May 20, 2025
With AI dominating headlines and boardroom agendas, it’s easy to get caught up in buzzwords and vendor promises. But delivering a real return on investment from AI takes more than enthusiasm and ambition. It requires focus, discipline and a lot of critical thinking.
I had the pleasure of moderating a thought-provoking panel discussion at our latest Expert Talk event in Brisbane. Titled “More than chatbots: How AI accelerates time to value and delivers more with less” the event invited industry experts to explore how AI is transforming business outcomes and share their real-world experiences.
It might sound obvious, but in the rush to implement AI quickly, many businesses are jumping in feet first without considering their use cases – the how and why of AI adoption. Simply implementing AI shouldn’t be the end goal for a business, it should be a tool that you can use to help you reach your goals and deliver outcomes.
Daniel Pludek, Group Chief Information Officer, Kip McGrath Education Centres, said: “The biggest mistake I’ve seen is people want to implement AI but they don’t actually consider what problem they want it to solve. Don’t look at AI as anything other than one of many tools you could use.”
Just like you wouldn’t teach a child to ride a bike by starting them on a racing bike, businesses need to start small with AI, focusing first on the problem and what they’re trying to achieve before embarking on a radical plan.
Hari Baran, Delivery Principal and Equal Experts Associate, said: “By starting small you actually gain two advantages – one of them is learning from your mistakes and the second one is finding out what is right for your organisation. Don’t do things just for the sake of doing things, try to solve real problems but also keep in mind how you measure success.”
With so much excitement around AI, many organisations have found it relatively easy to secure a budget for AI experiments. But pressure is growing to justify these investments and leaders are increasingly looking for concrete returns.
Nick Yates, Technology and Warranty Impact Manager at Hastings Deering, said: “From the business side you have to figure out a way to quantify the value that you’re delivering with AI and you have to be able to show that you’re going to help save money today and in the future.”
Daniel shared how Kip McGrath Education Centres, as an early adopter of AI is already seeing ROI from AI in reporting and curriculum development. For example, automated reporting notes using AI and natural language processing is saving staff 15 minutes per session, reducing costs from $16 per report to just $0.43 and freeing up time for more student engagement. Similarly, AI is accelerating and enhancing its curriculum creation. With effective guardrails and human quality control in place, it now takes just eight hours and $200 to generate a curriculum, enabling staff to be reallocated to teaching and providing individualised learning.
He added: “Everything can be allocated a dollar value – time savings, performance etc – but you need to make sure you’re using real numbers and you’re tracking it across the entire life cycle all the way through to benefits realisation.”
For some businesses, AI may offer an opportunity to modernise how they measure value – taking into account not just business outcomes but also the ways teams operate. Hari pointed out that the value of AI could also be seen in delivery, through the speed at which new features are delivered or the number of story points completed.
It was interesting to hear the panel discuss the “hidden costs” relating to AI, such as increasing model cost or being tied into vendor contracts, with Hari arguing that businesses need to change their mindset towards AI costs as the technology becomes increasingly important.
“You need to change how you are looking at costs across the software development lifecycle,” he said. “Just like you can’t call a server a hidden cost as it’s a main component of your software development life cycle, AI models are becoming main components as well and I think you need to really consider and quantify these costs.”
When AI first hit the news in a big way a few years ago, many headlines were dominated by fear with AI-related job losses and data bias frequently being discussed. Today, the conversation has matured, but some unease remains.
I’m a firm believer that AI is not taking people’s jobs away but it is changing the jobs that people have. That’s why keeping the human in the loop is critical. This means investing in AI literacy, helping teams adapt to new tools, and putting the right guardrails, governance, and regulatory practices in place to ensure AI is used responsibly.
Hari added that with increasing regulations coming into effect, such as the European Union’s AI Act, a lot of companies are reconsidering their approach to AI, in particular those with a self-iterating and self-learning system or those interacting directly with customers. “But businesses will probably want to invest in new capabilities as well, like AI security, AI usability and MLOps,” he said.
Daniel said: “AI is no different to any other tool you have in the organisation. Ensure you understand how AI works, and what the risks are and set it up correctly with guard rails, just as you would with your existing processes and controls.”
For organisations looking to expand AI use beyond technology teams, for example within finance or HR teams, a need to dispel fear by demonstrating value is key. Nick said: “Rather than focusing on the fact that it’s AI, you need to focus on their pain points or problems and create a solution for them. It’s only after you show them how it solves their problems that you talk about the fact it’s AI.”
AI undoubtedly has huge potential. But the organisations that will succeed are the ones treating it as a real business tool, not a magic bullet for everything. That means being clear about the problem you’re solving, understanding what success looks like, identifying true value (including all costs), and being strategic about where you start.
At Equal Experts, we’re embracing Responsible AI Delivery. That means helping our clients navigate this shift and take advantage of the opportunity – without falling into the traps of hype, endless proof-of-concepts, or major AI product and engineering failures. We avoid context-free claims and focus on using AI to deliver faster time to sustainable value, at lower cost.
Whether you’re exploring AI for the first time or rethinking your strategy to deliver greater business value, we can help you cut through the noise and focus on what really matters. Get in touch to learn more about what we’re seeing in the market and start a smarter AI conversation.
All business models have their pros and cons. But, when you consider the type of problems we help our clients to solve at Equal Experts, it’s worth thinking about the level of experience and the best consultancy approach to solve them.
If you’d like to find out more about working with us – get in touch. We’d love to hear from you.
