According to McKinsey research, generative AI is predicted to add trillions of dollars in value to the global economy by 2030. With the buzz in 2023, Gen AI has caused a complete watershed moment. The environment is just supercharged! It is nothing short of revolutionary. Anyone can use it without much technical knowledge or formal training. It is embedded in almost all the tools one uses—emails, word-processing apps, meeting software, and more. That already speaks volumes that it is set to transform how everyday people go about their work. However, it is in its nascent stages. It is only going to get more focused and intelligent. Generative AI and human ingenuity can augment the business world and workforce tremendously. It can boost employee experience, empower managers and also prompt senior leaders to lead differently.
From writing code, designing products, streamlining operations, analyzing documents, developing strategies, creating multimodal content, servicing customers via gen AI chatbots, and even expediting scientific discovery, Gen AI is a multi-potentiality when unleashed with humans-in-the-loop or even on its own. Among all the things, we know that customer service – a human-heavy workload will change. Some questions, however, arise- such as getting data together from disparate systems and how to figure out the ‘garbage in, garbage out’ puzzle. Let us find out the top 6 generative AI trends for 2024 and how they will be game-changing ahead.
Top 6 generative AI trends to look out for in 2024
Open-Source AI models
Open-source pre-trained generative AI models are gaining traction in 2024. These models enable businesses to boost their growth by integrating them with private or even real-time data. The collaborations skyrocket productivity and cost efficiency. What is open-source AI? They are AI models whose source code is available, allowing developers, researchers, and organizations to access, have clear visibility of their work, and collaborate. The developers can also customize to suit their specific needs. In the landscape of massive generative AI models, many enterprises such as Databricks advocate for enterprises to leverage open-source AI models – as they can offer greater control and customization.
For instance, MedPerf compiled by ML Commons Association targets to solve the data impasse by applying ML in medicine. It enables a ‘federated’ training approach where developers can test programs on real-world data while keeping the patient data private. No clinical data is shared with external organizations, while developers and clinicians collaborate over this secure platform. This initiative has been successful in radiology and surgery and is transitioning from the alpha to beta stage. This collaborative AI development without compromising data privacy can unlock several challenges in adopting medical AI. Moreover, enterprises can use tailored models for specific tasks.
Small language models
2023 can be the year of LLMs, but in 2024, the focus is shifting to SML or small language models. Trained on limited datasets, but nonetheless high-quality authoritative content such as journals and textbooks, SLMs can generate content of comparatively better quality and devoid of the noise that LLMs often introduce. Their parameters are smaller, and so are their storage and memory requirements. The result is that they can run on less power-intensive and less expensive hardware. Enterprises can finetune SLMs tailored for their domain-specific tasks, such as meeting legal and regulatory requirements. Microsoft’s PHI-2 and Mistral 7B are two promising SLMs that already stand out to fuel potent Gen AI applications ahead.
Autonomous agents
Generative AI models are undergoing another paradigm shift with autonomous agents. These agents are software programs built to execute and accomplish specific tasks. As a result, you will not need traditional prompt engineering in generative AI. These agents harness data to learn, adapt to new situations, and make decisions all on their own, without having humans. For instance, OpenAI has provided tools such as custom GPTs that allow the effective use of autonomous agents.
By engaging in smart and responsive interactions, autonomous agents can benefit customer experience tremendously. With their high contextual knowledge, the agents can be highly beneficial to specific industry sectors such as travel, hospitality, retail, education, and more.
Multimodal generative AI
The generative AI technology is moving beyond its text-based language. It embraces multimodal languages, integrating text, speech, images, audio, and video into its mix. The users can mix and match content based on the varied modes to prompt and generate content. For example, in a customer service call, the AI algorithm can analyze the customer’s verbal request (audio), evaluate their financial documents, and even assess the facial expression in the video. By analyzing the data points from audio, text, and visual cues, the AI can generate better-tailored financial advice with precision. Thus, harnessing several AI techniques such as natural language processing, computer vision, and machine learning, it can make better data-driven decisions, interact with accuracy, and take actions that lead to better results.
In 2024, multimodal Gen AI is anticipated to evolve substantially and unleash new generative AI capabilities. ChatGPT Plus is already immensely popular among its subscribers because of its multimodal features. The multimodality of the Gen AI makes it much more dynamic and intuitive. We can expect the rise of open-source models such as Large Language and Vision Assistant or LLava in 2024.
Customizing Enterprise AI
A key trend of 2024 is enterprises seeking tailored generative AI applications to meet their specific needs. These applications integrate proprietary data and result in accurate and relevant responses. The trend signifies a shift towards efficiency and personalization in AI-driven business solutions. It can cease from being a generic tool to a highly specialized strategic application. Especially when generative AI can play a significant role in customer service, boosting engagement, and streamlining operations, having a customized Gen AI for the enterprise can give a competitive edge in the ever-evolving business scene. For example, in Brazil, the AI can focus on warmth and engagement, whereas in Japan, it can prioritize precision and efficiency based on regional cultural nuances and customer habits.
AI governance
As more enterprises adopt generative AI internally, the significance of having robust AI governance is paramount. There are several risks associated with individuals using Gen AI for personal use or using any mainstream or experimental AI for doing their business tasks that organizations do not permit. To address these risks, organizations are investing in governance and compliance. It can involve flagging inappropriate prompts, monitoring internal AI usage, and staying abreast of the latest government regulations. Moreover, insurers may soon introduce policies to protect against Gen AI-induced hallucinations, recognizing the evolving risk permutations.
Similarly, there is a growing emphasis on AI safety and ethics. The AI Safety Alliance, formed by industry leaders, aims to promote responsible AI innovation, ensuring trust, security, diversity, and economic competitiveness. It also establishes global benchmarks and standards, promoting open innovation in AI development. Likewise, the European Union has approved the first AI Act to regulate and ensure that the AI systems used in the entire EU region are responsible, safe, and ethical to prevent risks of AI malpractices.
How can we help?
2024 will be another disruptive year when it comes to the practicality and adoption of Gen AI in the enterprise segment. The floodgates of generative AI have just opened in 2023. The trends predicted are, in fact, a roadmap for innovation and development. With responsible use of Gen AI and the right blend with human ingenuity, enterprises can unlock a new era of innovation. Are you a business leader looking forward to incorporating Generative AI in your enterprise to drive value? Look no further. At Saxon AI, we have Gen AI COE, where we find your business use case and develop custom solutions tailored to propel business growth.
