How AI will affect the global industry, in 2024

Global Industry, (2024) is a year of great uncertainty, and as such it will be a time for some companies to prosper it. Unlike other similar moments, at this moment, the correct implementation of artificial intelligence will be a differentiating element that will help decide which of these companies will take advantage of this moment.

In this post, I will tell you where companies will focus their AI efforts as they analyze big data and look for new revenue opportunities, in order to take advantage of this time of uncertainty. Did you sign up? Go for it.

Supply chain issues stemming from the global industry pandemic are affecting production in all kinds of industries. From cars to electronic devices, through furniture or even toilet paper.

At the same time, global industry food prices have jumped to their highest level in more than a decade, as worker shortages, factory closures, and high commodity prices wreck plans even in operations with more sophisticated logistics and forecasting.

Faced with this situation, many companies are starting to move to look for alternatives related to technology, which make them more competitive, as well as help them anticipate short-term trends and optimize their manufacturing processes.

According to a PWC survey that was carried out in mid-2021 among more than 1,000 companies globally, in nine sectors, including banking, health, or energy, it found that 86% of them were already prepared to make AI a “conventional technology”.

Based on what came out of that survey, as well as other related studies, we can determine, what the main predictions for 2024 for Artificial Intelligence in the global industry can be. Let’s see them.

7 main predictions about AI in the global industry, for 2024.

There’s a lot. Some in development, others already implemented and contrasted, but all of them are still not general in their use at an international level. Only a few companies are currently taking advantage of the opportunities offered by this technology.

Here I present some of the most talked about, and always based on various reports and opinions of experts at the international level. Let’s see what they are:

1. conversational AI.

Last year, conversational artificial intelligence was used mostly in the field of video games and entertainment. This was used above all to make video games more immersive by allowing real-time interaction with the different characters.

This 2024, is the year to also use it for the workplace. These new conversational artificial intelligence tools will allow us to work more efficiently and effectively, using natural language processing. Synthesized speech is poised to become as emotional and persuasive as the human voice by 2024, helping industries like retail, banking, and healthcare better understand and better serve their customers.

Going beyond natural language processing, companies that use both speech and text to interact with other businesses and their customers will employ AI as they go along with it, to understand the context or sentiment of what is happening. is saying. Is the customer frustrated?

Is your boss being sarcastic? Although in the Spanish language this is especially complex, the adoption of tools such as OpenAI Github copilot will be accelerated, which helps programmers to be more effective in their work related to this.

2. Programmable cars.

Every car lost value the moment it left the dealership, however, this will stop happening very soon. We will see more automakers move to reinvent the driving experience by creating software-defined architectures with the ability to support new applications and services through automatic over-the-air updates. Vehicles will get better and safer over time.

AI will help de-stress daily driving, for example, to the workplace. This artificial intelligence will act as a personal assistant, improving the journey in the vehicle, and providing a safer and more pleasant experience.

Vehicle occupants will have access to smart services that are always on, allowing them to use real-time conversational AI for recommendations, alerts, vehicle controls, and much more.

Additionally, artificial intelligence and data analytics will help train and validate autonomous vehicles for a wide range of driving conditions, providing everyday safety designed for the long haul.

3. Emerging standards for 3D focused on the Metaverse.

These advances will be aimed at the description of virtual worlds such as the Metaverse. Standards such as Universal Scene Description (USD) and glTF will rapidly evolve to meet the fundamental needs of Web3 and digital twins.

The rate of innovation in AI has accelerated throughout this decade, but AI cannot move forward without large amounts of diverse, high-quality data. Today, the data captured from the real world and labeled by humans is insufficient both in terms of quality and diversity, to jump to the next level of artificial intelligence.

In 2024, we will see an explosion of synthetic data generated from virtual worlds (If you want to know a little more about what the Metaverse will be like and its application in the area of ​​marketing.

4. AI4Science. AI will facilitate the discovery of new drugs.

In the last 25 years, the pharmaceutical industry has moved from developing drugs from natural sources (eg plants) to large-scale screening with chemically synthesized molecules. Machine learning or automatic learning allows scientists to determine which potential drugs are worth evaluating in the laboratory, and the most efficient way to synthesize them, generating, according to experts, up to a million new drugs.

AI will lead to breakthroughs in the discovery of new drugs and treatments and will revolutionize healthcare.

The category “drugs, cancer, molecular, drug discovery” received the largest amount of private investment in AI in 2020, with more than USD 13.8 billion, 4.5 times more than in 2019, for example.

The medical device industry has an innovative opportunity, enabled by artificial intelligence, to minimize and reduce costs, automate and increase accessibility, and continuously deliver innovation throughout the life of the product. Medical device companies will evolve from delivering hardware to providing software-as-a-service (SaaS) systems that can be updated remotely to keep devices usable after deployment.

AI will be deeply integrated with HPC (high-performance computing) and will enable scientific modeling and simulations at unprecedented scale and fidelity in areas such as weather and climate modeling.

5. Perimeter AI in manufacturing processes.

In this case, 5G technology may bring new opportunities for edge computing. AI – on-5G will unlock cases where edge AI could bring important solutions to the industry. This would pave the way for what is called “ Industry 4.0 ”: plant automation, factory robots, monitoring, and inspection, as well as facilitating autonomous systems on toll roads or in vehicle telemetry applications. In the same way, it will represent an advance in relation to intelligent spaces in retail, cities, supply chains, and even what is called the intelligent factory.

These factories use cameras and other sensors to perform inspection and predictive maintenance. However, detection is only the first step. Once detected, action must be taken. This requires a connection between the AI ​​application doing the inference and the monitoring and control systems, or OTs, that manage assembly lines, robotic arms, or pick-and-place machines.

6. AI to speed up service in businesses such as hospitality, retail, and logistics.

Customers increasingly demand faster service. For this reason, fast-food restaurants have been the first to implement AI for automated order-taking. That’s made possible by advances in natural language and speech understanding, combined with recommender systems. In this way, the ‘ fast food ‘ will implement automated order-taking to speed up delivery times and improve recommendations.

In supermarkets and big box stores, retailers will increase their use of intelligent video analytics to create automated checkouts and autonomous or cashier-less checkouts.

Logistics is another point in which AI will have special importance. And it is that, if we take into account that the strong point of artificial intelligence is in simplifying incredibly complex problems, as is the case of the supply chain, in this aspect it will have a lot to say. After the lack of supply that we are currently experiencing (see post “ The shortage crisis: Customer service as a solution ”), optimizing the supply chain, disposing of the product, and making much faster shipments, is going to be a critical area for development with AI, in the logistics sector.

AI can enable more frequent and accurate forecasting, ensuring the right product is in the right store at the right time.

In the same way, AI and Data Science will help in everything related to storage (autonomous forklifts, packaging automation…) and last-mile delivery (route simulations).

7. Unfreezing of Data Lakes as key elements in data analytics.

Data lakes have been a fundamental element since the beginning of Big Data work, however, they have been, so to speak, frozen, because they are isolated and decoupled from machine learning. However, these are very effective, as I have mentioned, in the large-scale data processing.

In 2024, data lakes are expected to be definitively modernized, through end-to-end data pipelines due to three inflection points: centralized infrastructure, the agility of applications based on Kubernetes, and the best storage adapted to the task from his class.

During the pandemic, as lockdowns became the new normal, businesses and consumers increasingly ‘digitized‘, providing and purchasing more goods and services online. This fact brought with it an exponential increase in data on these consumers, opening the door to a new use of this data that, together with Global AI, can open a new dimension and become the drivers of multiple applications in all sectors.

At the internal business level, artificial intelligence will mainly influence the automation of processes, preventing employees from spending too much time on repetitive work, and being able to focus on more creative tasks, for example. This will improve productivity.