Not every AI tool deserves a place in your budget. Our experts share the questions every small business owner should ask before paying for one, in this week’s Let’s Talk.
Every week there is a new AI tool promising to save you time, cut costs, and transform your workflow.
For small business owners already stretched thin, the real question is not whether AI is useful. It is whether the specific tool in front of you is worth the line item on your budget. We asked the experts how to make that call before you commit.
Let’s Talk!
Angad Soin, Global Chief Strategy Officer and Managing Director for Australia and New Zealand, Xero
“Every time you look online, there’s a new AI tool promising to run elements of your business while you sleep. But for most small business owners, paying for another subscription doesn’t create freedom – it just creates another login and another system to figure out, usually after-hours or on the weekend.
The truth is, AI only pays off if you use it deliberately. At Xero, we recently looked at the data and found a divide: small businesses using AI daily are twice as likely to see revenue increase (28% compared to 12% for non-users). But those successful owners aren’t throwing money at random AI tools. They are doing two things differently.
First, they’re using the AI already built into the tools they pay for; they aren’t buying new standalone apps. The most valuable AI isn’t flashy, it’s embedded. It’s the invisible helper providing smart reconciliation, invoice reminders to nudge late payers and improve cashflow. The email draft that saves minutes every time, compounding to less weekend work. It does the heavy lifting without forcing you to change how you work.
Second, they’re solving one specific problem at a time. AI doesn’t fix chaos. If processes are unclear, automation accelerates the mess. Successful small business owners start by asking: “Where am I losing time every week?”
Before paying for an AI upgrade, pinpoint where you are bleeding time. If a paid feature removes one hour of low-value admin, the real return isn’t the saved hour itself. It’s what you do with it.
The true return on investment is taking that reclaimed hour, picking up the phone and talking to your best customer. Ultimately, AI shouldn’t replace your judgment; it should create space for it.
For Australian small businesses, the opportunity isn’t to automate everything. It’s to automate what doesn’t need your brain – so you can focus on what does.”
Sergio Aguilera, APAC Head of Solutions Engineering, Zoom
“Deciding which AI tools are worth paying for starts with identifying where AI can deliver measurable value. Ask yourself: Will this save time on repetitive tasks? Will it reduce errors? Is the AI acting as a partner or just a feature?
Agentic AI tools, like Zoom AI Companion 3.0, don’t just assist but take the initiative. For example, rather than simply having an AI tool that converts a meeting to text and generates a summary, a proactive AI agent can generate and assign action items and help complete follow-ups. This propels your work forward – essentially going from conversation to completion.
Integration is another critical factor when evaluating AI tools. The most effective solutions fit seamlessly into existing workflows and can draw on multiple AI models to complement each other, allowing organisations to harness innovation without disrupting established processes.
If you’re only starting to experiment with these tools, check the fine print as there are free versions that offer sophisticated core features, such as agentic retrieval and meeting summaries, which may be ample for your needs. Paying for AI makes sense if it transforms the pace of work and the strategic focus, becoming a competitive advantage and ultimately a profit driver rather than a cost centre.”
Jonathan Tanner, Senior Director, Industry Principal Financial Services & Insurance APAC, Pegasystems
“When deciding whether to introduce AI tooling on top of existing systems or continue with existing processes, we must look beyond speed or novelty and ask: will this tool truly solve a pain point in my organisation, or will it become a pain point itself?
This means weighing the full cost of adoption, including workflow redesign, change management, and integration with existing systems to name but a few. These factors form the foundations shaping whether the investment truly pays off.
Implementing AI isn’t simply plug-and-play, it requires modernised systems that provide high-quality integrated data, strong governance, and scalable technology foundations that AI can connect with, learn from and enhance existing processes. The cost and complexity of maintaining outdated systems, a.k.a. technical debt, is one of the biggest barriers to adopting AI effectively, because legacy systems often block integration, slow innovation, and inflate maintenance costs. Addressing this through structured legacy transformation creates the foundation needed for AI to deliver real value, rather than add friction.
So, the question then becomes: will paying for this AI tool help reduce manual pain points and improve your core systems? If not, the manual might be wiser until your systems are ready.”
Inbal Rodnay, AI and tech adoption specialist, Inbal Rodnay
“Many of the AI tools on the market are in the early testing mode. The early minority are comfortable experimenting in public. They accept bugs, shifting features, and changing terms of service. The Confident Majority doesn’t need to operate like that. Speed isn’t a good strategy. it;s worth taking the time to observe, learn from what stabilises, and adopt tools once they are secure, and proven.
The danger isn’t just wasted money. It’s fragmented processes, inconsistent outputs, staff using tools without guidance, and confidential information being handled in ways the business cannot properly control. Even worse, you get AI theatre where leadership feels like progress is happening, but nobody can explain what’s approved or banned, or what good use looks like.
AI literacy and internal guidelines must come first before you buy the latest tool.
Before you pay for anything, you need three things: a shared understanding of what AI can and cannot do, clear rules about data and confidentiality, and a small set of approved use cases that map to your real workflows.
Don’t start with the tool. Start with the friction. Where are you or your team repeating the same task more than three times a week? Where are delays happening? Where is manual rework creeping in? If an AI tool directly removes that friction and can demonstrate time saved within 30 days, it’s worth testing.
Then check integration, not features. A powerful tool that doesn’t sit inside your existing workflow will create more work, not less and then test before you commit. Most AI tools offer trials. Run a small pilot with one workflow and measure impact. Did it save time? Improve consistency? Reduce follow-up? If not, stay manual.
Before you rush to buy a new standalone AI tool, look at the platforms you already pay for, whether that’s Gmail, Microsoft 365, Xero or your practice management system; many have embedded powerful AI features inside their existing ecosystem that can solve 70% of your needs without adding another subscription or layer of risk.”
Mandy Galmes, Managing Partner – Australia, Sefiani, part of Clarity Global
“AI search is fast becoming the front door to your business. Whether you’re a B2B or B2C company, customers are discovering and shortlisting your brand via AI. This means if you’re not actively managing how your brand shows up in AI search right now, you’re well and truly on the back foot.
This doesn’t mean spraying more content and hoping for the best. Your AI spend needs to be strategic and focused. Invest in tools that do three things: intelligence, automation and measurement.
- Intelligence tells you what AI tools are actually saying about your business, where the story is wrong or where your competitors are showing up more than you.
- Automation removes time-consuming and administratively burdensome tasks, allowing smaller teams to focus on strategic decision making, creativity and building relationships.
- Measurement links what you change – your messaging, content, and service – to what customers see, believe and do.
The bottom line? Pay for tools that earn their keep. AI tools should help you buy back time, reduce risk and shape the story that AI search models tell about your brand. By investing in AI visibility tools, you ensure your brand remains seen and discovered in a very noisy market.”
Cynthia Lee, APAC Vice President at Delinea
“When deciding whether to pay for an AI tool, most businesses focus on productivity. Will it save time? Reduce manual effort? Help teams move faster? That’s a sensible starting point. But an equally important question is: what data and level of access does the tool need to do its job?
Many AI tools require direct access to internal systems, cloud platforms, shared drives or code repositories to deliver benefits at scale. For example, an AI agent may operate continuously in the background, much like a digital employee with its own identity and permissions.
If an AI tool needs ongoing access to sensitive data, organisations must understand exactly what it can see, what it can change, and how long that access lasts.
You will need to manage AI tools or AI agents like any other employee. Their access to data should be limited to what’s necessary, granted only when needed, revoked when complete, and fully auditable. If you can’t control and regularly review that access, the convenience of automation can come at a cost, and the productivity gains may not outweigh the risks.”
Erich Kron, CISO Advisor, KnowBe4
“When it comes to choosing which AI tools are worth paying for, it really comes down to how prepared your people are. A tool can be powerful on paper, but if teams don’t understand how it works or how to use it safely, it’s unlikely to deliver the value organisations hope for.
We’re seeing a lot of companies rushing to adopt AI because they feel the pressure to ‘keep up,’ and that’s where things can go wrong. Having the right education and a basic level of AI literacy, including how data is handled, what risks to look out for, and where human judgment still needs to be applied, is imperative. Without this, businesses may end up with tools that create more risks than improved efficiency.
A good starting point is asking: Do our people feel confident using this? Do they understand the guardrails? And if the answer is yes, it becomes much easier to evaluate whether a paid tool genuinely improves workflow, reduces friction, or strengthens decision‑making. But if the answer is no, it’s worth stepping back and considering what foundations need to be built first.
The companies making the best decisions about AI adoption are the ones taking the time to prepare their workforce. Once people understand the technology, they’re far better equipped to make informed choices and adopt AI tools effectively.”
Tracy Moore, General Manager Data and AI, MYOB
“Australian small business owners are hearing AI will “change everything” – and they’re right to be curious. But the “change everything” framing sets the wrong expectation. The tools worth paying for aren’t the ones that automate what you’re already doing. They’re the ones that do things your business genuinely couldn’t do before: spotting a cash flow problem before it bites, catching a compliance gap before it costs you, or following up a late invoice at 11pm without anyone lifting a finger.
The AI tools worth paying for are the ones that measurably improve how work gets done, by freeing up time, reducing risk or strengthening decision-making. Start with the work, not the technology. Start by listing the tasks that quietly drain your week – the ones you postpone, batch up on Friday afternoons, or secretly dread. If something is repetitive, rule-based and time-consuming, it’s a candidate. But don’t stop there. The bigger opportunity is the work that never got done at all because it required expertise or time your business didn’t have.
Our MYOB November 2025 Business Monitor data shows around 40% of SMEs expect AI to deliver productivity or efficiency gains in 2026. That’s encouraging – but efficiency is actually the floor, not the ceiling. The businesses pulling ahead are using AI to do things that weren’t economically possible for a small team before.
Before committing to a paid tool, ask three questions:
- Does it give you a capability you genuinely didn’t have before – not just a faster version of something you could already do?”
- Does it integrate seamlessly with the systems we already rely on?
- Will it improve visibility, compliance, confidence, or decision quality?
If the answer is yes to at least one, the investment is worth testing.
At MYOB, we don’t add AI for its own sake. We ask: what decisions or tasks could our customers do better with a capable digital teammate alongside them? Then we measure it before we scale it.
The tools worth paying for are the ones that become genuinely indispensable – not because they’re impressive, but because your business would feel their absence.”
Ben Young, Field CTO, APJ, Veeam
“With a cybercrime reported every six minutes in Australia, manual security processes are struggling to keep pace – and the gap is widening. Threat actors are already using AI to scale attacks, find vulnerabilities, and write exploits faster than human teams can respond.
The decision to invest comes down to a few clear signals: alert fatigue, detection timelines measured in days, and threats you know about but can’t act on. When those signs are present, the tools that deliver real value aren’t just those that detect threats – they’re the ones built around your data. Visibility into where your data lives and how it’s behaving is critical for detecting early warning signs like ransomware and indicators of compromise, and for breach analysis during an active attack. That’s where data resilience platforms earn their place – not just as a recovery safety net, but as an active layer in your security posture.
The question isn’t whether to invest. It’s whether your platform gives you the visibility to detect threats early and the resilience to recover fast when it matters most.”
Damien Brennan, Strategic AI and Emerging Tech Partnership Manager, APAC, Sinch
“When deciding if an AI tool is worth paying for, businesses should look beyond the algorithm. The true value of any AI tool is not what it knows, but what it can reliably do.
This reliability is what customers demand. Our 2025 State of Customer Communications report found that people respond best to experiences that feel continuous across channels, favouring AI that remembers context, and saves them from repeating themselves. When a chatbot drops a message or a voicebot has poor call quality, it does not just fail a task; it disrupts that seamless experience, creating frustration and a negative ROI.
The same report reveals that two-thirds (66%) of Australians do not fully trust AI’s accuracy, and only a quarter (27%) are comfortable using it for support. This scepticism means every failed interaction does not just frustrate a customer; it validates their mistrust.
With agentic AI, the stakes are higher, because its value rests on whether it can autonomously complete tasks in a way that builds customer trust, not on how impressive its answers sound.
Businesses must shift focus from algorithms to outcomes. AI succeeds when it can reliably communicate and execute at scale. That is where the ROI lies.”
Anthony Capano, Regional Director, APAC, Intuit Mailchimp
“The smartest way to decide if an AI tool is worth paying for is to look at where manual work is slowing you down without improving outcomes.
For many small businesses, the most practical option is choosing platforms with built-in AI rather than adding standalone tools. Every new tool adds cost and complexity, and it’s essential to have a system that integrates cleanly with your data. When AI sits inside a platform you already use, your data stays connected, training and onboarding teams is simpler, and you can move from insight to action faster. For instance, Intuit Mailchimp recently introduced predictive analytics, AI-powered content tools and a ChatGPT integration that helps teams create, refine and launch omnichannel campaigns.
Start with the tasks that drain time, like setting up triggered emails or compiling regular reports. If AI can enable your team to dedicate effort for higher-value, strategic tasks, like strengthening customer relationships, it delivers value. Ultimately, the tools worth paying for are ones that accomplish tasks that don’t require human creativity, freeing you up for work that does.”
Kumar Mitra, Executive Director, CAP & ANZ,Lenovo Infrastructure Solutions Group
“As a business, deciding which AI tools are worth paying for can feel overwhelming in a crowded market. The most important starting point isn’t the technology itself but the problem you’re trying to solve. AI delivers the greatest value when applied to clear business challenges, whether that’s reducing time spent on repetitive manual tasks, improving data processing speed or enabling teams to make faster, more informed decisions.
Understanding the broader AI landscape helps narrow the field. Many organisations are drawn to “one-size-fits-all” tools, but flexibility and scalability matter far more in practice. Businesses should look for solutions that can be deployed easily, adapt as needs evolve and support workloads of different sizes, particularly as AI use grows from experimentation to everyday operations. This is where infrastructure designed for Hybrid AI environments becomes critical, Lenovo’s Hybrid AI Advantage portfolio is built to support real-world AI use cases across all industries, allowing businesses to scale securely and efficiently.
Flexibility is critical as AI evolves rapidly and today’s tools will continue to change. Businesses that succeed are those that remain open, build strong partnerships and choose AI solutions that can grow with them rather than locking into rigid systems that limit future innovation.”
Elise Balsillie, Head of Thryv Australia and New Zealand
“If you are deciding whether to pay for an AI tool or stay manual, make the call based on where time loss turns into revenue loss.
Start by mapping your week and circle the moments that either win or lose the customer: speed to first response, booking confirmation, no-show prevention, quote turnaround, invoice follow-up and review replies. If a task is frequent, time-sensitive and repeatable, paid AI tends to pay back quickly because it protects conversion and momentum. If it is rare, high-risk or emotionally charged (complex complaints, pricing strategy, sensitive people issues) I recommend it to be human-led.
Then apply the ‘connected workflow’ test. A standalone AI tool that creates more copy-paste can add friction. Platforms such as Thryv are built to reduce that double handling by bringing CRM, scheduling, estimates and invoices, payments and reputation management into one place.
The most valuable AI is the kind that helps you act, not just write. Thryv AI Lead Insights analyses calls, chats and form submissions then delivers summaries, suggested next steps, smart tags and a lead score so you can prioritise follow-up with confidence. For reputation, AI Review Response generates response options when replying to customer feedback, saving time while keeping your voice consistent.
I recommend investing in AI when it helps close the loop, reduces time to booked and brings payments forward, while keeping your judgement at the centre of every customer decision.”
MJ Robotham, Director, APAC at NinjaOne
“Most businesses don’t need more software tools; they need less congestion in their IT setup. When organisations are deciding if an AI tool is worth implementing, they must first consider what specific problem this tool is solving in their day-to-day operations. If this is unclear, then it likely won’t be a worthwhile investment.
Often, the biggest challenge with managing technology stacks is the amount of manual effort required, especially as they grow in complexity. Therefore, AI tools, which automate a large amount of manual work, should be measured against the outcomes you want to improve. For example, how quickly can the AI tool identify outdated or high-risk endpoints, and how many hours is this saving for the IT team? Running a short trial of the tool in the business’s real environment will provide tangible results and should present a clear comparison of before-and-after performance.
Organisations should avoid getting caught up in the hype around AI tools, and instead root their decision-making in addressing core operational challenges and establishing clearly defined outcomes they wish to achieve.”
Anthony Daniel, Managing Director, ANZ and the Pacific Islands, WatchGuard Technologies
“When deciding whether an AI tool is worth paying for, the real question isn’t whether it’s innovative. It’s what risk, cost or inefficiency it actually removes from the business.
Many SMBs still rely on manual monitoring and investigation processes. That approach may have worked when threats were slower and more predictable. Today’s threat landscape moves too quickly, attackers use automation, evasive techniques and increasingly sophisticated malware. The volume and speed of attacks mean manual processes alone can’t keep pace.
AI becomes valuable when it strengthens a zero trust approach, where every user and device must be continuously verified. For SMBs, that means gaining real-time visibility and responding quickly without relying solely on manual checks.
Solutions such as endpoint detection and response (EDR) and network detection and response (NDR), use AI to monitor activity across devices and networks, identify unusual behaviour and prioritise genuine threats. By reducing investigation time and enabling faster containment, they help businesses improve resilience without expanding internal security teams.
If an AI solution measurably strengthens detection, supports continuous verification and reduces breach risk, it justifies the investment. The tools worth paying for are those that make your business safer, not just more efficient.”
Dr Michael Bewley, VP, AI & Computer Vision, Nearmap
“If organisations are relying on site visits alone to understand property risk, they are working with an incomplete picture.
For organisations managing distributed physical assets – from architectural firms to insurers – risk management is a challenging problem. The physical environment is constantly changing, but site visits only provide point-in-time snapshots as recalled by a particular inspector, making emerging risks harder to detect before they escalate, and consistency more difficult to achieve.
This is where AI shifts the equation, but only if it is run as a rigorously controlled, consistent and reliable program over time – just asking a GenAI bot a question about an image doesn’t get you there. When applied to high-resolution aerial imagery, this kind of AI program can automatically identify patterns, deterioration, and risk exposure as it evolves across entire portfolios, continents and beyond – far beyond what manual review can realistically achieve. Rather than relying on reactive inspections, organisations gain continuous, data-driven oversight of the assets and environments they’re responsible for.
The human work complements this well – digging into the cause of an observed change, deciding how to respond (at a property or portfolio level), or taking action to remediate a new risk.”
Des Viranna, Global Head of Advisory and AI, Altis Consulting
“AI is advancing rapidly, and disciplined investment and governance must keep pace.
The smartest organisations don’t start by buying an AI tool – they start by defining the business problem and setting clear guardrails for decision-making.
A practical way to approach AI investment is to create a clear decision pathway. First, identify a genuine operational pain point or growth opportunity. Quantify the cost of the current manual process – in time, risk or revenue. Then assess whether a specific AI tool could materially improve speed, accuracy or scale, while meeting governance requirements around data, compliance and accountability.
If the potential upside is meaningful, run a small, low-risk pilot with defined success metrics before committing to long-term licences or broad rollout.
Only tools that demonstrate meaningful impact should be scaled. Those that don’t should be discontinued.
This approach prevents fragmented AI adoption, protects capital, and ensures AI investment is commercially grounded – not hype driven.”
Ashish Shetty, Founder & Director, DigitalScouts
“The biggest mistake business owners make with AI tools is buying based on hype instead of business impact. The real question is not which AI tool is popular, but which one directly improves revenue, margin, or efficiency in your specific workflow.
Start by identifying repetitive tasks that consume team time. If an AI tool can save more hours per month than it costs, it is worth testing. For example, AI that improves lead qualification, speeds up content production, enhances reporting clarity, or reduces admin overhead often delivers measurable return quickly.
Avoid stacking multiple tools that overlap. Many platforms already include AI features you are not fully using. Audit your current stack before adding new subscriptions.
Finally, run small pilot experiments. Measure output quality, time saved, and downstream revenue impact over thirty days before committing long term.
AI tools should either increase revenue, reduce cost, or improve decision making. If they do not clearly do one of those three, stay manual.”
Morgan Wilson, Founder & Director, creditte accountants & advisors
“AI tools are everywhere right now. The real question isn’t “Is this clever?” It’s “Does this actually make my business better?”
We see this all the time. Business owners sign up to five tools, use one properly, and wonder why nothing changed. The goal isn’t more tech. It’s better decisions and more time.
Start with three questions.
First, does this remove a real bottleneck? If it saves you two hours a week on quoting, reporting or admin, that’s capacity you can redirect into revenue.
Second, does it improve quality or reduce risk? If it cuts errors or tightens compliance, that’s leverage.
Third, will the team actually use it? A tool no one adopts is just another subscription.
Manual isn’t bad. But if you’re manually doing something repetitive, high-volume or data-heavy, it’s probably costing you more than the software.
Most businesses don’t need more AI. They need AI that creates clarity, speed and better decisions. That’s when it’s worth paying for.”
Maria Kathopoulis, CEO & Chief Marketing Officer at UNTMD Media
“AI is only valuable when it removes bottlenecks, not when it creates dashboards.
AI delivers ROI fastest when it automates coordination, reporting, and first drafts. Tools that save time, improve consistency, or trigger action automatically are worth paying for.
If a tool requires onboarding, management, or policing, it’s a liability.
A simple filter: does this reduce cycle time or decision fatigue? If not, skip it.
AI should shorten weeks into days. Anything else is theatre.”
Fabrizia Roberto, Fractional CMO
“I keep seeing two extremes. Either business owners sign up to every new AI platform because they’re afraid of missing out or refuse to pay for any because “I can do it manually”. Neither approach is strategic.
The real question is the same one we’ve always asked about any investment in software, systems or people: What does this mean for my business? AI doesn’t require a new decision- making framework. It requires disciplined application of the old one.
Every AI tool should do at least one of two things: make an existing task faster, cheaper or better, and unlock an opportunity that wasn’t previously realistic. If it does neither, it’s not an investment.
What outcome will this improve? Will it increase revenue, reduce cost or elevate quality? Does it free up leadership time? If you can’t answer these questions, you’re not ready to buy.
Secondly, look at the alternative. “If I don’t use this, what happens?” Usually the answer is “I do it myself, manually” or “I outsource it.” If a tool meaningfully reduces that load, the math is straightforward. But it’s not just about cost, it’s about focus.
If you bring work in-house using AI, you’re taking it on. You still need judgement, direction and quality control. If you keep working with contractors, you’re paying for their thinking, taste and accountability, not just execution. AI reduces production effort. It doesn’t remove the need for orchestration.
The third factor is setup and learning time. Every tool comes with integration effort, a learning curve and ongoing management. So, before committing, ask yourself: What specific outcome will this improve? What is the current cost of doing this manually? What is the current outsourcing cost? How long will setup and onboarding realistically take? Will this elevate quality or just increase volume? Is this aligned with where I want to spend my time?
If the numbers and the strategic fit make sense, test deliberately. Not because someone on LinkedIn said you should. But because it strengthens your business model.”
Renée Chaplin, VP – Asia Pacific, Constant Contact
“As AI becomes more embedded in how businesses operate, spending will naturally increase – but small business owners should be intentional about where that money goes. Not every AI tool is worth the investment, and the key is knowing where it will genuinely move the needle.
Start with the tasks that are repeatable, time-consuming, and directly tied to revenue. Marketing is a perfect example. Writing emails, creating social posts, optimising campaigns, segmenting audiences, following up with leads – these are critical activities, but they’re also the first to slip when you’re busy running the business. For time-strapped SMB owners, AI-powered marketing tools are a no-brainer. With a few inputs, the heavy lifting is done, and the technology learns from each campaign what’s working and what isn’t, then adapts accordingly.
Next, consider whether a tool reduces risk or error. Manually managing contact lists, personalisation, or compliance can lead to costly mistakes – often far more expensive than a monthly subscription. The right AI automates best practices so you’re not reinventing the wheel every week.
Finally, avoid AI for AI’s sake. If a tool doesn’t have clear potential to help grow revenue or reduce costs, it’s probably not the right fit. The best AI investments work quietly in the background, handling the operational load so owners can focus on strategy, customers, and doing what they do best – running their business.”
David Fischl, Legal Digital Transformation Lead Partner and Corporate and Commercial Team Lead Partner, Hicksons | Hunt & Hunt | Holman Webb
“The best AI tools to invest in are the ones that deliver genuine value and practical use to the business. At Hicksons, this is the principle we apply. When considering AI tools, we do not start with “What can this tool do?”, We start with “What value will this tool bring to our people and clients?”
If a tool does not address a clear need, such as removing repetitive work, simplifying complex tasks or improving decision making, it is likely to go unused. It can even add complexity to existing processes, leading to a negative return on investment.
It is also essential to assess whether an AI tool aligns with organisational values and long term strategy. Vendors work like partners, so how they handle ethics, transparency and data should line up with your standards
Compatibility and privacy are equally important. AI should integrate with existing systems to avoid extra costs, duplication or manual workarounds. Organisations need confidence that internal and client data will be handled securely, with clear controls around access and storage.
By focusing on value, alignment with values and strategy, integration and data protection, businesses can invest in AI that becomes a genuine asset rather than a distraction.”
Giovanni Forero, Senior Intelligent Information Management consultant, Konica Minolta Australia
“AI is the business tool of the future; however, it’s not a shortcut. AI systems can only perform well when they are fed reliable, well-structured, and accessible information. Without that foundation, results are inconsistent and the business risks increase. Further to this, there can also be issues with AI’s classification and governance.
Where AI can struggle with consistency, explainability and strict rule enforcement, traditional automation continues to play a critical role. Tools such as workflows, eForms, and robotic process automation excel when rules are fixed and outcomes are predictable. They are tried, tested and reliable, helping organisations to digitise information, standardise processes, and improve data quality with certainty and control, strengthening the foundations rather than depending on them.
However, once processes move beyond fixed rules and predictable outcomes, AI becomes worth the investment as these tools reach their limits. This typically happens when organisations need to process unstructured information, reduce manual decision-making at scale, or adapt processes as conditions change.
In practice, the strongest results come when AI is layered on top of proven automation, not deployed in isolation or as a replacement. The decision is less about replacing existing tools and more about having the right foundation first before using AI and traditional automation to complement each other for better business outcomes.”
Tim Mole, Head of Data & AI, JAVLN
“AI tools can start to feel like streaming services: another month, another subscription, another promise that this one will change your life. The truth is, businesses don’t need more AI unless it delivers a benefit big enough to justify the cost — and the cost isn’t just money, it’s human bandwidth and job satisfaction.
Start with the unsexy bit and do the maths. What’s the real cost of doing manual work? Most organisations never measure the “manual tax”, your most expensive “free” resource. Also factor in human-in-the-loop latency. If a task is repetitive, data-heavy, or requires quick responsiveness, manual effort becomes a bottleneck (and bottlenecks don’t scale).
Then consider the softer costs. Overly manual workloads quietly drain job satisfaction, and human inconsistency breeds rework. Leverage your people for high value-high EQ work and stop using them as expensive copy-paste machines. Offload the admin and keep the high-stakes, high-empathy and high-nuance work human.
If an AI tool reliably saves 30–60 minutes per person per week, and shortens turnaround, improves consistency, and reduces rework, it’s worth paying for. If it doesn’t, stay manual, and spare everyone another tool to learn.”
Dr Ian Gregory, Chief Technology Officer, Advancetrack
“As a CTO, I’m constantly approached by sales reps promoting AI technologies. How do I decide which to buy?
Keeping up with AI could be a full-time job, so I start with process: what am I trying to achieve, and what frustrates me day to day? I use a free consumer AI, currently Claude, to explore how AI might help, dig into what’s possible, ask for a shortlist of vendors, and review tools already emerging within our existing application stack.
I’ll then do some research – reviewing websites, watching help videos and sometimes speaking to a sales rep. One frustration was vendor due diligence for our ISO270001, so I built a Claude-based workflow to help review privacy and security documentation. Never put sensitive data into an AI tool you haven’t fully reviewed.
Finally, I run a trial. If it does what I need and saves time, I buy it – as they say, if the product is free, you are the product.
Right now, we use Claude Teams as a general AI tool and Fathom AI for meeting notes. I’m also exploring WisprFlow.”
Greg Wilkes, CEO of Develop Coaching
“Deciding which AI tools are worth paying for comes down to one question: does it save or make you more money than it costs?
Start with time. If an AI tool saves you five hours a week, and your time is worth £100 an hour, that’s £500 of value. If the software costs £49 a month, it’s a no-brainer. But be honest about your hourly value. If you’re still doing £25 tasks, fix that first.
Next, look at impact. Tools that directly affect revenue or margin usually justify payment. For example, AI that speeds up content creation, improves marketing response rates or automates quoting can increase leads or reduce admin. That’s commercial leverage. An AI image generator for “nice to have” social posts? Probably not essential.
Third, test manually before you automate. If a process is broken, adding AI just scales the mess. Get the workflow clear, then use AI to enhance it.
Finally, calculate payback. Will this tool increase profit, reduce headcount pressure or free you to focus on higher-value work within 30–60 days? If not, stay manual for now.
AI is a tool, not a strategy. Pay for outcomes, not excitement.”
Lee Robson, Founder & Director, iStories
“The question isn’t whether AI can do something – it’s whether it saves you more money than it costs.
tart with the maths: if a task takes you 3 hours weekly and you value your time at $100/hour, that’s $1,200 monthly. An AI tool costing $50/month that handles 80% of that work pays for itself immediately.
But here’s what matters more than the numbers: what work actually requires your unique expertise?
Social media scheduling? That’s process work – perfect for AI. Your brand voice and strategic positioning? That needs human judgement, but AI can execute it once you’ve defined it.
The sweet spot is AI that amplifies your expertise rather than replacing it. Tools that take your strategy and scale the execution. Platforms that deliver agency-quality work at a fraction of the cost, guided by frameworks built on real communications experience.
The manual approach works fine until it limits your growth. When you’re choosing between posting consistently or doing client work, that’s when staying manual starts costing you opportunities, not saving you money.
The right AI investment shouldn’t feel like a gamble – it should feel like hiring help you’ve needed for months.”
Justin Lester, Director, Market Enablement & Activation, Lexin Solutions
“When used properly, AI is an incredible tool, but paying for subscriptions adds up quickly. To decide what’s worth the investment versus staying manual, you should apply three strict criteria:
- First, does it buy back significant time? Look for tools that automate routine clerical work – like building tables or segmenting data – which allows you to focus on high-value core tasks instead.
- Second, does it bridge a skill gap? If a tool allows you to do something you simply cannot do yourself, it’s worth paying for. For instance, AI-driven video editors like CapCut or DaVinci are game changers for generating professional presentation visuals without a design degree.
- Third, does it filter noise from trusted sources? This is critical in heavy industry. At Lexin Solutions, we invest in AI that can analyse complex datasets – such as master data creation for large ERP systems – helping users find a clear signal to make better decisions.
Ultimately, if a tool returns hours to your week and allows you to verify results quickly and confidently, it earns its place in the budget. If it requires more management than the manual task itself, cut it loose.”
Adrian Randall, Founder and Director, Arcadian Digital
“Calculating ROI on AI tools involves more than just comparing a subscription fee to team salary hours. While cost-saving is the baseline, the real value lies in capability uplift. This is the ability to produce higher-quality work at a scale or speed that is physically impossible for a manual team.
Sometimes, manual work is inferior. If an AI tool can analyse 2,000 rows of customer data to find a pattern your team would miss, or generate 100 personalised ad variations in the time it takes a designer to make one, you are gaining a competitive edge.
Pay for tools that provide predictive insights, hyper-personalisation and accuracy at scale. This will help you to identify trends before they hit your bottom line, deliver a level of customer experience that manual workflows can’t touch, and remove the human error variable from high-volume data tasks.
Is your tech stack working for you, or are you drowning in underutilised subscriptions? A tool is only worth the investment if it eliminates the friction of tools that don’t `talk to` each other. Standalone AI that produces great work but sits in a silo is a productivity trap. New tools should plug directly into your existing CRM or tech stack. If the tool allows your current team to manage larger-scale projects without adding headcount, it’s a strategic win.
But, it’s important to avoid `shiny object` syndrome. High-quality AI output is worthless if it doesn’t drive measurable outcomes, like faster speed to market or reduced overhead. If adopting a tool creates a new training bottleneck for your team without a guaranteed lift in performance, the investment isn’t justified.
In a tight market, being first matters. If a paid AI tool shrinks your product-to-market timeline from months to weeks, the subscription cost is irrelevant compared to the front-run revenue.
Arcadian Digital can conduct a hands-on audit of your current systems to identify exactly where you can reduce costs and improve efficiency.”
Joe Romeo, Founder and Principal Consultant, Aperitif Agency
“I usually decide whether an AI tool is worth paying for by comparing the cost of the tool to my hourly rate. For example, if I value my time at $100 per hour and an AI tool saves me five hours per week, that’s $500 worth of time I’m saving. If the tool only costs $50 a month, it’s a no-brainer.
The real question isn’t, ‘Can I do this manually?’ It’s, ‘Should I be the one doing it?’
The same logic applies to data analysis. If an AI tool can review multiple 50-page reports, spot patterns faster than I can, and summarise key insights accurately, that enables me to spend more time decision-making, instead of sifting through data for insights.
As a founder, my highest value work is strategy, decisions, partnerships and growth. Anything repetitive, operational, or process-driven is a candidate for automation.
Ultimately, I pay for AI tools that buy back my time and allow me to elevate my focus.”
Nofil Khan, Head of AI at Avicenna
“Evaluate your processes. Find the processes that keep your business running; the ones that actually move the needle and generate revenue. Understand how AI can make these processes more efficient and effective. If it can, it’s worth either paying for a tool to help automate or enhance these processes, or to build out your own tools to do this. If you build it yourself, you own the tool, avoid subscription fees, and can customise the tool to your liking. This is the Time x Money approach to AI adoption. The “where” is more important than the “how” and the “what”. AI tools are a dime a dozen now, many use the same tools and techniques under the hood – simple prompting. For a business, the most important question to answer is where to implement AI. If you can answer this, you won’t even need to ask if an AI tool is worth paying for.”
Kelly Eldridge, Chief of Staff at Quickli
“In 2026, there are lots of brilliant companies that have revolutionised legacy systems. This is good, not only because of the superior experience and/or product for the end user but because, when tech actually works, it lifts entire industries, letting people do their jobs better and creating more opportunities.
There is also no shortage of tools that promise to ease your burden. These two things are not the same.
While some brilliant products come from people new to industries (usually with careful consultation), I’m a firm believer that some of the best solutions come from founders who actually worked in the space they’re fixing. You can feel domain expertise in a product. It solves the right problems, not just obvious ones.
So when you’re evaluating AI tools, start with this: does this solve a problem I actually have?
I see plenty of businesses adopting AI because it feels like they should, not because they’ve identified a genuine bottleneck. That’s expensive and performative.
Time your manual process first. Understand where the friction lives. If you’re spending 15 minutes per week on something, automation isn’t your priority. If you’re spending 15 hours? Now we’re talking.
The best AI tools are faster than manual, more accurate than manual, and slot into your existing workflow without creating chaos. If a tool fails any of those tests, it’s definitely not ready.
Don’t let initial learning curves scare you off. Change is never seamless and some friction is normal. But be honest about the math. If a tool saves you two hours weekly but needs three hours of ongoing maintenance, that’s not a win.
Of course, nothing beats a well-oiled product backed by a team with deep domain expertise that starts saving you hours from day one. But I might be biased ;-).”
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