Cracking the Gen AI code: how to get to the game the right way

Since ChatGPT's launch nearly two years ago, discussions about generative AI have intensified, and many anticipated workplace transformations are now becoming a reality.

The relentless attention to the subject, however, is compelling many businesses and professionals to implement the technology without enough understanding of its capabilities and limitations.

Some companies feel they must act even without a clear vision or the right team skills, but a hasty approach can lead to risks, wasted resources, and missed opportunities.

New skills

Generative AI is not merely a technological transition; it's a leadership and skills paradigm shift for everyone. Leaders need to develop new aptitudes to guide their teams effectively. While they don't have to become experts, a sound understanding of generative AI principles, capabilities, and limitations is critical.

As the technology disrupts existing processes, everyone who leads will have to become proficient at managing change and supporting employees.

Professionals of any level will also need to learn about the technology. Knowing how to use generative AI effectively and ethically is likely to become an expected skill, similar to familiarity with Microsoft's essential tools today. 

Successful generative AI implementation requires teams with diverse skill sets. Data scientists and analysts are key for developing and refining models. AI developers can ensure systems deliver actual solutions or address regulatory requirements.

Building or acquiring the right level of knowledge and competence is central to approaching the technology efficiently.

A well-balanced team should be able to identify and define the problems generative AI can solve, evaluate data validity, assess IT infrastructure, and choose the right path forward.

Results

Many industries are already benefiting from generative AI. It has shown great potential in improving customer service through intelligent bots or by providing professionals with faster, more tailored information.

In Australia, the Commonwealth Bank uses an AI-driven chatbot to enhance customer service. Telstra employs AI-driven predictive maintenance to prevent network outages.

According to one survey, half of Australian lawyers have already used generative artificial intelligence for day-to-day tasks. Generative AI can expedite legal research, generate summaries, and draft documents. Some professionals report that they now complete in 10 minutes jobs that, before the technology, would have taken 10 hours.

Multiple tools are available for businesses investigating the technology. Options range from individual subscriptions to models like ChatGPT (OpenAI), Gemini Advance (Google), or Anthropic, costing around AU$30 monthly, to enterprise solutions like Microsoft Copilot Studio or IBM Watson.

Pressure

Despite generative AI's significant benefits, businesses should avoid implementing it due to external pressure or because competitors seem to be doing it. 

It's best to identify projects offering clear value and start with a small pilot to test applications, allowing for learning and adjustment before scaling up.

Preparing for some of the technology's shortcomings is also needed. Even if generative AI can be more sophisticated than other types of AI models, it is still limited by the data sets it uses and the fact that, despite some impressive outcomes in natural language, it doesn't think or know what it is doing, as a human does. 

Depending on the inputs, it can, for example, be biased or make serious mistakes.   

Cultivating continuous team learning and adaptability is essential to understanding how to apply the technology. Only knowledge and foresight will ensure gains outweigh costs and minimise the risks, which can be significant. 

In February 2024, for example, Air Canada had to pay damages to a passenger after its AI assistant provided incorrect information about his eligibility for bereavement fares following his grandmother's death.

Last year, iTutor Group paid US$365,000 to settle a dispute with the US Equal Employment Opportunity Commission (EEOC). The federal agency said the company, which provides remote tutoring, used AI-powered recruiting software that automatically rejected female applicants above 55 and male applicants above 60.

Generative AI has the potential to revolutionise businesses, but it requires careful planning and execution to avoid such problems and create actual value.

By identifying specific uses, ensuring data quality, and acquiring the necessary skills and talent, businesses can effectively harness AI's power to unlock its full potential and change how they work. 

If you're interested in learning more about AI, check out RMIT Online's courses here.