Traditional organizations have high hopes for AI, but strategic flaws severely limit their ambitions.
That’s according to a new report from Silo AI, a startup based in Finland. The company recently Large scale model (LLM) with multilingual capabilities However, it is primarily focused on implementing AI into existing businesses. This provides an opportunity for mainstream adoption of this technology. A new study provides a more detailed picture.
The report analyzed a variety of traditional companies and organizations. Silo looked at companies in a variety of industries, from manufacturing and construction to financial services and the public sector.Despite the median 87 years oldall of them were involved with artificial intelligence at some level.
Nearly 70% have experiments or projects in development, and 86% expect their projects to go into production within the next 12 months. Additionally, nearly two-thirds (65%) have previous AI projects already in production.
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However, their efforts are not always successful. Almost half of them feel at best neutral about the outcome.
Digging into the data, Silo found that companies were being held back by opaque strategies and lack of leadership. Most respondents do not have a C-suite representative responsible for managing data and AI, with the majority of projects being managed locally within each business unit.
This broke Landscape poses several problems.
“One of the risks is that data management is unstructured and governance is unclear,” Peter Sahlin, CEO and co-founder of Silo AI, told TNW.
“Another risk is that AI investments and AI integration become relegated to various silos and fragmented across the organization, while research and development is largely a centralized effort.”
To mitigate these risks, Silo advises making someone at the C-suite responsible for integrating AI into the organization’s strategy. All efforts must also be clearly aligned with specific business objectives.
Beyond the broader strategy, Silo suggests some specific measures. one is under construction A framework for evaluating the ROI of AI projects.
New research provides evidence of its benefits. More than a quarter of respondents have already implemented such a framework. However, 37.5% of organizations that are satisfied with their AI initiatives have developed these structures. Of those who feel neutral at best, only 15.7% feel that way.
Silo also advises organizations to establish an AI center of excellence. These departments work with various departments to ensure project access and cost efficiency across the company.
“This holistic approach allows organizations to get the most value from their AI investments,” said Sahlin.
The approach won’t bring results overnight, he added.
“It is becoming clear that, like any technology, there are no quick wins with AI.”
“AI’s potential for value creation is greatest when the technology is deployed at the core of products, services, and processes.
“This will take a long-term view and a lot of effort, but the more these products, services, and processes are used, the more comfortable people will be using them and the more the models will learn. The more you do and get better, the more value you create.”
