Generative AI.

The Future of Generative AI for Businesses: A Kiwi Perspective

Gen AI is a type of artificial intelligence that uses neural networks and deep learning algorithms to identify patterns within existing data as a basis for generating original content. By learning patterns from large volumes of data, gen AI algorithms synthesise knowledge to create original text, images, audio, video, and other forms of output.

Language models are powerful software systems designed to understand, generate, and manipulate human language. Some models handle images and other media along with text. These are often referred to as multimodal language models.

Embracing Generative AI in Mid-Sized Firms: Key Factors to Consider

We're on the cusp of something extraordinary in the world of business, and it's unfurling at breakneck speed. Generative AI is poised to be a game-changer in the way we run businesses, not just for big corporations, but critically, for small and medium-sized enterprises in New Zealand and beyond. This innovation wave could well be the next PC or iPhone moment that we'll reminisce about down the track.

Now, you might've heard all sorts of fun examples of what generative AI can do—from penning quirky puns to generating photos of a Kiwi bird piloting a drone. Cute, right? But if you're steering a business, especially an SME, the focus should be on pragmatic, value-driving applications.

When you're looking to leverage generative AI in your business, the first port of call should be identifying real-world problems that this tech can solve. Think about areas where you can automate repetitive tasks, maybe like generating monthly financial reports or churning through customer queries.

The magic also lies in making sense of unstructured data—like sifting through customer reviews scattered across multiple platforms and drawing actionable insights. If you're running a boutique retail shop or a local consultancy, this can provide unparalleled insights into your customers' minds. And when it comes to success metrics, you could tie them to financial gains, enhanced customer satisfaction, or even sustainability milestones.

Integration is key. If you want your team to get the most out of generative AI, these tools need to fit seamlessly into the day-to-day workflows. We're not talking about standalone, highfalutin gadgets here. The aim is to have generative AI augment what your workforce is already doing—making everyone's life a bit easier, efficient, and more productive.

Ease of adoption is what will likely make generative AI an instant hit. It's so intuitive and user-friendly that transitioning should be a walk in the park. So, we're not just talking about a transformative tech that will take years to implement. We're probably looking at something that could become second nature to your team in mere months.

The promise of generative AI isn't a distant dream. Its impact will soon be felt by SMEs across New Zealand, changing the way we do business for the better and faster than ever before. And you'll want to be part of that journey—trust me, it's going to be a significant chapter in our tech history books.

What Sets Generative AI Apart for SMBs?

Generative AI is changing the game in how we interact with technology. At its core, this type of AI can create content on its own, thanks to machine learning algorithms trained on heaps of data. What this means for the user experience is groundbreaking—it's like having a meaningful conversation with your computer. While the tech employs a range of sophisticated techniques, like transformer models and GANs, it's becoming increasingly accurate, even if there are still some kinks to iron out.

You're probably familiar with ChatGPT, but the landscape is broadening with platforms like Stability.ai, Google’s Bard, and Microsoft’s AI-powered Bing. The key difference between consumer-focused generative AI and what businesses need is all about the data it's trained on. Most consumer models generate responses based on publicly available info, but that's not going to cut it for a business.

Take a local accounting firm in New Zealand, for example. While a general-purpose generative AI tool might offer generic financial advice, a system designed specifically for that firm could delve into proprietary data to generate detailed insights on client behaviour, transaction trends, or risk assessments. The same goes for other industries, whether it's a boutique healthcare practice or a Kiwi craft brewery.

What makes generative AI really sing for businesses is its ability to incorporate domain-specific, enterprise data alongside public data. Imagine you're running a tourism company in Queenstown. A generative AI model could factor in real-time weather data, regional tourist trends, and your own booking information to predict the best times for running your adventure tours.

The power of generative AI isn't just confined to a few experts in the tech department. This is about democratizing access to advanced, predictive insights across your team. Unlike consumer-grade offerings that base their output on past data from the web, enterprise-focused generative AI could forecast future trends unique to your business. It could tell you when your e-commerce platform is likely to see the most traffic or which services are due for an upgrade based on customer feedback loops.

So, in essence, generative AI is not just another tech fad. It’s a transformative tool that promises to change how we do business by offering bespoke, predictive insights that will give you that competitive edge.

Why Generative AI is a Game-Changer for business.

Data Quality and Accessibility
Generative AI thrives on abundant, quality data. For mid-sized firms, having access to adequate and reliable data is crucial for the technology's success. If data is scarce or of low quality, the AI system's accuracy could suffer. Businesses must take stock of their data landscape before diving into generative AI.

Security Concerns
While generative AI can be a treasure trove of insights, it can also pose a security risk if not managed well. Unauthorized access to sensitive business data can result in breaches and legal complications. Mid-sized companies should ensure robust data governance and access control measures.

IP Considerations
Using publicly trained generative AI can inadvertently put businesses at risk of infringing intellectual property rights. Businesses should be wary of this, especially if the AI is generating customer-facing content. Using an enterprise-specific training set can sidestep this issue.

Bias and Accuracy
AI models can propagate existing biases in training data, leading to skewed or unfair outcomes. Inaccuracy due to 'stale' or irrelevant data is another issue. This could have severe implications for businesses, especially those in sectors like healthcare or financial services.

Custom Domain Models
Companies should consider investing in custom models to harness the full potential of generative AI. These models would be trained on the company's proprietary data, mitigating security risks and IP issues. Additionally, a well-implemented feedback loop can continually improve the model's accuracy and utility.

By carefully considering these aspects, mid-sized businesses can navigate the complexities and fully unlock the transformative potential of generative AI.