Artificial intelligence (AI) is the science and engineering of creating machines
and systems that can perform tasks that normally require human intelligence,
such as perception, reasoning, learning, and decision-making. AI has been
advancing rapidly in recent years, thanks to the availability of large amounts
of data, powerful computing resources, and innovative algorithms.
AI can be divided into two categories: general AI and applied AI. General AI is the hypothetical ability of a machine to perform any intellectual task that a human can do. Applied AI is the use of AI technologies to solve specific real-world problems in various domains.
Applied AI can bring many benefits to businesses and society, such as automating tasks, enhancing capabilities, and improving decision-making. However, applied AI also poses some challenges and risks, such as ethical, technical, and social issues. Therefore, it is important for businesses and society to understand the potential and limitations of applied AI, and to adopt best practices and standards to ensure its responsible and beneficial use.
In this blog post, we will explore some examples of applied AI in different industries in Australia. We will also discuss some of the benefits and challenges of AI adoption for businesses in Australia.
Marketing
Marketing is one of the domains where applied AI can have a significant impact on you. Applied AI can help marketers better understand their customers’ needs, preferences, and behaviours; tailor their products and services to their customers’ segments; optimize their pricing and promotions; personalize their communication and engagement; measure their performance and impact; and innovate their campaign strategies and increase their effectiveness.
For example:
Koala: is an Australian online furniture retailer that uses applied AI to optimize its customer experience. Koala uses machine learning algorithms to analyze customer data from various sources (such as web analytics, and social media reviews) to segment its customers based on their demographics (such as age group), psychographics (such as personality traits), behaviour (such as purchase history), and feedback (such as satisfaction ratings).
Koala then uses these segments to customize its website design (such as layout), product recommendations (such as mattress size), pricing (such as discounts), and communication (such as email campaigns) for each customer segment.
Quantium: is an Australian data analytics company that uses applied AI to help its clients improve their marketing effectiveness.
Quantium uses machine learning algorithms to process large amounts of data from various sources (such as transaction records) to generate insights into customer behaviour (such as purchase patterns), market trends (such as demand fluctuations), competitor actions (such as price changes), and external factors (such as weather conditions). Quantium then uses these insights to provide its clients with predictions (such as sales
forecasts), recommendations (such as optimal product mix), and optimizations (such as dynamic pricing) for their marketing decisions.
For example:
Titomic is an Australian additive manufacturing company that uses applied AI to revolutionize its production process. Titomic uses machine learning algorithms to analyze production data from various sources (such as sensors, cameras, scanners) to segment its production parameters based on their material properties (such as density, strength, durability), product specifications (such as shape, size, function), production requirements (such as speed, cost, efficiency), and production feedback (such as defects, errors, failures). Titomic then uses these segments to customize its production process (such as nozzle design), production control (such as temperature,
and pressure), production optimization (such as layer thickness), and production evaluation (such as quality testing) for each production segment.
