Artificial Intelligence (AI) has the potential to revolutionize traditional organizations across industries. However, many businesses are facing challenges and limitations when it comes to implementing AI effectively. In this article, we will explore the key issues that traditional companies face in adopting AI due to unclear strategies, and how these challenges can be overcome.
The Potential of AI in Traditional Companies
Traditional organizations have high hopes for AI and its ability to enhance operations, improve efficiency, and drive innovation. However, strategic shortcomings are severely restricting their ambitions. According to a recent report by Silo AI, a Finnish startup specializing in bringing AI into established businesses, unclear strategies and absent executives are holding companies back from fully harnessing the potential of AI.
The report analyzed various traditional businesses and organizations across industries, including manufacturing, construction, financial services, and the public sector. Despite the median age of these companies being 87, all of them were engaging with artificial intelligence at some level. Nearly 70% of these organizations have experiments or projects in development, and 86% expect their projects to progress into production within the next 12 months. However, the success rate of these initiatives is not always satisfactory, with almost half of the respondents feeling neutral or dissatisfied with the results.
Challenges Faced by Traditional Companies
Silo AI’s research reveals that unclear strategies and absent executives are major obstacles for traditional companies in effectively implementing AI. Most of the surveyed organizations lack a C-level representative who is responsible for data and AI management. Additionally, the majority of AI projects are managed locally within each business unit, creating a fragmented and uncoordinated landscape.
This fractured approach to AI implementation leads to several problems. One significant risk is that data management becomes unstructured, and governance becomes unclear. Peter Sarlin, the CEO and co-founder of Silo AI, points out that investments in AI and its integration are often relegated to different silos within the organization. This fragmentation hinders the organization’s ability to leverage AI effectively and limits the overall value it can derive from AI initiatives.
Overcoming Challenges and Maximizing AI Adoption
To overcome these challenges and maximize AI adoption, Silo AI advises traditional companies to adopt a holistic approach and make someone in the C-suite responsible for incorporating AI into the organization’s strategy. This ensures that AI initiatives are aligned with specific business objectives and priorities. By having a dedicated executive overseeing data and AI management, organizations can streamline their AI efforts and create a unified approach.
In addition to a clear strategic direction, Silo AI suggests several specific measures for traditional companies to enhance their AI adoption. One such measure is creating frameworks to assess the return on investment (ROI) of AI projects. The research shows that organizations with established ROI frameworks are more likely to be satisfied with their AI initiatives. These frameworks enable companies to evaluate the impact and effectiveness of AI projects, making data-driven decisions about their future investments.
Another crucial step is establishing an AI center of excellence within the organization. These centers work collaboratively with different departments to promote accessibility and cost-effectiveness of AI projects across the entire company. By centralizing AI expertise and resources, organizations can avoid duplication of efforts, share best practices, and ensure consistent implementation of AI technologies.
Long-Term Perspective for AI Success
While implementing AI in traditional companies requires a long-term perspective and significant effort, it offers substantial value when integrated into core products, services, or processes. The true potential of AI lies in its ability to learn and improve over time, generating more value as it becomes more widely used and people become more comfortable with its capabilities.
However, it’s important to note that successful AI adoption does not happen overnight. The deployment of AI at the core of an organization’s operations requires careful planning, investment, and continuous evaluation. Organizations should embrace a culture of learning and adaptability to fully leverage the benefits of AI and stay ahead in today’s competitive landscape.