The automotive industry’s AI future holds great promise, with advancements aimed at enhancing driving, development, manufacturing, marketing, fuel efficiency, safety, and even sales. As AI integration burgeons in vehicles, projections suggest that by 2030, AI technology will be ubiquitous in 95- 98% of new cars [1]. The integration of autonomous robots and machine learning in the automotive industry–exemplified by Ford’s use of Cobots for efficient car sanding and BMW’s AI-driven robots in Spartanburg–enhances productivity, reduces environmental impact, and generates significant cost savings. Mercedes-Benz’s collaboration with NVIDIA for digital twin technology in its MO360 system streamlines supplier coordination, halving the process time [2]. This sector’s robust adoption of AI technologies is underscored by a projected market value of $7 billion by 2027 [3], making it a frontrunner in AI-enhanced manufacturing. Automation is set to reduce costs while simultaneously enhancing performance and efficiency.

Gartner reports that chief supply chain officers (CSCOs) are expressing concerns regarding their supply chains’ capacity to manage forthcoming challenges within the next two years [4]. AI is revolutionising the manufacturing sector by introducing predictive maintenance to foresee and mitigate machinery failures, employing computer vision for impeccable quality control, and optimising supply chains for unprecedented efficiency. Additionally, AI-driven robotics and automation enhance production capabilities, allowing for the creation of more sophisticated and customised products. This integration of AI not only boosts operational efficiency but also significantly reduces costs and improves product quality across the manufacturing landscape. Yet, AI isn’t all-knowing, and it’s doubtful we’ll be kicked to the curb anytime soon. But take it from me, supply chain management using AI is about to make the version without it look like it’s still chiselling on stone tablets.

In the finance industry, AI is poised to enhance data analysis capabilities, automate processes, and deliver personalised financial services. AI algorithms will enable financial institutions to extract valuable insights from vast amounts of data, improving risk management, fraud detection, and customer segmentation. Automation of routine tasks will increase efficiency and reduce operational costs, while algorithmic trading will optimise investment strategies and market efficiency. AI chatbots and virtual assistants have already changed the customer experience, but it will get even better with the proliferation of large language models able to personalise support and resolve issues in real time. However, challenges such as regulatory compliance and the need to upskill employees remain important considerations for the successful integration of AI in finance. According to Gartner, only 10-30% of companies have reported significant financial gains from using AI [5]. Lack of expertise and employee acceptance rank among the top reasons for minimal financial returns on AI investments.

Agriculture and horticulture are key pillars of Aotearoa New Zealand’s export economy. However, the agricultural sector in Aotearoa New Zealand faces persistent challenges such as climate change, sluggish productivity growth, labour shortages, mounting regulations, and the imperative of environmental sustainability. AI adoption in agriculture is still in its infancy on a global scale and remains similarly nascent in Aotearoa New Zealand. Predictions suggest that the implementation of AI in agriculture could add up to US$486 billion to the global economy [6]. This includes utilising AI-powered sensors and drones for precision farming, employing AI algorithms for crop monitoring and management, implementing livestock monitoring systems with AI-powered sensors, optimising supply chain logistics using AI-driven predictive analytics, deploying smart irrigation systems based on AI technology, utilising AI for weed and pest control, and leveraging AI for crop breeding and genetics research. These applications of AI can help farmers in Aotearoa New Zealand make data-driven decisions, optimise resource use, and improve agricultural outcomes.

I am personally excited about the potential AI holds for education, a realm in which I proudly wear the hats of a lifelong learner and a teacher. Witnessing the transformation AI will bring to our educational landscapes–reshaping learning processes, altering expectations of teachers and students, revolutionising exam systems, and streamlining institutional operations–is nothing short of thrilling. Imagine the possibility of personalised, stress-free learning journeys where new courses are just a click away, thanks to AI’s guiding hand. We’re on the cusp of welcoming AI-based educators who could transcend human limitations in availability, objectivity, specialisation, and endurance. It’s not just students who stand to gain; teachers, too, can harness AI’s power to redefine educational experiences, as showcased by innovations like Khan Academy’s Khanmigo and the Duolingo app. The future of education, powered by AI, is bright and incredibly close!

AI is on the brink of reshaping life in myriad ways, revolutionising industries, refining operations, and elevating everyday convenience and customisation. Summarising its vast impact is challenging. Every sector is evolving positively, yet the issue of privacy looms large. In the foreseeable future, it’s likely that companies will develop proprietary AI systems to prevent data leaks and ensure confidentiality. The smarter the input data, the more tailored and intelligent the output, moulding AI into the tool we desire it to be. So, get ready and let AI chauffeur you straight to your destination–just don’t forget to enjoy it along the way!