State of Gen-AI in NZ - Where are customers getting stuck?

Most are treading very carefully. The winners are striding ahead with purpose

I’ve talked to over 40 NZ companies about how they are working with Generative AI. These range across industries including Engineering, Recruitment, Finance, Primary Industries and Health. Companies in each stage of the journey shared surprising similarities, not in the way they were implementing AI, but their attitudes toward it. Most are stuck in strategy however the companies moving forward at pace are not necessarily the small agile companies. They are companies who have approached the technology with curiosity and the ability to experiment. No-one had a head start technically, culture is the key driver to success.

Stuck on Strategy

These companies often find themselves trapped in a cycle of risk, compliance, and fear, struggling to navigate the safe use of technology and occasionally even prohibiting GPT models. Many grapple with concerns about bias. It's not just the large corporations; smaller businesses also face hurdles, often due to apprehension about regulations or intricate policies.

Recommendations:

Take small steps - establish a controlled environment and experiment
Focus on internal tools
Follow large industry players on the risk/compliance journey

In the playground

Businesses are beginning to explore technology options. Teams are adopting and becoming familiar with off-the-shelf tools such as Co-Pilot and Grammarly. While custom internal tools are under development, they have not been fully implemented company-wide or for customers yet. Although some value is being obtained from these tools, it tends to be limited to specific areas, and tools that benefit the entire company or customers are not in widespread use yet.

Recommendations:

Establish metrics to measure successs of use cases
Ensure progress is company wide, deploy tools internally
High value use cases companywide cannot be ignored

The DO-ers

These companies have identified crucial use cases and are innovating to generate fresh value, enhance productivity, and empower their employees with tools to reshape their work. Their success was not solely dependent on experience or large teams of data scientists. Instead, the key was rapid experimentation throughout the organization, not just within technical teams, embracing failure as a learning opportunity, and concentrating on use cases that deliver value. These companies are transforming their operational practices and are well-prepared for upcoming technological advancements.

What's next?

Automating feedback mechanisms
Iterating
Exposing tools to more staff and customers
Monetise tools built on companies proprietary data
Revenue will create more opportunity to experiment

Playing the waiting game

As much as moving quickly is important, having the confidence to wait is undervalued in the current climate. I view these companies as the bravest and boldest of them all. Rather than wasting time continuing to tweak strategy and trying to keep up, being confident enough to wait while keeping options open is a great strategy.

Keys to success:

Keep current software up to date. Let the big players build value for you.
Watch your competitors closely and be ready to follow fast
The technical barrier to entry is low currently, but be ready for it to grow and become more expensive.

Where should your company be?

Contrary to popular belief, we shouldn’t all be DOing AI currently. Aside from being stuck on strategy all other points in the journey are great places to be right now. There will be benefits to being the first mover, however being ready to follow quickly is just as important. Taking the time to experiment and find the game-changing use case will avoid pouring money down the drain.

The one phase I’d advise getting out of is strategising. Look to industry for developments, unblock your innovators or be brave and save your time and resources and simply wait.

If you'd like some help navigating this journey or driving value out of each phase please get in touch!