AI Trends for 2024
2024 will see many question the trustworthiness of AI due to the hacking of databases and deep fakes spreading misinformation.
Open-source generative models were one of the top 10 most-favored projects on the code hosting platform GitHub this year, making them easier for developers to access and implement.
At the same time, shadow AI has emerged – employees using AI without IT oversight or approval and creating new security risks for organizations.
1. AI at the Edge
Artificial intelligence (AI) at the edge allows it to analyze data quickly without depending on network connections or cloud services, making it a powerful asset for companies across industries that need to respond rapidly to customer demands – retail, manufacturing and energy are just three industries that could benefit from using AI at its edge.
At a time when consumers expect hyper-personalized experiences from businesses, accessing data at the right moment allows businesses to deliver tailored experiences. Unfortunately, with large volumes of data often generated across multiple devices simultaneously being processed real-time can prove challenging.
Storage data in a centralized database presents security risks and may impede analysis processes, creating delays. Utilizing AI technology at the edge allows real-time processing of the data with reduced latency for improved performance and reliability.
Technology surrounding IoT devices has seen rapid expansion with increasing consumer demand for them. IDC predicted that by 2025 there will be 41.6 billion connected IoT devices producing 79.4 zettabytes of data each year – necessitating innovative strategies to analyze and process this vast trove of information efficiently.
An ideal application of AI at the edge is automotive manufacturing, where real-time data analysis is key. If an autonomous vehicle detects an imminent collision, for example, it must react immediately by applying brakes or even taking steps to avoid it altogether. AI at the edge ensures this crucial response takes place by quickly analyzing data and acting upon it within milliseconds.
Intelligent forecasting in energy involves using historical data along with weather patterns, grid health data points and other sources to optimize output, ensure stability and reduce human intervention. Predictive maintenance improves production line efficiency by detecting faults early and alerting management before they worsen into larger problems. AI at the edge is also effective at increasing safety in industries like oil and gas where equipment may be situated in remote locations by analyzing sensor data to detect any structural damages or fire hazards that might exist within equipment locations.
2. Augmented AI
As generative AI models continue to improve, their creative capacities will emerge as an enabler of creating novel forms of writing, music and digital art. Furthermore, Generative AI systems may assist businesses with advanced analytics, project management assistance, revolutionizing coding techniques and providing better healthcare and customer services; all proving themselves as disruptive trends to transform future businesses and technologies. This trend in creative capabilities marks a pivotal point that will transform how businesses and technology operate for decades to come.
AI should become accessible to a wider range of users. By making AI more easily accessible, this will reduce barriers to adoption and create opportunities for innovative uses cases like chatbots to automate common tasks more efficiently and save time in general. Furthermore, this democratization will facilitate AI becoming a collaborative partner that enhances productivity and decision-making within workplaces.
This new collaboration will accelerate the search for insights by streamlining data landscape, providing key information at precisely the right moment, and prioritizing fruitful paths of analysis. Furthermore, it will facilitate more dynamic and personalized experiences by understanding individual preferences and anticipating user behavior.
Attaining this objective requires shifting perspectives; from viewing AI as solely capable of performing lower-level tasks, to understanding its value in higher-level activities that demand creativity and emotional intelligence. Artificial Intelligence can serve as an indispensable asset in these higher-level activities due to its speed, precision, and ability to learn from past results.
Sales, marketing and customer service departments can use artificial intelligence (AI) as an ally in providing real-time insights that personalize user experiences more precisely. Pharmaceutical industry researchers can utilize AI technology to accelerate drug screening processes while simultaneously improving research efficiency thereby reducing drug discovery costs. The new paradigm will require an agile business strategy that optimizes efficiency while mitigating risks and cultivating a future-ready workforce. Furthermore, an ethical legal framework must exist in order to ensure AI serves humanity responsibly; initiatives like UK’s AI Safety Summit, Bletchley Declaration and formation of national/international regulatory frameworks have already taken steps toward this end.
3. The Better Together Story
GenAI has already produced tangible business benefits and is poised to see even greater expansion by 2024. GenAI is a potent tool proven to boost productivity and foster creativity; moreover, its promise of making businesses more agile, efficient, and responsive in an ever-evolving business landscape has been delivered on.
As this technology matures, its versatility has grown steadily; now being applied in areas as varied as drug discovery via faster molecular simulations, climate change modeling, and financial market analyses; customer experience improvement, as well as cost reduction for areas like logistics optimization and advanced material design, are just some of its many uses.AI at the edge is revolutionizing how we use technology, by placing intelligence closer to where it’s needed–in real-time at network edge nodes. This means less data travels across cloud systems and computations can take place on-site for faster results with reduced latency, efficiency gains and scalable solutions.
Another key trend to watch out for is the move toward open-source generative AI tools, which will foster a more democratic approach in the industry. While ChatGPT previously led AI advances and performance advancement, now more open source alternatives with impressive capabilities have made their mark and provide more flexible and cost-effective options for smaller entities looking to adopt the technology faster.
While generative AI continues to gain in popularity, its advancement will still be limited by a shortage of high-quality training data. We should expect 2024 to witness new models that can more efficiently learn from data, helping bridge this gap and lead to increased accuracy and sophistication in models trained.
Watch out for explainers – AIs that allow AIs to explain their results and rationale to nonexperts – which will become an increasingly vital capability across many industries, from law to medicine and insurance, where understanding factors that went into a recommendation is vital. They’re also making waves in academia where they could potentially mass-check papers for plagiarism or other IP violations and become invaluable allies for researchers as they work toward building more reliable models.
4. Integration
Artificial Intelligence is quickly transforming every aspect of business and daily life. While traditional narratives depict AI systems replacing human jobs with systems powered by artificial intelligence (AI), the real story is much more nuanced: AI will enhance humans’ capabilities while freeing them up for more strategic, value-adding tasks – this trend known as the better together story is one of the most significant and consequential AI trends of 2024.
In the cybersecurity space, for instance, generative AI tools will be employed to translate technical content for less tech-savvy employees, which will enable security teams to maximize the human element of their security technology by simplifying communication of complex machine-generated log data and analysis output into simpler language. It will also broaden non-security experts’ roles by giving them more advanced security tasks to perform.
As AI becomes mainstream, its development and deployment are being guided by robust legislative frameworks that ensure its responsible development and deployment. Countries worldwide are adopting comprehensive regulations to govern the ethical use, risk mitigation, transparency, and accountability of AI systems – an encouraging step that’s expected to help create an accountable AI landscape globally by 2024.
AI’s boundless potential is only equaled by its daunting realities – from hallucinating chatbots and expensive GPU chips to intellectual property and copyright challenges and intellectual property and copyright challenges.
Intellectual Property/Copyright issues, in particular, pose serious legal and liability concerns when creating AI-generated content such as art or music pieces, due to intricate algorithms that produce them; creating such work requires formulating mathematical equations that then feed into systems to generate final products which then poses numerous legal liability concerns, necessitating creative legal solutions in order to succeed.
Due to AI’s complexity, businesses must approach it with strategic agility and foresight if they wish to succeed in today’s AI-powered environment. Companies should understand how different technologies integrate together before selecting the most cost-effective ways to integrate them into products and processes – for instance, combining AR with AI could create interactive customer experiences; similarly, AI-enabled medical devices will revolutionize our lives.
