As we approach the end of 2024, I find myself reflecting on a year that has been both challenging and incredibly rewarding. In January, I made the bold decision to fully commit to Intelligence Assist, driven by a vision to help small businesses navigate the complex world of AI. Looking back, it’s remarkable to see how far we’ve come, and how the AI landscape has evolved from buzzing hype to practical reality.
The journey began with a simple observation: small businesses were struggling to make sense of AI, but not in the way many might expect. Through countless conversations at business networking events, a clear pattern emerged – most small business owners didn’t think AI was even applicable to them. They saw it as the domain of large enterprises with substantial budgets and dedicated IT teams. This misconception was perhaps the biggest barrier we needed to overcome.
These early conversations were invaluable, fundamentally shaping our approach and reinforcing our mission. We discovered that the key to successful AI adoption wasn’t about massive technological overhauls or significant upfront investments. Instead, it was about finding small, incremental productivity gains that could create the capacity for innovation.
This realization led to one of our core principles: when time, money, and resources are limited, you need to find capacity to innovate before you can actually innovate. And when you do innovate, it has to truly make things easier, cheaper, or faster – not just add another layer of complexity to existing processes.
There were moments of doubt, I’ll admit. Times when I questioned whether the AI hype was justified, whether we were truly on the right path. But these doubts only strengthened our commitment to a practical, results-driven approach. We made the conscious decision to remain tool-agnostic and focus on no-code AI solutions, ensuring that our recommendations would truly serve our clients’ needs rather than forcing them into complex systems they didn’t require.
This past year has taught us the importance of careful evaluation in the AI space. While there are incredible tools being developed, there’s also a fair amount of “AI washing” – products that claim AI capabilities but fail to deliver meaningful value. We’ve dedicated significant time to experimenting with various tools, separating the truly useful from the merely trendy, ensuring that our recommendations don’t end up costing more than they deliver. This commitment to practical, verified solutions has become a cornerstone of our approach, helping small businesses navigate not just the technology, but the marketing hype surrounding it.
October marked a pivotal moment for Intelligence Assist when we officially launched our service offering. The response has exceeded our expectations, with performance surpassing all our initial goals. While 2024 has brought its share of personal challenges and moments of sadness, we’re ending the year on an undeniable upward trajectory.
The recent announcements from major Australian universities have been particularly validating. The University of Sydney’s decision to allow students to use Generative AI for assessments, and UNSW’s partnership with OpenAI for ChatGPT Edu, are clear indicators that AI has moved beyond the hype cycle and into what Gartner calls the “Plateau of Productivity.”
As we step into 2025, the future looks incredibly bright for AI adoption and implementation. Unlike other technological trends that have come and gone – blockchain, NFTs, 3D television, or wearables like Google Glass – AI has proven its staying power by delivering tangible value across industries and applications.
None of this journey would have been possible without the incredible individuals who have contributed to Intelligence Assist along the way. To Sky Reidy, Libby Porter, Harriet Brown, Mo Ahmed, Aaron Ding, and Alan de Zwaans – thank you for being part of our story. Your contributions, however brief or extended, have helped shape who we are today.
And to our current team – Kate Tabalba, Sam van Leeuwen, Issey Stevens, and Taylor Shutes – I’m filled with excitement about what we’ll achieve together in 2025. Your dedication, creativity, and shared vision for helping small businesses thrive in the AI era make me incredibly proud to work alongside you.
AI in Education: A Student's Perspective
By Taylor Shutes, Engineering Student at the University of Sydney
As a student at the University of Sydney, I’m witnessing firsthand how Australia’s leading academic institution is embracing the AI revolution. When ChatGPT first emerged, many feared it would undermine the foundations of university education by giving students instant access to complex solutions and pre-written essays. However, those of us who explored its potential quickly realised that AI isn’t replacing education—it’s elevating it. Just as we learned to harness search engines effectively for research, mastering AI requires understanding its strengths and limitations. The key lies not in requesting complete solutions, but in leveraging AI for targeted research, refining communication, debugging code, and enhancing our learning process. Much like how calculators transformed mathematics education, AI is a powerful tool that, while capable of completing basic tasks, ultimately enables us to tackle more sophisticated concepts efficiently and dive deeper into our studies.
During my study of engineering, I’ve observed USYD’s evolving approach to AI integration. Rather than resisting this technological shift, the university has adapted by implementing AI use declarations in assignments and placing greater emphasis on practical application of knowledge. This adaptation acknowledges that while AI can make theoretical knowledge more accessible, the true value of education lies in applying these concepts. This shift has addressed one of my main concerns about university education—the gap between theory and real-world application. With AI as a learning companion, I’ve been able to develop more sophisticated coding solutions and envision detailed mechatronic systems that extend well beyond basic classroom concepts.
USYD’s proactive stance recognizes a crucial reality: in the professional world, AI tools will be ubiquitous, and students who haven’t learned to harness them effectively will be at a significant disadvantage. By leading this educational revolution, USYD isn’t just adapting to change—it’s preparing students for a future where AI literacy is as fundamental as digital literacy is today. This forward-thinking approach to an inevitable technological shift ensures that graduates enter the workforce not just familiar with AI, but skilled in leveraging it responsibly and effectively.
AI vs Wearables: A Tale of Two Technologies
Understanding the Gartner Hype Cycle
The Gartner Hype Cycle is a powerful framework for understanding how new technologies evolve from their initial emergence to mainstream adoption. This model illustrates five distinct phases that most technologies experience:
- Technology Trigger: A breakthrough spawns initial interest and media attention, though practical applications may not yet exist.
- Peak of Inflated Expectations: Early publicity generates unrealistic enthusiasm and inflated expectations.
- Trough of Disillusionment: Interest wanes as implementations fail to deliver on the initial hype.
- Slope of Enlightenment: Real benefits begin to crystallise and become more widely understood.
- Plateau of Productivity: Mainstream adoption takes off as the technology’s benefits are clearly demonstrated and accepted.
A Tale of Two Technologies: Head-Mounted Wearables vs. AI
The contrasting journeys of head-mounted wearables and AI through the Hype Cycle offer fascinating insights into what determines a technology’s success. While both started with enormous promise, their paths have diverged significantly.
The Wearables That Weren’t
Head-mounted wearables, exemplified by devices like Google Glass and VR headsets, faced several critical challenges:
- Physical Discomfort: Studies show 25-40% of users experience VR sickness, with symptoms ranging from nausea to eyestrain.
- Privacy Concerns: The potential for surreptitious recording led to significant social resistance and regulatory challenges.
- Technical Limitations: Issues with battery life, bulky design, and high costs have limited practical applications.
- Social Acceptance: The conspicuous nature of the devices, combined with privacy concerns, has hindered their integration into daily life.
These factors have kept head-mounted wearables largely confined to niche applications, unable to break through to mainstream adoption.
AI’s Journey to the Plateau
In contrast, AI, particularly platforms like ChatGPT, has demonstrated remarkable success:
- Unprecedented Adoption: ChatGPT reached 1 million users in just five days, compared to Instagram’s 2.5 months to reach the same milestone.
- Accessibility: No specialised hardware required, just a web browser and internet connection.
- Immediate Utility: Offers clear value across various applications, from writing assistance to coding help.
- Continuous Improvement: Regular updates and refinements based on user feedback maintain engagement and satisfaction.
What Made the Difference?
The divergent paths of these technologies highlight several key factors that influence successful adoption:
- Barrier to Entry: AI platforms require minimal investment and no special equipment, while wearables demand significant financial commitment and lifestyle changes.
- Immediate Value: AI delivers clear benefits from the first use, whereas wearables often struggle to justify their cost and complexity.
- Social Integration: AI integrates seamlessly into existing workflows and social norms, while wearables face significant social and cultural barriers.
- Improvement Cycle: AI benefits from rapid iteration and improvement based on usage data, while hardware-based technologies face longer development cycles.
Looking Ahead
As we move into 2025, AI has clearly reached the Plateau of Productivity, with widespread adoption across industries and clear demonstrations of value. The technology has moved beyond hype to become a foundational tool transforming how we work, learn, and create.
Meanwhile, head-mounted wearables continue to evolve, with companies still searching for the right combination of features, comfort, and social acceptability. Their journey serves as a reminder that technological success depends not just on capability, but on addressing real human needs and social dynamics.
The contrast between these technologies underscores a crucial lesson: true technological revolution isn’t just about innovation—it’s about creating solutions that seamlessly integrate into and enhance our daily lives.
