Michael Wegmüller has more than 20 years of experience in AI. He is Co-Founder of Artifact SA and a widely recognized AI business expert.
The advancements in GenAI in 2024 have demonstrated that the technology is no longer just a buzzword but rather a useful tool for businesses across various industries. From the improved reasoning capabilities of LLMs to specialized AI agents designed for industries and functions, GenAI seems here to stay. Based on my experience working with AI over the last 20 years, here is a look at how we got to where we are now, as well as what business leaders can do to enhance their AI adoption in the coming year.
The Journey So Far
The introduction of GPT-1 was a step toward an AI that can reason and solve problems more effectively (especially in math, science and coding). VCs and investors have further increased their bets into large-scale language models, and we have seen increasing investments into AI agents tailored to specific business needs. Specialized GenAI solutions are being designed to address industry challenges across all sectors and professional services, demonstrating that the technology is not just a general-purpose tool but also useful for serving businesses and augmenting employees.
Another example of latest advancements are AI-driven video generation tools like Sora from OpenAI. While many initially assumed that such technology would require several years to go public, it is now possible to transform text prompts into video clips, using diffusion models combined with transformer architecture. The research departments of Alibaba and Microsoft have also shared advanced research that is able to generate a video from a simple image and an audio track, ready for innovative storytelling approaches.
The significance of AI development was also underscored by two Nobel Prizes awarded in 2024. This recognition highlights not only the transformative potential of AI across various domains but also its capacity to address some of society’s most pressing challenges. A Chemistry Nobel was awarded to Demis Hassabis and John Jumper, along with David Baker, for their algorithm AlphaFold, which has revolutionized our understanding of protein structures, providing insights that are important for drug discovery and addressing complex biological questions. A Physics Nobel was awarded to John Hopfield and Geoffrey Hinton for their foundational contributions to machine learning through artificial neural networks.
A Game Changer For Businesses
In 2024, GenAI became mainstream for employees as many organizations released in-house AI solutions that provide ChatGPT-like functionalities. These tools are typically focused on enabling safe usage within corporate boundaries while ensuring compliance with data protection regulations and securing the company’s intellectual property.
About 75% of surveyed companies have adopted GenAI technologies, according to the recent IDC study, indicating a increasing integration into their operations. This widespread acceptance reflects a growing recognition of AI as a core technology, important for competitive advantage.
However, the adoption of AI presents an important challenge for executives. As organizations increasingly recognize the transformative potential of GenAI, they are also encountering various barriers that may slow down its implementation. Some of these concerns include employees’ fears about AI’s impact on their roles; uncertainty about ROI; and issues like missing ownership, poor governance or incomplete specifications leading to underperforming projects.
Global Powers Shaping The Future Of AI
In 2024, both the U.S. and China accelerated their efforts to lead the AI sector, while Europe has been enforcing new regulations. AI has entered the field of geopolitics, and the dynamics will need to be further followed over the coming years.
The U.S. government has prioritized AI innovation through substantial investments and initiatives aimed at fostering a robust domestic AI ecosystem. This includes partnerships with tech companies and research institutions to enhance capabilities in various fields of AI.
Conversely, China continues to leverage its vast resources and state support to advance its AI technologies, focusing on applications that can enhance national security and economic growth. The competition between these two superpowers is not just about technological advancement but also about establishing global standards and influence in AI governance.
Amid this competitive backdrop, the EU has taken a proactive stance with the implementation of the EU AI Act. This legislation aims to position the EU as a leader in ethical AI development by emphasizing governance frameworks that prioritize data protection and ethical considerations. This act establishes guidelines for AI usage across sectors to help ensure that these technologies are developed responsibly and transparently.
I believe the EU’s approach should serve as a model for balancing innovation with ethical responsibilities and addressing concerns about privacy, discrimination and accountability in AI systems. This regulatory framework is particularly relevant as organizations worldwide seek to adopt AI technologies while navigating complex ethical landscapes.
Strategies For Effective AI Adoption In 2025
As we reflect on the transformative advancements in GenAI throughout 2024, I believe it’s become clear that the technology is no longer just a passing trend but rather an important asset for driving business success. To effectively harness this potential, companies can adopt strategic approaches that facilitate AI adoption within their operations. Here are a few that I have found to be effective:
• Focus on problem resolution first. Start to implement projects in phases, and address specific business problems that have a wider usage first.
• Engage your employees. Develop a culture that supports AI adoption. Help employees understand the benefits of this technology for their jobs, and pursue its acceptance across all management levels.
• Facilitate employee training. As AI solutions become more specialized, companies will need more advanced skills to identify and shape future solutions that will generate business impact. That is why upskilling is important for key roles such as sales.
• Create strong AI governance frameworks. Future solutions will likely help break silos to empower omnichannel strategies. Ensure your company is implementing resilient governance structure and processes that will help foster collaboration and accountability.
Conclusion
Organizations can adopt a proactive approach to AI implementation by focusing on problem resolution through phased projects and by establishing robust governance frameworks. By addressing smaller, high-impact business challenges first, you can build confidence in AI solutions while ensuring that your employees are equipped with the necessary skills to thrive in an evolving landscape. Ultimately, I believe that embracing these strategies can not only enhance organizational effectiveness but also prepare businesses to leverage AI’s full potential for future growth and innovation.
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