AI Adoption Across Industries – Which Sectors Are Gaining the Most Advantages?
Following the public availability of generative artificial intelligence (AI) around the end of 2022, it has quickly become the most disruptive global trend since the invention of the Internet.
Within that disruption, generative AI is driving mind-blowing increases in the speed, productivity, and efficiency for businesses across all industries.
Clearly, AI presents a tremendous opportunity for businesses to save time and money, and to allow employees to spend more time on higher-value tasks. But is the reality matching the hype?
Olivia Gambelin, author of Responsible AI: Implement an Ethical Approach in Your Organization, explains, “The adoption of large language models (LLMs), generative AI, and similar solutions undoubtedly offer great benefits to businesses. But we’re still in very early stages. Over the past year, it may have sounded in the media like this technology is already widespread and widely used but, in reality, there are a lot of challenges that are still holding enterprises back from being able to engage with it.”
Here’s how generative AI and intelligent automation are set to have the most transformative impact on businesses in 2024.
AI in Financial Services
The financial services sector has been cautiously experimenting with generative AI for over a year now.
Some examples of the tasks that tools like ChatGPT have augmented in financial services organizations include summarizing large, complex documents into succinct high-level notes, correcting erroneous spreadsheet formulas, summarizing recent macro trends, exploration of financial concepts, and repetitive tasks like data analysis.
Of course, ChatGPT is a publicly available tool. It’s also important to consider that many large enterprises will want to build their own proprietary LLMs internally for a variety of reasons, such as business-specific use cases and data protection. Unsurprisingly, many tasks and processes within financial services organizations have not been suitable for augmentation with tools like Chat GPT yet due to the risks and sensitivity of the data.
AI in Healthcare
AI is being used to read X-rays and MRI scans, then provide a preliminary diagnosis at a rate much faster than doctors can hope to meet. These AI algorithms can interpret medical images, detecting and diagnosing conditions with the great accuracy and efficiency.
Similar capabilities in analyzing large sets of data will provide benefits in a number of other areas, such as research into diseases and drug discovery processes. LLMs can be fed vast amounts of data on past patient cases to improve treatment and deliver bespoke services tailored to specific illnesses or injuries as well.
A valuable function of AI algorithms across many industries is their ability to make predictions from highly sophisticated analytics. Predictive analytics can enable healthcare providers to be proactive, rather than reactive, in their treatment of patients, which will improve their ability to intervene at earlier stages of cases and save lives.
AI in the Supply Chain
Global supply chains, serving all industries, have gained enormous increases in speed and productivity from AI, among other advantages.
For example, a U.S. regulation within drug and medicine production has recently been introduced, called the Drug Supply Chain Security Act. This requires manufacturers to demonstrate full control over the supply chain, no matter where in the world the raw materials are produced, all the way through to the patient.
AI tools have allowed manufacturers to monitor, track, and visualize every step of production in real time.
This advanced monitoring and automated functionality is commonplace these days, allowing highly complex global supply chains to run more efficiently than ever before. Capabilities like predictive analytics can also prevent machinery from failing, then autonomously replace parts to eliminate unplanned downtime.
On the logistics side of the supply chain, AI-powered data analysis can be used to optimize the cost and speed of shipping and delivery of materials.
AI in Manufacturing
Manufacturing businesses have been leveraging intelligent automation for decades, with many similar use cases to those that are enhancing the supply chain. The introduction of LLMs and generative AI, however, is set to take that to an entirely new level.
Tamas Toth, an enterprise IT leader with more than 20 years of experience, explains, “AI gives manufacturing organizations a further boost to their ever-ongoing efforts to optimize in key areas like energy efficiency and sustainability, process automation and improvement, predictive maintenance, warehouse operations, interdependent systems planning, delivery fulfillment and logistics, and strategic data-driven decision making.”
“In manufacturing and supply chain, AI technology won’t redefine the landscape,” clarifies Toth. “Rather, it empowers leaders to realize long-standing goals with newfound precision and efficiency.”
AI in Retail
Like manufacturing, retail businesses have already been leveraging AI for many years.
Susan Sly, Co-Founder of RadiusAI, an AI-powered real-time data analytics platform, is another who believes the hype may still be outpacing the reality for some businesses, though. She says, “Currently, expectations are often greater than AI capabilities. My advice is to start with one problem area, select one item in which speed or efficiency could significantly improve profitability, and start there.”
“An example is using computer vision to solve food waste in convenience or quick-serve restaurants with real-time alerts for re-stocking, as opposed to having a timed restock that might not correlate with demand.”
Still, for enterprises like Amazon, widespread adoption of AI and intelligent robotics have played a crucial role in transforming them into the global juggernauts they are today. For instance, Amazon currently uses around 750,000 mobile robots to fulfill customer orders around the world. And 75% of Amazon’s customer orders globally are delivered with the assistance robots.
AI in Other Industries
In the legal industry, 2023 saw the first legal contract negotiated and agreed upon by AI tools without any human involvement. Law is seen as one of the sectors that stands to gain the most from generative AI, due to its ability to process and analyze enormous volumes of data or written content in mere seconds, among other use cases.
Regarding other industries set to gain transformative advantages from AI, Susan Sly adds, “I’m personally fascinated by what AI is doing in agriculture. For instance, computer vision applications on tractors, or increased accuracy for tilling soil. AI is increasingly helping farmers become more efficient.”
“AI will also be able to be prescriptive to farmers in terms of what to plant, when to plant it, which types of animals to have, when to rotate them, and how to optimize their land. We all need agriculture to survive, and farmers have such low margins, are weather-dependent, and candidly do not get the respect they deserve. I think AI will help to optimize farming in ways that we cannot yet fathom, and this will ultimately be attractive for people who want to pursue careers in agriculture.”
For professions like engineering and software development, generative AI has unlocked great opportunities for accelerated work and creative innovations. However, some professionals still fear it could create challenges with finding work in the future, as businesses recognize that specialist skills have become far easier to supplement with AI tools.
Olivia Gambelin says, “When Chat GPT first came out, I saw a clear divide in the engineering profession. Some were afraid they’d completely lose their jobs and reacted negatively. But the more confident and open-minded engineers viewed Chat GPT as an enabler to push boundaries and improve their ability to work.”
This example highlights a valuable lesson. AI is only going to gain more momentum in the coming years, and continue to disrupt the way people work and businesses operate.
For businesses and individual workers alike, those who ignore this trend or take a negative stance will inevitably fall behind.