AI Insights, MAY 2024

AI trends in 2024

Navigating the landscape for business success with AI in 2024

This blog post includes insights from 2021.AI’s Chief Data Scientist, Björn Preuß and summarizes the key takeaways from AI Watch Episode 15 featuring Henrik Fabrin.

The rapid advancements in Artificial Intelligence (AI) are transforming the business landscape. Below is a breakdown of key considerations for businesses of all sizes to navigate the exciting world of AI and achieve success in 2024.

The generative AI boom and responsible use

The widespread adoption of generative AI models in 2023 has brought significant benefits, but also raises crucial questions about responsible use and ethical considerations. Businesses must now strategically plan how AI will impact their industry and develop strategies to leverage its power while adhering to regulations like the EU AI Act. Get help navigating the EU AI Act here.

The easy access, versatile use, and endless application of LLMs have made them very popular, and not just among technical people. This popularity has triggered changes in guidelines, regulations, and has led to leadership thinking not only about the benefits but also the risks of such systems. This shift in perception will continue in 2024 with decision-makers being more thoughtful when implementing such systems. This however, will not limit the value one can get out of the systems but just lower the value at risk.

The AI divide: large vs. small businesses

There is a significant difference between large and small businesses regarding AI strategy and resources. Smaller businesses may have limited resources to invest in customized AI solutions. Standardized solutions can be a viable option for them to address the disparity and gain the benefits of AI. As Henrik Fabrin stated, “AI will lift everyone, the good actors and the bad actors. If we disregard the bad actors and then talk about good actors, everyone wants to do it in a good, proper, safe, secure, responsible way. And the better the tools are to help them do that, then great! If it costs a zillion dollars to do, then it’s only the large corporations [that will benefit], then the SMEs are at a disadvantage.”

In 2024, we still see a strong focus within SMEs on value creation on use cases, concentrating on the construction of models and their successful integration into processes and products.

Conversely, larger organizations exhibit a higher level of maturity in model development. Despite this, hurdles remain, particularly when bringing models into production. This is primarily due to regulatory and process-related challenges rather than technical knowledge or monetary resources.

Flexibility is key

Openness and flexibility are paramount for successful AI adoption. Companies should avoid vendor lock-in and maintain the ability to switch models as AI technology rapidly evolves. This allows them to stay adaptable and leverage the latest advancements. Having solutions based on open source components also ensures compatibility with other procured systems that will share the same standards.

However, alongside the quest for flexibility, there is also a need for standards and for support and SLA’s. Raw open source projects will not be the first choice in larger organizations given the cost and uncertainty connected to the maintenance. Even though that flexibility and a reduction in vendor lock-in is important, total cost of ownership will remain a significant factor.

Compliance and responsible AI is a must

With the growing influence of AI, compliance and responsible use must be top priorities. Businesses need to ensure the ethical deployment of AI models. Tools and expertise offered by companies like 2021.AI play a crucial role in helping businesses achieve this objective.

In 2024, regulations and frameworks will be updated and more concrete guidelines will be posted. This means that companies start to gear up on their effort of implementing processes to ensure control over their model portfolio. This commonly grows as more use cases are developed and AI becomes the norm in self-built software and procured software.

Bridging the gap

Many companies are already unknowingly using AI in their everyday operations. But the number of models and their purpose is not known, which could pose governance challenges. Furthermore, there’s a need to bridge the knowledge gap between tech-oriented and less technical companies, which often correlates with the company size. “I’m a big believer in an AI-assisted organization. So everyone from CEO to intern will use different types of AI, different types of models, depending on the different tasks they have throughout the day. And they will also bake AI into their products that they service to their companies,” envisions Henrik. This thought highlights the all-encompassing nature of AI in future organizations, regardless of technical expertise. Clear guidance and readily available tools and solutions are essential to empower these companies and enable successful long-term AI adoption.

By embracing these considerations, businesses can navigate the dynamic and opportunity-rich landscape of AI. Prioritizing responsible use, leveraging the right tools, and maintaining flexibility are key to harnessing the power of AI and achieving success in the years to come.

You might also like…

You might also like - AI deployment

Leveraging AI TRiSM for trustworthy and safe AI implementations

In today’s rapidly evolving digital landscape, the adoption of AI technologies is no longer just an option but a strategic…


EU AI Act download

The long-awaited EU AI Act: A comprehensive timeline and preparation guide

The European Union’s AI Act (EU AI Act) is a landmark piece of legislation that aims to establish a framework for…