In the past six months, every other business owner I’ve spoken to has mentioned AI in some capacity. Whether they're curious about how to integrate it, figuring out where it fits into their operations, or sharing what it’s already accomplishing for them. The AI age is no longer a distant concept; it’s here, and it’s moving faster than anything I’ve seen in my eight years in business.
When I started Moonward in 2017, I was an early adopter in the mobile app space. Back then, though, most business owners were hesitant to dive in fully. Mobile app development was slow, expensive, and the end results were often uncertain. Fast forward to 2024, and we’re in the midst of a technology revolution unlike anything I’ve experienced before. The excitement and genuine action around AI in these early stages is extraordinary. The hype around AI, reminds me of the crypto and blockchain hype in 2021, remember when everyone was talking about Bitcoin and NFTs? However, after a lot of buzz and speculation, I don't recall many businesses truly emerging themselves into those technologies. Some may have accepted Bitcoin as payment, but beyond that, the adoption didn’t go far. So the difference, is 2024, is that almost every business owner I speak with is currently researching and investing in AI. Why? The answer is simple: AI is fast to develop, it delivers almost instant results, and it’s relatively easy to work with. You don’t need to be a computer genius to use tools like ChatGPT, and you don’t have to wait months to see results from your efforts.
The reality is that the AI age is upon us. Businesses around the world are tapping into AI’s potential, and here at Moonward, we’re fully embracing it.
I recently checked the global AI Index, Australia is currently ranked 17th, not really punching above our weight. This ranking was lowered largely due to two areas where we’re lagging: commercialisation of our AI products and government strategy. Despite the wealth of talent and innovation in Australia, we’re missing the right conditions to scale our AI innovations globally. With the right support, we have the potential to punch far above our weight.
With all that said, Moonward is thrilled to be working with so many forward-thinking businesses. Having now developed a range of AI solutions and constantly investing in new ideas, we've identified 8 key areas where organisations are investing in AI. I’ve outlined this list below, complete with tangible examples to help you relate to each one. Please keep in mind, these aren’t your typical ChatGPT or email grammar fix strategies, I’m diving into the deeper, more impactful ways businesses are using AI today. I hope you find these insights valuable as you explore AI’s potential for your own business. And of course, should you need any help implementing AI for your own business, check out our AI Business Strategy Map here.
Google recently announced that AI is now responsible for writing 25% of all their code, a remarkable figure considering the vast scope of Google’s software suite, which includes over 20 enterprise-grade products. This milestone highlights how quickly task automation is becoming the new norm, not just at Google but industry-wide. At Moonward, we’ve also embraced this approach to streamline repetitive tasks in software development.Historically, our team would spend hours on manual code reviews, thoroughly checking for errors against our internal standards. Now, we’ve implemented an automated AI-driven review process that flags these issues in seconds before the code even reaches a peer for final review. While we still conduct manual reviews, our focus has shifted from catching simple errors to refining and elevating code logic, ensuring our team can dedicate their time to high-value work. This change has significantly reduced our review time and amplified the impact our team delivers for clients.
For businesses looking to adopt task automation, start by listing all the repetitive tasks you or your team handle daily, whether it’s answering calls, sending emails, or entering data. Once identified, consider which tasks might be streamlined with AI. Later in this article, I’ll cover more on implementing automation, but for now, focus on pinpointing areas where automation could boost efficiency and accuracy. Task automation offers immense potential, and with AI advancing rapidly, 2025 will likely bring even faster, more accurate solutions.
I recently spoke with a medical professional who’s pioneering the integration of AI into healthcare. Over the past 12 to 18 months, they’ve been capturing depersonalised patient data before and after specific medical procedures. After partnering with a research and AI institute, they’ve developed a model capable of predicting the success of certain procedures based on basic preoperative data. This model gives medical professionals realistic outcome predictions and flags potential issues before a procedure even takes place! Allowing them to proactively prepare and improve patient care. This is just one example of the many AI-driven innovations I've encountered recently, where businesses are converting client data into powerful analytical tools.
At Moonward, we’re similarly developing an AI model designed to pinpoint the data points that correlate with the highest success rates for software startups. By analysing anonymised client data, our goal is to help startups identify the factors that optimise success, from ideal capital allocation to marketing spend, target market size and tester numbers.AI is reshaping how businesses understand and anticipate customer needs, allowing them to predict behaviour and tailor products or services to specific segments. This level of insight lets companies address needs preemptively, building stronger client relationships and fostering loyalty. From analysing purchase trends to foreseeing customer churn, AI-powered customer analysis is transforming client engagement and setting new standards in customer understanding. So many business owners have been capturing valuable data for years and AI now provides the platform to convert this data into pinpoint analysis.
If you’re anything like me, you’re probably seeing AI-generated data summaries daily without even realising it. Just recently, I opened Strava to discover their new "Athlete Intelligence" feature, a small text box at the bottom of a completed workout that summarises your recent exercise. This feature draws on historical and recent workout data to provide instant insights into heart rate, distance, pace, endurance, and stamina, all condensed into a single sentence. It’s an impressive way for users to gain meaningful insights at a glance.
We’re seeing similar data summary features in tools like Notion, where meeting recorders and note-takers summarise large datasets into digestible paragraphs. Data summaries are a powerful method for businesses to convert complex information into immediate, actionable insights. Whether it’s analysing employee performance, breaking down sales metrics, CRM data, or meeting notes, data summaries cut through extensive information, helping teams move quickly from insight to action.
Data summaries are also becoming increasingly popular in report generation. Most industries are required to deliver key reports to stakeholders, employees, board members etc. AI Data summaries now enable you to quickly garner insights into your data, reducing report generation by a huge margin. As well as enabling you to report on data that was once considered too complex or too difficult to gain insights from. Businesses can now effortlessly share insights, KPIs, and other metrics, enabling transparent communication and better decision-making. Automated data reporting ensures that essential information is consistently available, fostering trust and clarity between clients and service providers.
Some of the earliest AI projects we worked on focused on eliminating knowledge bottlenecks within companies. Business owners quickly recognised that AI could be the perfect solution to replicate and enhance their own knowledge, improving the way information is shared across their teams. AI enables seamless knowledge transfer and employee training by creating intelligent assistants that pull data from various sources such as websites, handbooks, and internal documentation.
One client in the construction industry built a tool that allowed employees to ask specific product-related questions and receive instant, accurate answers. The AI pulled data from internal documentation, supplier handbooks, and Australian standards websites. By combining these three data sources, employees received reliable, company-approved information that also aligned with industry standards. This AI-driven approach not only increased productivity but also ensured consistent knowledge across teams, making it an invaluable tool for businesses looking to build a highly skilled, informed workforce.
Similar to the internal knowledge transfer tools, we’ve seen a significant increase in the adoption of fully customised AI-driven customer support tools. These systems are revolutionising the way businesses manage client interactions by automating responses and empowering customers to self-serve. This not only leads to faster resolution of customer issues but also reduces the manual workload involved in customer support.
While automated customer support isn’t new, AI has dramatically improved the quality of service. In the past, many automated systems were quite rigid, if customers didn’t follow the exact path expected, they’d be stuck in a loop or placed in a wait queue. Today, AI-driven customer support tools provide a more sophisticated, personalised experience, offering extensive information and tailored assistance.
At Moonward, we noticed that many of our clients were struggling with the process of setting up their Apple and Google Developer accounts. Despite creating detailed support documents, we found ourselves spending hours walking clients through the setup. To solve this, we leveraged both our internal documents and external data sources to build a fully automated AI assistant, named ‘Moonie,’ to guide clients through the account creation process. The introduction of Moonie has not only saved our team a significant amount of time but has also greatly enhanced customer satisfaction, providing a smoother and more efficient experience.
AI has transformed market research by automating data gathering and analysis, making it faster and more efficient. In the past, using search engines meant manually reading through multiple sources to extract actionable insights and statistics, a time-consuming process.We recently worked with a client who was facing exactly this challenge. They were cross-referencing an ASIC notices website daily to find specific data, which updated every few hours. However, the relevant data was often buried among unrelated information. Once they identified what they needed, they’d conduct a secondary search to validate the data on another site, an intricate process that consumed hours each week.
To solve this, we introduced an AI-powered web scraper, coupled with a data validation process. This system automated the tedious tasks they’d previously done manually, allowing them to simply open a dashboard and access the processed data. Not only did this save the client significant time, but it also delivered more accurate and reliable results.
This is just one example of how AI is revolutionising data research. With tools like ChatGPT, even everyday consumers now have access to powerful, instant data insights. Whether you’re gathering industry-specific data or researching market trends, AI is making it easier and faster to obtain accurate, relevant information without the manual legwork.
AI is making complex software development more accessible than ever, especially for businesses and startups that previously might have been priced out of such ventures. Not long ago, building intricate software solutions would have been an overwhelming financial and logistical challenge. Take, for instance, the development of an audio recognition app that Moonward’s team recently worked on. Unlike conventional software that recognises words, this product needed to identify specific sounds, a solution that was not readily available in the market.
Traditionally, developing a tool like this would require gathering an extensive, manually collected dataset of audio samples, a process that could take months to complete. Even after collecting the data, training a machine learning model to work with it would be both prohibitively expensive and resource-intensive, potentially costing hundreds of thousands, if not millions of dollars.
But AI has changed the game. Instead of spending months gathering audio samples, Moonward used AI to automatically generate sound variations from a small pool of existing data. What would have once taken us months to build, we were able to achieve in just a few days, enabling us to develop an incredibly accurate product without the data limitations that would have previously held us back. This approach not only saved us time but also drastically reduced the cost of development, opening up new possibilities for innovation that were previously out of reach.
This breakthrough isn’t just specific to audio recognition. Across a wide range of industries, AI is tackling complex software challenges that were once unimaginable. By generating synthetic data and accelerating the training of machine learning models, AI is enabling businesses to innovate faster, more efficiently, and at a scale that would have been impossible just a few years ago. Businesses that once had to rely on slow, expensive development cycles can now push forward at unprecedented speeds.
If you're in the process of building software, I’d strongly recommend asking your development team, "How can we incorporate AI to enhance our product and make our development process more efficient?" I’d be surprised if you don’t discover several ways to improve your current delivery, and even open doors to innovations you hadn’t yet considered.
At this point in time, most people are assuming that AI is limited to a single-point process. For example, summarising this data, providing action items from meeting notes, or finding bugs in code. However, when combined with advanced software, AI automation can become a multi-step process that enables businesses to build advanced AI pipelines.
This kind of AI-driven automation goes beyond simple task execution, it enhances operational efficiency by seamlessly managing complex processes, ensuring greater accuracy and significantly reducing the risk of errors. With AI handling the routine, data-heavy tasks, teams can shift their focus to higher-level decision-making, strategic planning, and problem-solving.
For example, just like software developers have an automated pipeline that prepares and tests code, AI can oversee the progression of multiple stages in any business process. The challenge for business owners, is identifying the processes that can be automated and then deconstructing them, so help boost efficiency.
By automating multi-step workflows, AI empowers businesses to scale their operations with more speed and confidence, all while maintaining a high level of accuracy and control. This leads to smoother, more efficient workflows and allows businesses to operate at a higher level of productivity, ultimately driving better results and fostering business success.
Throughout this article, I’ve shared a range of examples that highlight the diverse ways AI is transforming industries, some more complex than others. The key takeaway, however, is simple: AI is still in its early stages and constantly evolving. While this presents challenges, it also offers tremendous opportunities for businesses willing to adapt. The rapid pace of investment in AI technology globally signals that it will soon become a fundamental part of every business strategy.
We understand that adopting AI can seem daunting, and determining the best starting point can be overwhelming. But the time to act is now. As AI continues to grow in importance, businesses that fail to embrace it risk falling behind.
To help companies navigate this journey, Moonward is introducing our AI Business Strategy Map for 2025. This four-week process will guide you through building a tailored AI roadmap for the next 12 months, positioning your business as a leader in the AI space.
If you're ready to leverage AI to enhance your business or need assistance in bringing your ideas to life, click here to learn more about how we’re helping businesses harness the power of AI to stay ahead of the curve.
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