilot in one area. For instance, you might deploy a chatbot on your website to answer common questions or use an AI scheduling assistant to handle meeting bookings. This hands-on experience will help your team get comfortable with AI making some decisions (even minor ones) and learn what works best.
5. Train and Involve Your Team: As you introduce AI agents, involve your team from the start. Provide training so they understand how the AI tools work and how their roles might shift. Emphasise that AI is there to handle the grunt work and assist them, not replace them. Encourage a culture where the team gives feedback on AI outputs – for example, if an AI-generated report misses a key insight, the team should flag it. This two-way learning makes the AI better and helps staff feel ownership. The more your people become “AI-literate”, the more value you’ll get from the tools. (On the flip side, lacking the skills to use AI could become a bottleneck – so invest in your people’s skills now.)
6. Set Clear Policies and Monitor Results: When you let an AI agent start making certain decisions, set clear rules and limits. Define what it can and cannot do. For example, “the AI can respond to customer emails, but it won’t issue refunds above £50 without approval” or “it can reorder supplies up to a cost limit per week”. Put in place a monitoring system – many AI tools provide logs or summaries. Make time to review these regularly, especially at the start. This way, you maintain oversight and can catch any issues early. Over time, as confidence grows, you might relax some limits. Always keep an eye on outcomes: is the AI achieving the goal (e.g. keeping stock levels optimal, responding to customers faster)? Use those new KPIs – like error rates, response times, or cost savings – to measure the AI’s impact.
7. Plan for Ethical and Trustworthy AI Use: Finally, consider the ethical dimension. Small businesses earn customer trust by being honest and personal – don’t lose that as you automate. Be transparent with customers if AI is involved in certain interactions (for instance, if you use an AI chatbot, let users know they’re chatting with an AI, and give them an option to reach a human). Ensure you’re using data responsibly and in compliance with privacy laws. Choosing AI tools that can explain their decisions (or at least provide reasoning) will help maintain trust. In short, treat your AI agents like new team members – they need guidelines and values to follow, just as any employee would.

By taking these steps, you’ll build a strong foundation for agentic AI in your business. It’s not about jumping in all at once, but about being prepared. Businesses that slowly incorporate AI and learn from it will be in a much better position than those that ignore it until it’s unavoidable.

Agentic AI is no longer a distant idea – it’s arriving in tools and services around us. Small businesses that embrace this shift early can reinvent parts of their operations, achieve efficiencies, and open up new opportunities that were once out of reach. Those that don’t risk playing catch-up in a few years when autonomous decision-making becomes standard. 

The good news is, you don’t need a PhD in AI or a big IT department to get started. As I’ve outlined, small practical steps today – from educating yourself to trying out AI in one area – can set you on the right path.

I encourage you to think about where an “AI agent” could be your next helpful team member. If you’re unsure how to begin, let’s have a chat. 

Whether it’s making sense of the latest trends or figuring out which process to automate first, I’m here to help you work through it. Small businesses are often nimble and innovative – this is another chance to prove that advantage by adapting faster than the big players.

Noel Guilford

PS Pick one of the steps above and put it into practice this month. Even a tiny experiment can teach you a lot. Feel free to reply to this email with any questions or to set up a meeting – I’d be happy to discuss how agentic AI could fit into your business.