Decidr

Fast, good or cheap — pick two.

This old school belief has long dictated how businesses approach production and service. The idea that all three could be possible was unfathomable.

Compromises and tradeoffs have therefore been baked into the very DNA of business ops.

Sure, a company could deliver high quality work quickly. But it wouldn’t come cheap. Yeah, they can provide great prices and speed. But the quality won’t be the best. Absolutely, you can get excellent quality at a great price. But you’ll have to wait awhile.

AI technology is changing this outdated reality – challenging the traditional belief that businesses must compromise between cost, speed and quality.

By leveraging AI properly, companies can have high standards when it comes to delivering quality products and services quickly and affordably. This is because AI, particularly broad AI, combines the best human capabilities with vast amounts of data that it can analyse quickly to exponentially improve suggestions and outcomes.

We’re no longer tapping into the vintage meme “porque no los dos” and instead saying “¿Por qué no los tres?".

The quality AI brings to the table

Nobody wants a crap product, which is why quality tends to be the cornerstone of a company’s value proposition. And AI can help with that, particularly when you let it analyse and learn from your datasets.

Unlike humans, AI can process and interpret data at incredible scale and speed – without human inaccuracy.

In the finance industry, the Commonwealth Bank of Australia (CBA) has adopted AI to streamline a variety of operations.

The integration of Microsoft's 365 Copilot resulted in 85% of employees saying they wouldn’t want to go back to working without the capability, with 96% reporting increased productivity.

This included engineers who took part in a 12-week Copilot for Github trial where almost 80,000 lines of code were recommended by the AI.

CBA's chief information officer, Gavin Munroe, said that AI has been integral to CBA’s strategy, with investments into the technology leading to innovations such as AI-driven fraud detection, which improved financial transaction protection by 35% in the first year. This led to roughly $10 million in savings.

“With the introduction of generative AI, it's just reaffirmed our position and we see it as a critical enabler for making our customer's lives better and improving the experience with CBA,” Munroe said.

AI can also speed up operations by automating routine tasks, allowing for faster customer service and decision making. Tasks that once required human intervention can now be handled by AI, freeing up human resources for more complex, creative and frankly more fun endeavours.

In the retail sector, companies like Zara use AI to predict fashion trends and analyse customer data to help manage inventory more effectively. This helps the company reduce waste and ensure that it has the right products in stock at the right time.

Qantas also uses AI to optimise flight schedules and improve operational efficiency. By analysing vast amounts of data (including weather patterns), AI helps Qantas minimise delays, optimise fuel consumption and enhance the overall travel experience for passengers.

This not only speeds up its international operational processes but also leads to cost savings and better overall resource management.

What about the law of diminishing returns?

The Law of Diminishing Returns says that adding more resources to a project eventually results in proportionally smaller improvements in output.

Another way of looking at this theory is that in a team, scaling up can lead to inefficiencies and unmanageable complexity.

We’d argue that AI circumvents this by maintaining high levels of effectiveness, even when applied to large scale projects.

This can be seen in Google's use of DeepMind AI to manage the energy efficiency of its data centres. And this was all the way back in 2016! Google applied machine learning algorithms to analyse data from thousands of sensors within its data centres, leading to a 40% reduction in the energy used for cooling.

This significant improvement was achieved without the need for proportional increases in human resources or other inputs, demonstrating how AI can be used at scale for efficiency and effectiveness – even when applied to large and complex operations.

Investors and early adopters have also recognised AI's potential to redefine business success, and made it an essential component to their business strategies. You're here so perhaps you've taken the first important step.